Description
Leveraging business intelligence management to business performance management in a manufacturing environment
Leveraging business intelligence management to
business performance management in a
manufacturing environment
Stephanus Landman
21943486
Mini-dissertation submitted in partial fulfilment of the requirements
for the degree Master in Business Administration at the
Vanderbijlpark campus of the
North-West University
Study leader: Mr. Johan Coetzee
November 2011
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ACKNOWLEDGEMENTS
• To my Lord and Saviour. The journey was set and learning’s were made, but getting
closer to You with each step in my life to learn Your ways.
• To my wife Lorianne, my sons Fanie and Christian; your support and willingness to leave
me for several hours a day.
• My study leader Johan Coetzee, for your time and generous insight to support my ideas
and sometimes confusions in some aspects.
• To Mrs. Antoinette Bisschoff, for the language editing
• To Mari Van Reenen, for statistical analysis
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ABSTRACT
No business can effectively be managed without the proper management and information
that reflects and creates the milieu it operates in. Business performance management
creates the framework in which a structured approach can be followed in setting the scene
for a predictive and controllable environment. Business intelligence creates the information
structures; information relationships and a reflection of the value chain of the business. By
combining the two methodologies it creates a total business solution that harmonises all
aspects of value creation in an objective manner.
The aim of this study is to conduct a thorough theoretical study on the relevant aspects
involved in business performance management and business intelligence, and to assess the
relationship of business performance management and business intelligence within the South
African natural resource' mining and manufacturing sector.
The various processes of business performance management and business intelligence are
discussed in the literature study. During the literature research several approaches to
business performance management implementations and the pros and cons of business
performance management are discussed. A broad look at business intelligence is done, with
key focus on delivering of information.
KEY WORDS: Business performance management, business intelligence, value chain, out-
strategise, primary activities, supportive activities
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TABLE OF CONTENTS
ACKNOWLEDGEMENTS ....................................................................................................... ii
ABSTRACT ............................................................................................................................ iii
LIST OF FIGURES ................................................................................................................ vii
LIST OF TABLES ................................................................................................................. viii
CHAPTER 1 ............................................................................................................................ 1
1.1. INTRODUCTION ..................................................................................................... 1
1.2. BUSINESS PERFORMANCE MANAGEMENT VERSUS BUSINESS
INTELLIGENCE ...................................................................................................... 2
1.3. IMPORTANCE OF THE STUDY ............................................................................. 3
1.4. PROBLEM STATEMENT ........................................................................................ 4
1.5. CAUSAL FACTORS ............................................................................................... 5
1.6. OBJECTIVES OF THE STUDY ............................................................................... 5
1.1.1. Primary objective ..................................................................................................... 5
1.1.2. Secondary objectives .............................................................................................. 5
1.1.3. Theory evaluation: ................................................................................................... 6
1.1.4. Empirical research: .................................................................................................. 6
1.7. SCOPE AND DEMARCATION OF STUDY ............................................................ 7
1.8. LIMITATIONS .......................................................................................................... 7
1.9. RESEARCH METHODOLOGY ............................................................................... 7
1.10. DIVISION OF CHAPTERS ...................................................................................... 8
1.11. CONCLUSION ........................................................................................................ 9
1.12. CHAPTER SUMMARY ............................................................................................ 9
CHAPTER 2 .......................................................................................................................... 10
2.1. INTRODUCTION ................................................................................................... 10
2.2. BUSINESS PERFORMANCE MANAGEMENT .................................................... 11
2.2.1. Business Performance Management Roadmap for Manufacturing ................ 13
2.2.2. Business Improvement ....................................................................................... 14
2.2.3. Why Business Performance Management ........................................................ 15
2.2.3.1. Advantages ............................................................................................................ 15
2.2.3.2. Disadvantages ....................................................................................................... 16
2.3. BUSINESS INTELLIGENCE ................................................................................. 16
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2.4. DATA COMPILED INTO INFORMATION ............................................................. 17
2.4.1. Investment into Business Intelligence............................................................... 19
2.4.2. Technology .......................................................................................................... 20
2.4.3. Advantages .......................................................................................................... 21
2.4.4. Disadvantages ..................................................................................................... 21
2.4.5. Summary .............................................................................................................. 21
2.5. RELATIONSHIP BETWEEN BUSINESS PERFORMANCE MANAGEMENT AND
BUSINESS INTELLIGENCE ................................................................................. 22
2.5.1. Business Strategic Management ....................................................................... 24
2.5.2. Summary .............................................................................................................. 25
2.6. CONCLUSION ...................................................................................................... 25
2.7. CHAPTER SUMMARY .......................................................................................... 26
CHAPTER 3 .......................................................................................................................... 28
3.1. INTRODUCTION ................................................................................................... 28
3.2. DISCUSSION OF MINING AND MANUFACTURING ENVIRONMENT................ 28
3.3. THE PROCEDURE AND SCOPE OF THE QUANTITATIVE RESEARCH ........... 31
3.3.1. Survey instrument ............................................................................................... 31
3.3.2. Overview of questionnaire.................................................................................. 32
3.3.3. Sample group and size ....................................................................................... 33
3.4. DESCRIPTION OF DEMOGRAPHICAL INFORMATION ..................................... 36
3.5. OVERVIEW OF RESPONSES .............................................................................. 37
3.6. FREQUENCY ANALYSIS AND DESCRIPTIVE STATISTICS ............................. 38
3.7. COMPARISON BETWEEN THE NEW MANAGEMENT LEVELS ....................... 39
3.8. DISCUSSION OF RESULTS ................................................................................ 40
3.8.1. Relationship of NewManagers responses ........................................................ 40
3.8.2. Relationship of NewEngineers responses ........................................................ 43
3.8.3. Information Relationships .................................................................................. 46
3.9. CONCLUSION ...................................................................................................... 47
3.10. SUMMARY ............................................................................................................ 48
CHAPTER 4 .......................................................................................................................... 50
4.1. INTRODUCTION ................................................................................................... 50
4.2. BUSINESS PERFORMANCE MANAGEMENT AND BUSINESS INTELLIGENCE .
.............................................................................................................................. 50
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4.3. PRACTICAL DESIGN PRINCIPLES FOR A BUSINESS PERFORMANCE
MANAGEMENT AND BUSINESS INTELLIGENCE PROCESS ........................... 53
4.3.1. Review and Performance Meeting ..................................................................... 54
4.3.2. Wiring ................................................................................................................... 55
4.3.3. Key Performance Indicator Management .......................................................... 56
4.3.4. Task management ............................................................................................... 56
4.3.5. Idea Management ................................................................................................ 56
4.3.6. Impacts ................................................................................................................. 58
4.4. RECOMMENDATIONS ......................................................................................... 58
4.5. RECOMMENDED FURTHER STUDIES ............................................................... 59
4.6. CONCLUSION ...................................................................................................... 59
4.7. SUMMARY ............................................................................................................ 60
ANNEXURE A ....................................................................................................................... 64
ANNEXURE B ....................................................................................................................... 78
ANNEXURE C ....................................................................................................................... 79
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LIST OF FIGURES
Figure Page No
Figure 2.2.3.1: Business Performance Management Framework ..................................... 12
Figure 2.2.3.1: Injection of Business Improvement ........................................................... 15
Figure 2.2.3.2.1 Categories of business intelligence ........................................................ 18
Figure 2.2.3.2.1: A holistic view of Business Performance Management ......................... 23
Figure 2.2.3.2.1: Porter’s Value Chain for Mining and Manufacturing .............................. 29
Figure 2.2.3.2.2: Information Technology Supporting Organisations ................................ 30
Figure 3.3.3.1: Respondents per Natural Resource ......................................................... 36
Figure 3.8.1.1: Strategise versus Plan ............................................................................. 42
Figure 3.8.1.2: Plan versus Actions .................................................................................. 43
Figure 3.8.2.1: Business Performance Management objectives versus Business
Intelligence supporting goals .................................................................... 45
Figure 3.8.2.2: Plan versus Monitor & Analysis ................................................................ 46
Figure 3.8.3.1: Inputs of Business Intelligence ................................................................. 51
Figure 3.8.3.2: Relationships of Use by Organisational Level .......................................... 52
Figure 3.8.3.1: Review Performance Management with accountability ............................ 55
Figure 3.8.3.1: Idea pipeline ............................................................................................. 57
Figure 3.8.3.2: Value creation of ideas ............................................................................. 57
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LIST OF TABLES
Table Page No
Table 3.3.1: Detail of response size ................................................................................. 33
Table 3.3.2: Summary of response size ........................................................................... 35
Table 3.6.1: Cohen’s guideline to effect size .................................................................... 38
Table 3.7.1: Managers and Engineers re-coded .............................................................. 39
Table 3.7.2: Business Intelligence re-coded ..................................................................... 40
Table 3.8.1: Managers – BI and BPM correlations ........................................................... 41
Table 3.8.2: Engineers – BI and BPM correlations ........................................................... 44
Table 3.8.3: Information relationships .............................................................................. 47
LIST OF EQUATIONS
Equation Page No
Equation 3.1: Sample size determination for the proposition ........................................... 35
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CHAPTER 1
NATURE AND SCOPE OF STUDY
1.1. INTRODUCTION
Businesses deliver products or services to customers in the market (Baltzan, Phillips & Haag,
2009:23). Staying in business means one needs to out-strategise competitors through
successfully executing the strategy of the business (Frolick & Ariyachandra, 2004:41; Kellen,
2003:2). Businesses need to act faster in the present, to maintain market shares, out run
competitors and adapt to customer needs.
Porter’s value chain model for manufacturing organisations indicates the primary and
supportive activities, which cost leaders focus on when competing in a cost curve market,
(Turban, Leidner, McLean & Wetherbe, 2006:44). When a cost strategy is predominant in the
business, business performance is key to the survival of the business, by staying the lowest
cost producer by creating a wide enough gap between your business’ costs and the highest
cost producer (price setter) in the market; resulting in the profit margin.
Organisations acknowledge business performance management as an enabler, to define
clear goals, actions and to monitor and control the business operations (Baltzan et al.
2009:21). Business performance management is also referred to as a series of processes
and applications to reach the business’s strategic objectives (Mojdeh, 2005:9).
Organisations are expecting improvement through the alignment of business strategies and
knowledge, the most valuable asset of the business. No thorough studies concluded the
relationship of resource alignment to knowledge management and often this is
misunderstood by management and consultants, resulting in poor operational performance
(Asoh, 2004:2).
Applied business processes on data are defined as information or converted data into
reasonable output formats constituting information. This information could be the calculation
of data points to an end result or applied business rules contributing to the information that is
output to the decision processes. Business has plenty of data, but realising it into valuable
2
information that is relevant and could give insight to improve the business performance is
mostly a challenge.
According to the Miles and Snow topology, business could be classified according to the
behaviour it adopts for business strategy (Asoh, 2004:34). The analysers’ profile in business
strategy is those organisations that take minimum risk, but in the same time maximise growth
in stable markets (Asoh, 2004:35).The processing operation could be seen as an analyser,
as they will take calculated risks, while creating market shares and position the business on
the best cost curve possible.
Key metrics or better known as key performance indicators is measurable indicators based
on value driver information which has an effect on the business (Bacalu, 2007:36). Identifying
key performance indicators, one needs to understand the business. What makes it “tick”?
From input, processing and output – what are the internal and external influences effecting
business performance?
1.2. BUSINESS PERFORMANCE MANAGEMENT VERSUS BUSINESS INTELLIGENCE
Business performance management enables business strategic intent to be obtainable
through a series of intertwined processes. Business intelligence enables the function of
addressing identifiable gaps in the business processes.
Some confusion exists to what business performance management and business intelligence
is, and is not. If business performance management provides a process of improving
business and business intelligence leverage the ability to disseminate the information of a
business to support business decisions, it would be true to state that you need business
performance management and business intelligence, but business intelligence supports the
overall process of business performance management. The orchestration of the two
processes advances the business’s ability to improve on the bottom-line. Business
performance management is also the fundamental cohesiveness of all management
processes (Mojdeh, 2005:1). As much as 84% of business indicated using business
intelligence in some form within the business (Miller, Brautigam & Gerlach, 2006:16).
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In the rapid changing and competitive environment businesses operate in, knowledge
management as leverage is not enough and not the biggest contributor to increase
performance. Knowledge of the business mechanics and applying new avenues to overcome
current performance is more contributing to the bottom-line of the business (Asoh, 2004:1).
1.3. IMPORTANCE OF THE STUDY
One of the most diversified mining companies in the world, consisting of more than 100
operations, across 25 countries around the globe is diversified into 10 customer sector
groups, to illuminate the products offered into the market.
The manganese business is spread across Africa (South Africa and Gabon) and Australia
(Tasmania and Groote Eylandt islands in the South and North of Australia). Raw materials
are mined in the Kalahari Desert and sent to the processing plant in the Gauteng province for
converting the ore to alloy.
This processing operation is to produce high quality, low cost Ferromanganese and Silicon
manganese alloys. By combining manganese ore and other raw materials, it is smelt within
sub-merge arc furnaces to the final products. The business consists of eight sub-merge arc
furnaces, an energy production plant, raw material and final product management
department. The business also has four supporting departments that manage the technical,
health & safety, human resources and financial services.
The business has embarked onto a business improvement road, since 2008 and yet
business intelligence was not focused in the sense of intelligence by means of cubes and
dimensional information nor technology. If business intelligence is used effectively it could
improve performance, by means of leveraging on the insight it offers to make improvement
decisions (Howson, 2008:2).
The processing operation has earned the position of lowest cost producer in the manganese
industry globally. Being on the lowest cost curve also indicates that to stay there, the need to
improve ever more. The processing operation was faced with dead-ends to improve even
further and insight to how the exact measurable key performance indicators are actually
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measured on the value added processes within the business (Phelps, 2004:4). Business
need to know what makes them do business, what do they know to survive and thrive in the
very quick-changing markets experienced currently (Kellen, 2003:1).
1.4. PROBLEM STATEMENT
A certain amount of confusion does exist, even in the business intelligence world, to what
actually is meant by the terminology. Business intelligence is neither a technology nor the
warehouse in which all the business data is stored. Business intelligence is the way in which
information, across functional areas within the business, is interpreted to give enriched
paradigm shift information that will enable decisions to be made for the better of the business
(Howson, 2008:2). The depths of business intelligence’s enrichment as a tool include
scorecards, dashboards, predictive analysis, and BI search and visualisation of the
information. By exploiting the gaps and relationships of information dimensions bring another
level of insight and knowledge to the business.
Many businesses struggle to disseminate strategic goals into workable set points in the
lowest level of the business. The roll-up of the lowest level measuring points need to total up
to the high level goals of the business. This sometimes does portrait its own challenges. Not
only is the dynamics important but also the collaborative channels between line management
and the workforce.
Businesses usually find themselves in situations where projects do not deliver as expected or
consultants overpromise the deliverables and customers do not get what they had asked for.
To “wire”, aligning business measurement points to organisational positions, a business and
the focus in the initial project start-up is what drives the business. What needs to be
measured and in which frequency? How does this articulate into the strategic goals of the
business? For the consultant to deliver on a real business performance management, the
business sense, measurement dimensions and accountability positions is critical. Fitting all of
this into a collaborative, monitoring and controllable environment is even more challenging.
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1.5. CAUSAL FACTORS
The causal factors for this study are the following:
• The natural resource industries have become under high pressures around the globe
and cost effectiveness is highly sought after.
• An investigation indicated that the maturity level of the natural teams in the business
has been engrained and possible business improvement processes would be easily
introduced into it and positive return could be capitalised on.
• Operating costs were not on satisfying levels and being on the lowest cost levels will
result in more profits. This was established before the great recession the world
experienced in late 2008 and the first half of 2009.
• Staying competitive is crucial as a business can easily lose market share in the very
dynamic international environment.
• An initial investigation indicated that management strategy is not filtered through to the
lowest level within the business.
• The investigation also indicated that measurements against these strategic goals are
non-existent in some cases.
• No standardised measurements and progress review sessions existed, which
highlighted risk of business continuity to address the strategic goals.
• High level indicators were not possible and countless time was dedicated to align
actual facts to be rolled up to the highest level in the business.
1.6. OBJECTIVES OF THE STUDY
The objectives of the study are split into primary and secondary objectives.
1.1.1. Primary objective
The primary objective of the research is to establish a relationship between business
intelligence and business performance management.
1.1.2. Secondary objectives
Secondary to this, the following will also be investigated:
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1.1.3. Theory evaluation:
1.1.3.1. Perform a literature study to research the different aspects of business
performance management and business intelligence.
1.1.3.2. Perform a literature study to indicate the relationship of business
intelligence and business performance management.
1.1.3.3. Provide an overview of a business performance management
implementation framework or models found in literature and business
environments where it was implemented.
1.1.3.4. Perform a high level assessment of the current status of business
performance management in the mining and manufacturing sector, with
emphasis on successful implemented processes.
1.1.4. Empirical research:
1.1.4.1. Investigate the opinions of respondents of the maturity levels of different
business performance management and business intelligence principles.
1.1.4.2. Investigate a readiness for implementing a business performance
management process with specific emphasis on information availability to
support a business performance management roll out process.
1.1.4.3. From both the theory and empirical research the final objective is to
recommend practical design principles which can be used to implement a
business performance management programme which will result into a
competitive advantage to the mining and manufacturing sector.
As can be seen from the above objectives, a broad spectrum of aspects will be researched in
business performance management. Based on the literature a survey will be designed to
determine the maturity of the business performance management process, the availability of
information and possible models to utilise for engraining business performance management.
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1.7. SCOPE AND DEMARCATION OF STUDY
The study is to focus on the mining and manufacturing businesses of South Africa where
business performance management and business intelligence are present. The focus is to
understand the contribution of the correct value drivers that leads into decisions being made
to enhance the performance of the business and to indicate a model for adoption by other
mining and manufacturing businesses.
The study will be limited to primary sources within the mining and manufacturing sector, with
specific reference to the processing operation in Gauteng. Secondary sources of information
were limited to those generally available on the Internet, in the form of English documents
and generally available literature study.
1.8. LIMITATIONS
The surveys will be limited to the mining and manufacturing sector from executive to
engineer’s level in the business. The objectives set out will be covered within the survey only.
1.9. RESEARCH METHODOLOGY
Literature Study
Various publications were reviewed during the completion of the literature review. These
included text books related to the field of information management, business process
management and business intelligence.
Journals and websites were also accessed. The following topics were explored:
• Defining business intelligence and business performance management.
• Frameworks of business performance management used in the industry.
• Relationship to business strategy and value chains of manufacturing and mining operations.
Empirical study
Empirical research was done conducted by means of a structured questionnaire. The study
population included mining and manufacturing businesses, from executive to engineer’s
level. The data was collected in electronic format by means of web based survey services.
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1.10. DIVISION OF CHAPTERS
Chapter 1 – Introduction and problem statement
Chapter 1 serves to supply the background to the study. Important concepts on business
performance management, business intelligence, the right information, information gaps and
business performance processes within the organisation are touched on, as well as a
discussion on the relationship of business performance management and business
intelligence of an organisation. Thereafter, a short discussion on the implementation road will
follow in business improvement. The reader will be introduced to the organisation as well as
the elements of a typical business improvement process constituting business performance
management.
The problem statement highlights the objectives and strategy of the organisation, and from
this the primary and secondary objectives of the study are derived. The remainder of the
chapter covers the scope of study and research methodology.
Chapter 2 – Literature study
Chapter 2 contains a literature review on business improvement. Some concepts that will be
explored include:
• Defining business performance management
• Defining business intelligence
• Relationship between business performance management and business intelligence
• Define business strategic management
• Explain Porter’s value chain within business performance management
• Creating a business performance management road map, processing operation approach
• Describe in detail the elements, tools and systems utilised as part of a processing operations
review and performance management process.
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Chapter 3 – Research methodology and findings
Chapter 3 contains a comprehensive explanation of the research methodology that will be
followed to complete the empirical study. This will include the data gathering process, as well
as an analysis of the findings and presentation of results.
Chapter 4 – Conclusion and recommendations
In this final chapter conclusions will be derived from both the literature study as well as the
results of the empirical research. The conclusion will aim to present a response to the
problem statement and objectives as defined in Chapter 1. Practical recommendations for
business performance management to the broader group will be discussed.
1.11. CONCLUSION
It is a fundamental decision to improve a business to stay competitive in the market. Even so,
being more and more proactive, quicker to respond and to understand the complete
environment the business operates and to stay focussed with the business strategy remains
a challenge. Utilising processes, tools and knowledge to attain right of existence in the
market is imperative.
1.12. CHAPTER SUMMARY
The culmination of business performance management and business intelligence to assist
businesses to address the strategic gap within an organisation is of utmost importance.
Insight to the processes and defining and embedding it into the organisation is instrumental
to the success of investments made. Adapting to the way businesses need to run its
operations, focus on the correct measurements that impacts the bottom-line and to actively
control the process to reach the strategic goals will create the gap between competitors.
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CHAPTER 2
LITERATURE STUDY
2.1. INTRODUCTION
No business can effectively be managed without the proper management and information
that reflects and creates the milieu it operates in. Business performance management
creates the framework in which a structured approach can be followed in setting the scene
for a predictive and controllable environment. Business intelligence creates the information
structures; information relationships and a reflection of the value chain of the business. By
combining the two methodologies it creates a total business solution that harmonises all
aspects of value creation in an objective manner.
Business information requirements are becoming more and more of a necessity to run a
business successfully (Lonnqvist & Pirttimaki, 2006:32). Some businesses have fast amount
of data but it’s not formalised into aggregated management information within the system and
usually gets reported in Microsoft Excel. Due to the high performance that is required in the
business environment, rich information is needed to obtain proper insight into the business
performance and to identify opportunities. Business performance management and business
intelligence facilitate a proper approach to strategic goal setting of a business and to
formulate it into lower levels within the business. Business performance management does
not only facilitate the processes in identification and creation, but also addresses the
planning, monitoring and corrective actions of the business management aspect,
(Ariyachandra & Frolick, 2008:114).
Several invested projects have failed by poor understanding of business intelligence and
business performance management processes. Project sponsors were either confused by
the meaning of the processes and thought the one would deliver the other’s outcome and
resulted in negative perceptions on both side of these investment options.
To understand the processes and getting an understandable representation of what it
purport, an explanation will be supplied on both methodologies and approaches of
implementation. The aspects of only one present in a business will also be distended.
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2.2. BUSINESS PERFORMANCE MANAGEMENT
To reach the moon (goal), a road needs to be mapped, the flight needs to be monitored and
controlled and the landing on the specific spot is reaching the goal set up front.
In business context the following defined statement describes the reasoning what business
performance management is all about. It is defined as the enabling business process that
aligns business strategy, operational objectives and business activities, to manage
performance through better informed and proactive decision-making actions, resulting in
common organisational objectives (Ballard et al., 2005:3) and (Ariyachandra & Frolick,
2008:113).
To enhance the understanding of Business Performance Management, the framework will be
exploded, as can be seen in figure 2.2.1. The framework indicates the four areas and rotation
the process will follow, starting at the “Strategize” block.
• Strategize – defining the way to identify business strategy, the discovery of key value
drivers to accomplish strategy and create metrics to monitor the performance,
(Ariyachandra & Frolick, 2008:114). To be competitive, one needs to stay competitive.
This is accomplished to challenge the boundaries of performance. To strategise,
owners or executive management of the business, review the past performance of the
business and decide on future intent or direction for the business. This is also
supported by a SWOT analysis.
• Plan – defining a road map that is followed with specific projects, budgets and
activities to fulfil the strategy. Planning to build a bridge from the current status of the
business to the to-be state. If the goals were defined as part of the strategy process,
planning will include the formulation of required key indicators to measure the
progress towards the goals. Identification of gaps on measuring points is normally
done in this process.
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Figure 2.2.3.1: Business Performance Management Framework
Source: Adapted from Frolick & Ariyachandra, 2006:43
• Monitor and analyse – actual performance against target values are reviewed and
dissected to understand the post actions taken resulting in the current position.
Monitoring is continuously measuring how we are moving towards the target. Think of
the GPS in your car, continuously tracking your move on the road, any deviations,
you’ll get the word. The same with businesses, progress need tracking and alerts to
indicate to decision makers the course taken is not delivering the required results or
we are on track.
• Take corrective actions – by understanding the status quo, rectification with
identifiable reactions to re-align the actions to achieve the desired performance levels.
Adjusting the driving direction will result in you reaching your destination. Available
information will give you insight to what happened. Part of corrective actions is also
tracking the status of the action. Have we done what we said?
These four steps are a continuous loop of processes to be followed, as long as a business
exists. The goals will determine the monitoring focus, while the corrective actions will be
determined by the current status of the business. The planning will follow the goals and map
out the detail of achievement.
Strategize
Plan
Monitor and
analyse
Take
corrective
action
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The business goals are aligned horizontally and vertically throughout the business, to ensure
the business goals are measured at the source and all are focusing from the lowest level in
the business to the top. This means the contribution, how small that you might have in your
area of accountability, sum to the greater total of the over arching key indicator of the
business.
Actions are taken proactively and directed to the source of rectifications. Employees can view
the correct metrics and have insight into the performances. Business performance
management improves team effectiveness and productivity (Ballard et al., 2005:5).
Business processes and applications need to be in concert with one another, destroying silo
effects and misalignments of data, information and processes. This alignment brings forth the
correct measurable on goals and distribution to all relevant parties. Business needs to
understand what needs to be continuously monitored, how often it needs to be reviewed and
what steps to put in place in order to maintain the necessary performance levels.
The objective of business performance management is to help organisations with
improvement and optimization processes across all aspects of the business. In order to be
rapidly flexible the business needs to understand the playing field, the current situation of the
business and the players in each position to contribute, (Ballard et al., 2005:30).
2.2.1. Business Performance Management Roadmap for Manufacturing
How do we approach a beast like this? It sometimes sound very simple and when we
approach it, we found it to be somewhat difficult and scope creep on the project highlights
this quite quickly.
Types of approaches
Business starts off usually by one of these three approaches:
1. Enterprise wide – the approach will be top-down through strategic change. This
approach has the longest timeline before realisation of benefits will be seen. Much
more planning up front will take place in order to include all operations. This approach
14
will also have several iterations of deployment and upgrades to relevant operations, as
they need to align to the processes and system standards.
2. Cross-functional – smaller approach to the above and includes some functions like
finance and supply processes. It could be smaller like regional based.
3. Functional– based on functional area and will not necessarily mean the
implementation will drive new strategies, but rather control and improve performance
in a certain function like Human Resources.
4. Mixed – this is a combination of all functional areas in the business, but is demarcated
by a section within the business. i.e. a production unit of a production facility, where
costing, human resources, health & safety, maintenance and production are all
present, but at a very small scale of the business.
2.2.2. Business Improvement
Business performance management can include a business improvement process where
innovation is supported until it realises into measurable and cultural change benefit for the
organisation. This is done through an injection of improvement ideas after planning, as a
secondary “planning” process that redefines, in some cases, the key performance indicators
that are monitored in the next process.
Figure 2.2.1.1 indicates the blue block for position of this process into the business
performance management process. Why is this done? Think of your old computer that may
have a turbo button. This is the same. Although the business performance management puts
all effort in concert, this improvement process unlocks stored potential within the business to
be reaped. This is continuously asking the question: “Are we moving fast enough?”
Institutionalise idea generating cultures within the business to create a capacity of
improvements that can be assessed and prioritised for implementation.
15
Figure 2.2.3.1: Injection of Business Improvement
2.2.3. Why Business Performance Management
Business needs to become more responsive and flexible to minimise disruptions to
operations. Business also needs a single place to have a current view of their organisations.
The major drivers for implementing business performance management solutions are the US
Sarbanes Oxley Act and the new European Basel Capital Accord (Base II). Base II is a
critical piece of legislation that will impact how data and processes are integrated and how
risk-management, finance and operations function. It also encourages providing information
for better performance management, risk-management and capital decision-making (Ballard
et al., 2005:17).
2.2.3.1. Advantages
Business performance management gives the business the ability to reduce costs, increase
revenue and ultimately provides a competitive advantage. It also recognises proactive
monitoring, measuring and attaining performance targets. The ability to monitor business
processes also creates the opportunity to improve and manage these processes (Ballard et
al., 2005:24).
Strategize
Plan
Monitor and
analyse
Take
corrective
action
Business
Improvement
16
By unification of the business performance management processing and business
intelligence system it results in business process effectiveness. The result of the unification
also defines the simplification of the data structures in the business performance
management and business intelligence systems. Business performance can be compared,
monitored and aligned with the business strategies, goals and objectives when integration
with business intelligence is done.
2.2.3.2. Disadvantages
The disadvantageous impact of not having business performance management is bullet
below:
• A common threat is information - availability for business performance management
• Silo effect of decentralised information hubs within the business
• Lack of transparency on enterprise level, only departmental or functional area views
available
• Timely activities in aggregating information for higher levels within the business
(Ballard et al., 2005:25).
2.3. BUSINESS INTELLIGENCE
Business Intelligence is defined in more than one way by people, like, the right information to
the right people at the right time, utilising information effectively or to realise business
success by means of accessible information that can be put into action (Howson, 2008:1;
Schauer, 2004:58).
Business intelligence is also referred as the application or technology layer and techniques
used to gather, store, analyse and provide business information in a timely and easily
manner within the technology stack.
Business intelligence enables the business to make more effective decisions with the
information at hand. The technology gathers information systematically, which could be
analysed, disseminated (slice & dice) and compared from internal and external sources of the
17
business environment (Lonnqvist & Pirttimaki, 2006:32; Turban, 2006:423; Baltzan et al.,
2009:11; Howson, 2008:1).
The purpose of the business intelligence process is to identify and gather vast amounts of
data and information within and outside the business into a more condensed format that will
bring richer information trends (intelligence) to the audience.
With the capability to extract information in ways and means that put context and patterns to
information, business intelligence would add value only to the business when acting upon
opportunities identified within the business performance and information patterns (Howson,
2008:4).
2.4. DATA COMPILED INTO INFORMATION
The operational raw data are usually kept in data sources like database systems, electronic
documents and/or physical documents across the business. The information is gathered into
a multi-dimensional data warehouse in order to construct queries, reports or analysis on the
information, for decision-making (Turban, 2006:424). The information can be conducted in
real-time, but is limited to the latest upload of complete data sets to the warehouse. Patterns
are evaluated and meaning is added to the information. A response is formulated based on
the patterns of the information and the knowledge that was added (Baltzan et al., 2009:98).
Applying knowledge to the information viewed, knowledgeable actions are given to improve
processes (Baltzan et al., 2009:98).
Key statistical figures or key performance indicators indicate the perfectness of a process.
The data mining tools could be utilised to slice and dice between different areas in the
business or to identify the underlying issues. Understanding the process failure modes, will
lead to mitigating actions and be verifiable through key performance indicators.
Business intelligence (not the technology), needs to be competitive and is enabled through
fairly available technologies, distribution of intelligent information to all people within the
business and a performance based culture within the business (Baltzan et al., 2009:98, 99).
18
A typical business intelligence environment could be broken into reporting, analysing and
data mining. Figure 2.4.1 below depicts the split of the two major categories in the business
intelligence layer from a business process perspective.
Figure 2.2.3.2.1 Categories of business intelligence
Source: Adopted from Turban, 2006:425.
The “Information and Knowledge Discovery” stream defines the analytical processes of
searching for opportunities within the business environment. The “Decision Support and
Intelligence Systems” stream refers to the analytical result to be put through decision
processes to identify the most valuable option for the business to take. The “Metrics,
scorecard, dashboard, BPI, BPM”-process block is also utilised to perform the monitoring
process in business performance management. This metrics and scorecards are key
performance indicators defined to support the goals of the business. When fully developed,
the metrics and dashboards are deployed to all within the business that has a part of
accountability towards the over arching indicators of the business.
19
For some businesses the products and services delivered by business intelligence is not on
the same level of maturity as some will reflect on it through a single market-project and
others through a continuous process that delivers products and services to different users
(Lonnqvist & Pirttimaki, 2006:33).
Performance metrics can be developed for business intelligence to indicate investment
positions of the business intelligence project to executives and to indicate the correctness of
application to the user group, (Lonnqvist & Pirttimaki, 2006:33). Investment costs for a
business intelligence solution and the benefits that it will deliver are pivotal in the success
delivery of the project. Although these measurements are quite challenging to measure, the
proposed benefit of a Business Intelligence solution, is to measure the realised cost saving,
ideas generated from using the intelligent information (Lonnqvist & Pirttimaki, 2006:34).
Business intelligence performance measurements within an organisation could typically
phase:
1. Identification of information needs
2. Information acquisitions
3. Information analysis
4. Storage and information utilisation
The above phases could be defined as what information is needed to be measured and why
it needs to be measured. What information could be combined with other information to
indicate a key relationship of business activities that impacts business performance? The
third is how to analyse the information. Relationships between information groups are in
some cases not relevant at all and knowledge of the business is required to understand the
relationships. Lastly, the period of storage and how often the information is available, on-time
and to the right people making the decisions (Lonnqvist & Pirttimaki, 2006:37).
2.4.1. Investment into Business Intelligence
Some of the very difficult calculations to do are the return on investment (ROI) on information
technology projects. Although ROIs get compared to see viability of investment options to the
business, key project stakeholders do find it very difficult to stick the neck out on a number to
20
indicate for business intelligence, (Howson, 2006:40). The best practice in the business
intelligence space is to rather evaluate the business performance after implementation of
such functionality (Howson, 2008:68).
2.4.2. Technology
Source systems like operational or manufacturing, sales, supply, financial, customer
relationships (CRM) and external sources feed into the data warehouse through the Extract
Transform and Load (ETL) layer of business intelligence. The data warehouse’ data
structures are set up in multi-dimensional tables to give the richness of slicing and dicing of
information to relationships like time dimensions.
The integrity of the data, management of the data in the warehouse and development of
front-end tools to the users will dominate the success of the business intelligence project.
Business intelligence tools like query, reports, analysis and alerts could be set up to view the
information. Business involvement to assist in the selection process and tools that are
available in the technology will support the adoption rate by the users (Howson, 2008:166).
Different levels of users will use different depths of data and tools of the business intelligence
technology. Normally the tool will be able to secure data points to restrict the users access.
The famous Excel spread sheets are not demolished from the environment. Microsoft has
seen the flexibility the product offers by itself and incorporated it as an add-on to the
environment whereby cubes can be refreshed into the sheets and additional slice and dice
power could be added like Microsoft PowerPivot add-ons.
The depth of the tools being deployed into the business and segmentation of the users, will
define the platform of information the user will excel from. It is notable that the production
environment is not to be seen as being utilising analysis or statistical business intelligence
tools, as mentioned in a survey result (Howson, 2008:173). The picture has somewhat
changed due to these gaps being identified by the maturity of the manufacturing execution
system (MES) manufacturers. New products in this space have been developed like Dynamic
Process Management (DPM) and Enterprise Manufacturing Intelligence (EMI) of
21
Wonderware software suite, to give the production user the capability to analyse real-time
financial and production data, (Martin, 2004:1).
2.4.3. Advantages
• Single point of truth is one of the advantages all businesses familiarise themselves
with. Information is scattered all over the business and to try to pinpoint the exact
source or latest update, could be a daunting task. If data is managed within a business
intelligence environment, there is only one source of the data, where everybody gets
their information from. With a matured business intelligence system, it is possible to do
predictive analysis for the business, based on the external pressures. Such
businesses normally are very innovative, flexible and could easily adapt to market and
economic conditions (Miller, 2006:4).
• It also allows people to interact with the same data concluding several different
scenarios, performance measures and information patterns, whereby source data is
aligned and the business picture painted can be trusted (Howson, 2008:2).
• Better decision making to improve the business processes (Schauer, 2004:58).
2.4.4. Disadvantages
• Implementation of such systems are very costly and timely
• Business understanding of deliverables versus consultants promises
• Business’ clear understanding of its value chain and processes – reflects in rework in
the development layer of the project
2.4.5. Summary
Business intelligence is not about having a BI-software suite available in your business, but
it’s the combination of having sensible, structured and representative information available at
the right time to the right people.
Approaching a business intelligence project would not be easy and justification of the ROI
would be very difficult. Businesses would struggle to survive without it, as information is not
22
readily available to the decision makers. This will result in opportunity losses when it count
the most.
2.5. RELATIONSHIP BETWEEN BUSINESS PERFORMANCE MANAGEMENT AND
BUSINESS INTELLIGENCE
With the look at defining business performance management and business intelligence it is
clear that both processes need information. It is also evident that business intelligence
encompasses the workhorse of information, by means of extractions, manipulations to data,
based on the business rules and by reporting and analysing information by means of
dashboards, reports and analytical capabilities (Ballard et al., 2005:28).
Analytical capabilities from a business intelligence perspective, is to build and demonstrate
relationships between entities and to supply the user with rich functionality to explore the
possibilities within the information patterns.
Business performance management on the other hand was defined with some processes not
being built into systems due to the collaborative aspects of outcomes that is finalised
between groups of people. This type of functionality is not technology driven, but is based on
knowledge obtained and available at the individuals to design, agree and monitor objectives
for the business. It is also clear that it would be very difficult to maintain high level of success
with only one of the processes. It is also evident that the one fulfils the other in a relationship
where information is transferred between processes to overcome the obstacles in order to
reach the desired goals.
Business process effectiveness is enhanced by unifying the business performance
management and business intelligence environments. Information is distributed across the
enterprise through the use of information technology.
From the definitions it is apparent that there are two processes and it is aimed at achieving
business performance. Literature confirms this and states that there is a clear differentiation
between business intelligence and business performance management and researchers
generally agree that business performance management is not business intelligence and vice
versa (Ballard et al., 2005:13; Ariyachandra & Frolick, 2008:42, 113). What was also evident
23
is that the business performance management area is still new and not widely distributed as
a product in businesses. For managers it is crucially important to understand the processes,
but more importantly to invest into these processes from an organisational perspective. A
survey done in 2006 indicated a 53% of companies cited budgeting as the leading
component in a business performance management initiative (Stamford, 2006:2).
The integration of business intelligence, business process management, corporate
performance management, business service management and business activity monitoring;
as shown in figure 2.5.1; creates a single view of the business performance management
functions (Ballard et al., 2005:3) that supports it. These functions are interlinked by an
“information band”. It is apparent that business intelligence will contribute to the business with
information structures and dimensions, as previously discussed. By having these insight to
the processes and information, results in better actions to be taken against goals to reach the
business objectives.
Figure 2.2.3.2.1: A holistic view of Business Performance Management
Source: Adapted from Ballard, et al., 2005:3
Business
Performance
Management
Business
Intelligence
Business
Process
Management
Corporate
Performance
Management
Business
Service
Management
Business
Activity
Monitoring
Information Band
24
The strategic goals of a business in not always very well understood within the business, as a
survey result showed, less than 60% of senior managers had a clear understanding of the
goals in the business (Phelps, 2004:6).
The common theme across the functions for business performance management is
information, as can be seen in figure 2.5.1, with the orange band. It is the common ground for
all in the business, to know what is to be monitored and controlled in order to attain
organisational objectives.
2.5.1. Business Strategic Management
Strategy is the action plan that is derived to excel the business into a more favourable
position based on profit, stakeholder interest and strengthening of the business for the future
(Thompson, et al., 2009:6). By having a sustainable competitive advantage will ensure a
lasting customer preference to be formed for your product and your business (Thompson et
al., 2009:7).
The strategy a business’ executives put forward is the best future indication that will influence
investments and market share. This is influenced by a number of approaches:
• “Actions to gain sales and market share via lower prices, more performance features,
more appealing designs, better quality or customer services, wider product selection,
or other such actions.
• Actions to respond to changing market conditions or external factors.
• Actions to enter new geographic or product markets or exit existing ones.
• Actions to capture emerging market opportunities and defend against external threats
to the company’s business prospects.
• Actions to strengthen market standing and competitiveness by acquiring or merging
with other companies.
• Actions to strengthen competitiveness via strategic alliances and collaborative
partnerships.
• Actions and approaches used in managing R&D, production, sales and marketing,
finance and other key activities.
• Actions to strengthen competitive capabilities and correct competitive weakness.
25
• Actions to diversify the company’s revenue and earnings by entering new measures.
(Thompson et al., 2010:10).
These approaches all reflect the need for information to ensure timely decisions.
2.5.2. Summary
The equation reads, good strategy and good strategy execution will result in good
management (Thompson et al., 2010:17). The good strategy plan that is derived based on
intent of moving the business from the current status quo to the future position and executing
against the strategic plan will result in a good performance of the business. In order to obtain
this good performance, the Business Performance Management and Business Intelligence
processes support the capability to be available for management to obtain good results. As
described earlier, Business Performance Management is the culmination of strategy,
performance and actions. Business Intelligence on the other hand will supply the information
available to make strategic decisions.
2.6. CONCLUSION
It is apparent that business performance management is an information “requester” to move
from the one process to the next. Business intelligence is an information workhorse,
extracting, transforming and loading relevant information and supplying it to the appropriate
decision makers.
It is not transparent to what the relationships are between the two spheres.
Business performance management are not based on technology nor information, but the
success of the process is dependent of having information to action against. Business
intelligence on the other hand fulfils the need of the business performance management
processes.
Highlighting some key aspects to both processes:
• Business performance is influenced by the means to have the right information
available to the right people in the organisation at the right time.
26
• Business ability to grow in the respective industry is related to the capability that is
possible to lower the business strategic goals to the lower levels within the business.
• Business Performance Management is a different process that entails strategizing,
planning, monitor and controlling and corrective actions to be taken.
• Business Intelligence is the culmination of data to supply rich information through
queries, reports and analytical tools within the technology.
• Business Performance Management delivers improvement to the business by means
of leveraging on Business Intelligence for informational substance to make decisions.
2.7. CHAPTER SUMMARY
Firstly we discussed what business performance management is and what it is constructed
of. The sphere starts with the strategising, planning, monitor & analysis and finally corrective
actions processes.
Secondly, the approaches for embedment of a business performance management were
discussed. It would be dependable on the business’ approach to which approach is
applicable for their project.
Thirdly, business improvement as a “turbo” button to the business performance management
process was discussed and can be seen as a second planning process delivering inputs into
the business performance management process.
The reason why business performance management is a needed process in today’s
businesses were discussed and the pro’s and con’s were weight up. It is more advantageous
to have it, than not having it.
Business intelligence were discussed in brought context through what it is, how data gets
transformed into sensible information and justifying investment of such a project. The
technology of business intelligence in lower levels of the business like operations is a newly
added dimension in the market. The technology is developed for real-time environments that
27
are quite different to transactional based systems like enterprise resource planning (ERP)
systems.
Advantages and disadvantages are weight up and two major factors on both sides are to be
taken of note: advantage – information availability, disadvantage – return on investment and
delivery of a successful project.
Lastly the relationship between business performance management and business
intelligence are discussed and indication is that there should be. The two spheres are
dependent on each other to produce workable output for the business.
Chapter 3 will cover the research methodology and findings of this literature study and
conclusion of some relationships will be drawn.
28
CHAPTER 3
RESEARCH METHODOLOGY AND FINDINGS
3.1. INTRODUCTION
In chapter 2, Business Performance Management and Business Intelligence were defined
and assumptions were made if the two spherical processes could have some relationship(s)
with one another and in what context. In this chapter the focus is on obtaining evidence for
the research objectives laid out in §1.6. In addition, the survey findings are presented.
The aim of the survey is to understand the relationship of business intelligence on business
performance management within the mining and manufacturing sector. Both these supporting
frameworks have huge benefits to the business, if deployed and understood correctly.
3.2. DISCUSSION OF MINING AND MANUFACTURING ENVIRONMENT
The mining sector of South Africa is the fifth or sixth biggest contributor to the GDP of South
Africa. Also the largest producer of platinum and one of the leading producers of gold,
diamonds, base metals, coal and the best grade in manganese ores in the world. The biggest
natural reserves held in South Africa are gold, platinum-group metals, chrome ore and
manganese ore.
The metals industry, subset of the manufacturing sector, makes up a third of South Africa’s
manufacturing. As this is seen as a beneficiated process or processing of primary resources
to a final or semi-finished product for the market. The manufacturing environment is running
under utilisation due to raw material input constraints, caused by rail capacities. South Africa
is a net exporter of steel products.
The value chain of the mining and manufacturing industry could be summarised as the
acquiring, mining and supplying of natural resources to the market in raw or processed into
semi - or final product format. Manufacturing downstream in the same commodity is usually
considered due to supply chain constraints and/or better value propositions for units of
29
products sold or placed through the value chain. Figure 3.2.1 indicates a common value
chain for mining and manufacturing.
Figure 2.2.3.2.1: Porter’s Value Chain for Mining and Manufacturing
Source: Adapted from Turban, 2006:515
It could be considered a given to understand the internal operation of a business and in
today’s milieu external factors or pressures are having more impact on high performance.
The macro-economic policy is the major driving force behind economic activity and also
environmental impacts. The policy aims at economic growth, increasing employment, positive
trade balances, combating inflation and equity.
As earlier stated, mining and manufacturing can only be profitable if the cost to produce is
kept to the minimum. From Figure3.2.1 it is also visible that the value chain can become
complex and management spans across a wide range of functions to support it.
30
When external pressures; indicated by Figure 3.2.2; like societal and external market are
forced onto the business, it would require synchronised efforts in the right direction, to keep
the boat afloat, (Turban, 2006:13).
Figure 2.2.3.2.2: Information Technology Supporting Organisations
Source: Adapted from Turban, 2006:12
These external pressures in respect to South African context are rail constraints that impacts
mine production output to terminals for exports; unskilled worker class, stable and adequate
energy supplies to feed production facilities, environmental impacts currently experienced
around the globe and equity imbalances within the mining industry.
The aim of the questionnaire is to establish an understanding of the relationships between
business performance management and business intelligence’s level of application within the
natural resource sector.
31
3.3. THE PROCEDURE AND SCOPE OF THE QUANTITATIVE RESEARCH
The empirical study focuses on the mining and manufacturing, of natural resources industry.
It spanned across a range of natural resource sectors and across the management levels
within the businesses. The usage of business intelligence and business performance
management were analysed, based on sub-processes of business performance
management, as well as the relationship in which business intelligence assisted the
businesses through information.
The reason for the study was due to the most minuscule study in the manufacturing and
mining for these two aspects. Other studies are starting to develop in this area and software
vendors are aligning their products to deliver on some aspects. Some studies now starting to
surface, indicates the need for real-time business intelligence within a production
environment. These industries are real-time based, which enlarge, are captive to quick
response against negative impacts in the business. This indicates a far more robust and
enhanced business intelligence system to support such quick response times.
3.3.1. Survey instrument
Conducting data collection through surveying is one of four data sources that are used in
gathering data from the sample in a population. The other three: distribution of data by
organisations, designed experiments and observational studies are the other three data
sources, (Levine, Stephan, Krehbiel & Berenson, 2008:6,7).
Research can be grouped into two categories: quantitative and qualitative. Quantitative, also
known as positivist can be summarised as the natural-scientific method in human behavioural
research. It is limited to what can be observed and measured objectively. Qualitative, also
known as anti-positivist, can be summarised as the inverse of human behavioural research,
also seen as the experience of the human behaviour for specific humans researched,
(Welman, Kruger & Mitchell, 2007:6).
A quantitative approach was chosen by the author to objectively meet the research
objectives. The sampling approach was non-randomly (voluntarily).
32
3.3.2. Overview of questionnaire
A questionnaire was chosen for data collection and other instruments were also considered.
The advantage and disadvantage was considered and found more favourable due to the
timing and cost to gather the data. The sources used for the compilation of the questionnaire
included the following sources: Vlerick Leuven Gent Management School (2007:17-26); plus
author experience within the business performance management and business intelligence
area. The primary objective was not visible within previous studies and interpretation of
literature and experience was used to formulise some of the questions. The questionnaire’s
questions compose of 42 questions with the following answering methods:
• Questions (31,33 to 47) were based on a 4-point Likert scale, 1 (Very relevant) to 4
(Irrelevant)
• Questions (17, 18, and 20 to 27) were based on a 4-point Likert scale, 1 (Completely)
to 4 (Not at all).
• Questions (10 to 15) - The fourth option don’t allow for analysis beyond the frequency.
Therefore the second variable which only includes responses of participants, who had
an opinion, was included. The new scale was re-coded with the answers 1 (Exceeds
expectations) to 3 (Below expectations) and is referred to after this as 10R to 15R,
annexure B.
• Questions 16 and 19 are multiple selection criteria questions and would be used in
frequencies.
The layout of the questionnaire can be grouped as follow:
1. Questions 1 – 6 demographics
2. Questions 7 – 9 background of business performance management within the
business
3. Questions 10 – 15 satisfaction of business performance management within the
business
4. Questions 16 – 19 values and challenges of business performance management
within the business
5. Questions 20 – 27 usage of business intelligence within the business
6. Questions 28 – 30, 32 usage of reports for processes within the business
33
7. Questions 31, 33, 34, 36 – 43 business intelligence support of business
performance management processes
8. Questions 35, 47 – business performance management support of business
performance management processes
9. Questions 48 – 51 information relationships within business performance
management processes
The questionnaire was developed within an electronic web based system hosted on an
external environment plus hard copies were also printed for companies close to the author’s
base of work. The questionnaire is included in annexure A. The distribution was done through
an electronic link in a web group and physical delivery of hard copies to companies. A time
frame of three weeks was given for respondents.
3.3.3. Sample group and size
The main target group of the study was from executive level down to engineering. All
functions within the business were included finance, production, maintenance, human
resources, technical, health and safety, strategic and general management. The reason for
the wide spread, is due to the value chain depicted in figure 3.2.1, indicating a complex
interlinked processes that needs orchestration by all. The sample composition was a broad
spectrum in regards to gender, experience, levels and functions within the mining and
manufacturing of natural resources.
The number of returns from a population of 467 was 187. Table 3.2.3 indicates the sample
response. Table 3.2.4 summarises the response according to management level within he
business. The major groups contributing to the questionnaire were engineering and middle
management levels, contributing 81% of the response.
Table 3.3.1: Detail of response size
Area of responsibility Number
(N) Position Level
Engineering
Middle Management 6
Senior Management 4
Engineering 15
Financial
34
Middle Management 10
Senior Management 2
Executive
Management 1
Engineering 21
General Management
Middle Management 2
Senior Management 4
Executive
Management 1
Engineering 6
Health & Safety
Middle Management 2
Senior Management 1
Engineering 4
Human Resources
Middle Management 8
Senior Management 5
Engineering 7
Other
Missing 1
Middle Management 7
Engineering 2
Production
Middle Management 12
Senior Management 6
Engineering 16
Technical
Middle Management 6
Senior Management 7
Engineering 16
Missing
Missing 1
Middle Management 2
Strategic
Middle Management 7
Senior Management 2
Engineering 3
35
Table 3.3.2: Summary of response size
Area of responsibility Number
(N)
Percentage
of response
Position Level
Summary
Middle Management 62 33%
Senior Management 31 17%
Executive Management 2 1%
Engineering 90 48%
(blank) 2 1%
Grand Total 187 100%
Sample sizes are determinable on the collection of the data to ensure that the confidence
levels are marginal enough to make decisions on the statistics. To determine the sample
size three aspects need to be considered; the confidence level desired, acceptable sampling
error and the population proportion.
The following equation is used to determine the sample size for the proportion in equation 3.1
below:
Equation 3.1: Sample size determination for the proposition
? =
?
?
?(1 ? ?)
?
?
Where:
n = sample size
Z = desired confidence level (1.96 for 95% confidence level)
? = population proportion (no prior estimate of the population proportion select 0.5 for
maximum result)
e = sampling error, in this case 10%
Source: Levine, et al. (2008:303)
From equation 3.1 above, it was calculated with the set values to have a sample of 97
questionnaires to be returned. The total received was 187, for which is above the minimum
requirement and we can conclude that it is representative of the opinion of the population.
36
3.4. DESCRIPTION OF DEMOGRAPHICAL INFORMATION
Percentage of respondents per natural resource sector is summarised below in figure 3.4.1.
The manganese, coal and aluminium sectors were more responsive 25%, 19% and 19%
respectively. Other demographics of the respondents are summarised below in figure 3.2.
The position level responded were mostly the engineering level, with a total of 49%, followed
by middle management of 33% and senior management on 17%. Executive management
contributed 1% of all respondents.
Figure 3.3.3.1: Respondents per Natural Resource
On the gender, the female constituted a 40% of the total. The functional area for
representation was widely spread across all functions, with the highest respondents of
financial (18%), technical (16%), production (18%) and engineering (13%).
The working experiences of the respondents are also distributed across the categories of
years, with a 30% response rate to the 10 – 15 years working experience.
37
Figure 3.2: Respondents’ other demographics
3.5. OVERVIEW OF RESPONSES
There was a relative good response from respondents on questions indicated for
correlations. A range of 5 to 14 missing answers were counted on these questions. Question
10R to 15R there was a range of 9 to 35 taken out of the data set, as the questions were re-
coded to eliminate irrelevant aspects from the analysis. See annexure C for detail of
response.
38
3.6. FREQUENCY ANALYSIS AND DESCRIPTIVE STATISTICS
We use analytics to get an idea of why we see a variation in the responses. To identify the
sources of variation on the data set [questions 10R to 15R, 17, 18, 31, and 33 to 51]; the
author looked at statistical significance and practical significance.
The null hypothesis test is done through methods of statistical significance indicating the
coincidence of what is being seen in the data set. The question is if the population will also
show this difference or correlation which is indicated by the sample. We use the p-value with
a value of ? 0.05 to state a 95% probability that the correlation or difference will also be
reflected in the population.
The practical significance indicates the effect size of this correlation or difference to have an
impact in reality, (Steyn, 2002: 10-15).
The tool - Cohen's “d” and the effect size “r” was used to indicate the practical significance.
Consideration will be given for r-value to be >= to 0.3 for practically visible and a 0.5 will be
considered as a practical significance. See table 3.5.1 for r-value.
Table 3.6.1: Cohen’s guideline to effect size
Test Value Small Medium Large
Compare groups d 0.2 0.5 0.8
Correlation associations
(effect size)
r 0.1 0.3 0.5
Source: adapted from Cohen, 1988:20-27
Parametric and non-parametric tests were conducted on the responses. Parametric tests are
more powerful but it requires the data to be normally distributed and groups to have variation.
The following tests for normality were conducted: Kolmogorov-Smirnoff (non-parametric),
Shapiro-Wilk (parametric) and the (quantile-quantile) QQ-plots were used for assessing this
normality.
To conclude, we tested for deviations from assumptions as indicated above. However, no
severe deviations were found. Also to be noted, to ensure accurate representation both non-
39
parametric (Spearman’s rho test) and parametric tests were performed against the sample
data.
The SPSS software package was used for the frequency analysis and descriptive statistics.
3.7. COMPARISON BETWEEN THE NEW MANAGEMENT LEVELS
The management levels were re-coded into two levels, namely NewManagement and
NewEngineers. NewManagement re-code consists of executive management, senior
management and middle management. NewEngineers consist of the engineering level.
The responses are divided in a half position by these new groups. The NewManagement and
NewEngineers groups respectively had 52.4% and 48.6%, see table 3.8.1, of the frequency
of 95 and 90 responses. There were 2 responses missing from the total response count.
Table 3.7.1: Managers and Engineers re-coded
Frequency Percent
Valid
Percent
Cumulative
Percent Frequency Percent
Valid
Percent
Cumulative
Percent
1 2 1.1 1.1 1.1 95 50.8 51.4 51.4
2 31 16.6 16.8 17.8 90 48.1 48.6 100.0
3 62 33.2 33.5 51.4
4 90 48.1 48.6 100.0
Total 185 98.9 100.0 185 98.9 100.0
Missing System 2 1.1 2 1.1
187 100.0 187 100.0
Q2 Q2New
Valid
Total
To find a more suitable correlation between business performance management and
business intelligence, the positive reply on businesses making use of a business intelligence
system within the business, were narrowed down, in order to keep only intelligence owners
where they have business intelligence totally used in the business or where it is used in 2 or
more departments within the business. Table 3.8.2 indicates the distribution of the 96
respondents divided in only 12.5% having business intelligence used totally within the
business. The remainder of 87.5% are businesses using business intelligence in 2 or more
areas within the business.
40
Table 3.7.2: Business Intelligence re-coded
Frequency Percent
Valid
Percent
Cumulative
Percent Frequency Percent
Valid
Percent
Cumulative
Percent
1 12 6.4 6.6 6.6 12 6.4 12.5 12.5
2 84 44.9 46.4 53.0 84 44.9 87.5 100.0
3 80 42.8 44.2 97.2
4 5 2.7 2.8 100.0
Total 181 96.8 100.0 96 51.3 100.0
Missing System 6 3.2 91 48.7
187 100.0 187 100.0
Q20 Q20_1and2
Valid
Total
These applied re-codes and filtered criteria are applied to the responses that will be
discussed within the result discussion.
3.8. DISCUSSION OF RESULTS
3.8.1. Relationship of NewManagers responses
The following statistical- and practical significances, see table 3.8.1, were detected on the
responses, with the applied filtered criteria described in §3.7. Table 3.8.1 is a summary of the
defined (post hoc t-tests) and the corresponding effect sizes where results met the criteria of
table 3.6.1. All effect sizes (correlations) are positive of nature and vary from medium to
large. The focus will be placed on the large effect sizes.
Respondents, who indicated to have in use business intelligence systems, were
acknowledging business performance management and business intelligence has a
correlating association in assisting them in reaching business objectives, (r = 0.658). In the
literature, figure 2.2.2 indicates the business performance management, with business
intelligence as a sub-process supporting it. The correlation coefficient is positive, indicating
some relationship between business performance management and business intelligence in
support of business objectives.
41
Table 3.8.1: Managers – BI and BPM correlations
Questions relationship
Correlation
Coefficient (r)
Significance
(p)
N
Business performance management assist in business goals
- >
Business intelligence assist in reaching the business goals
0.658 0.0000001 54
Business intelligence assist in corrective actions taken
->
Business intelligence assist in strategizing processes
0.363 0.0075427 53
Business intelligence assist in identifying strategies
->
Business intelligence assist in identifying actions
0.555 0.0000158 53
Business intelligence assist in creating plans
->
Business intelligence assist in reaching the business goals
0.526 0.0000527 53
Business intelligence assist in creating plans
->
Business performance management assist in business goals
0.422 0.0016512 53
Business performance management assist in managing
objectives
->
Business intelligence assist in reaching the business goals
0.417 0.0020989 52
Business performance management assist in managing
objectives
->
Business performance management assist in business goals
0.355 0.0097780 52
Business performance management assist in managing plans
->
Business intelligence assist in identifying actions
0.53 0.0000448 53
Business performance management assist in managing plans
->
Business intelligence assist in identifying strategies
0.429 0.0013570 53
Business performance management assist in managing plans
->
Business performance management assist in managing
objectives
0.359 0.0090116 52
The identification of strategies and corrective actions has however have a high correlation
association. This could be seen somewhat controversial to the above paragraph on a lower
correlation association between using business intelligence in these processes. With an r-
value of 0.555, it seems that the business intelligence is used for some data mining activities,
to explore identification of corrective actions and strategies.
Business goals defined in this perspective are as follow: it is time-based measurements that
are a resultant of the strategy that will be implemented, (PlanWare, 2011). From the
correlation coefficient on the questions posed to the respondents, if business intelligence is
assisting in planning and the business goals; as well as business performance management
the 0.526 indicates a high level of correlation. From the
formalising the strategy of a business
more focus where you want to be. This is creating a cavity to the norm that exists on
performance. The setting of goals creates
competitive level. Goals are measurable and in order to define it with the current level
performance, a tool is needed to supply the data.
highlights the business performance management process (strategise, plan, monit
analyse and corrective actions) with two blocks indicating a
questionnaire results from the respondents. In the top right, goals are an output of the
function strategy and business intelligence is an input to the process
function (right bottom), indicates the achievable measurements as an output, supportive of
business intelligence to the process.
Figure 3.8.1.1: Strategise versus Plan
From figure 3.8.2 there is a high correlation association between business performance
management supporting the planning function and business intelligence supporting the
actions to be identified, (r = 0.53).
Corrective
Actions
Monitor &
Analysis
on the questions posed to the respondents, if business intelligence is
assisting in planning and the business goals; as well as business performance management
the 0.526 indicates a high level of correlation. From the executive blue-sky ideas to
ing the strategy of a business, less emphasis is on internal business status, with
where you want to be. This is creating a cavity to the norm that exists on
setting of goals creates the bridge to leap from the norm to the new
Goals are measurable and in order to define it with the current level
performance, a tool is needed to supply the data. To indicate this crisper, figure 3.8.1
the business performance management process (strategise, plan, monit
analyse and corrective actions) with two blocks indicating an in/out put perspective to the
questionnaire results from the respondents. In the top right, goals are an output of the
function strategy and business intelligence is an input to the process. Moving to the plan
function (right bottom), indicates the achievable measurements as an output, supportive of
to the process.
Strategise versus Plan
3.8.2 there is a high correlation association between business performance
management supporting the planning function and business intelligence supporting the
actions to be identified, (r = 0.53).
• Achievable
Measurements (output)
• Business Intelligence
(input)
• r= 0.422
• Goals (output)
• Business Intelligence
(input)
• r=0.526
Corrective
Actions
Strategise
Plan
Monitor &
Analysis
42
on the questions posed to the respondents, if business intelligence is
assisting in planning and the business goals; as well as business performance management,
sky ideas to
, less emphasis is on internal business status, with
where you want to be. This is creating a cavity to the norm that exists on
the bridge to leap from the norm to the new
Goals are measurable and in order to define it with the current level
To indicate this crisper, figure 3.8.1
the business performance management process (strategise, plan, monitor &
perspective to the
questionnaire results from the respondents. In the top right, goals are an output of the
. Moving to the plan
function (right bottom), indicates the achievable measurements as an output, supportive of
3.8.2 there is a high correlation association between business performance
management supporting the planning function and business intelligence supporting the
Measurements (output)
Business Intelligence
Due to the re-coding of the management levels, it seems th
described on basis of putting plans into actions. As business performance management
drives the process from strategising to corrective actions, it seems the planning to corrective
actions is dictated by this process. On the othe
formalise a view of what the current status quo is and what could be the problem area where
action is required. Once again this is not a daily action of tasks but more focused on strategic
actions.
Figure 3.8.1.2: Plan versus Actions
3.8.2. Relationship of NewEngineers responses
The following statistical- and practical significances, see table 3.8.2, were detected on the
responses, with the applied filtered criteria described in §3.7. Table 3.8.2 is a summary of the
defined (post hoc t-tests) and the corresponding effect sizes whe
table 3.6.1. One finding of effect size (correlations)
vary from medium to mid-large positions
• Actions (output)
• Business Intelligence
(input)
• r=0.53
Corrective
Actions
Monitor &
Analysis
coding of the management levels, it seems that the relationship can be
described on basis of putting plans into actions. As business performance management
drives the process from strategising to corrective actions, it seems the planning to corrective
actions is dictated by this process. On the other hand business intelligence is used to
formalise a view of what the current status quo is and what could be the problem area where
action is required. Once again this is not a daily action of tasks but more focused on strategic
: Plan versus Actions
Relationship of NewEngineers responses
and practical significances, see table 3.8.2, were detected on the
responses, with the applied filtered criteria described in §3.7. Table 3.8.2 is a summary of the
tests) and the corresponding effect sizes where results met the criteria of
effect size (correlations) is negative of nature and
large positions.
• Plans(output)
• Business performance
management (input)
• r= 0.53
Corrective
Actions
Strategise
Plan
Monitor &
Analysis
43
at the relationship can be
described on basis of putting plans into actions. As business performance management
drives the process from strategising to corrective actions, it seems the planning to corrective
r hand business intelligence is used to
formalise a view of what the current status quo is and what could be the problem area where
action is required. Once again this is not a daily action of tasks but more focused on strategic
and practical significances, see table 3.8.2, were detected on the
responses, with the applied filtered criteria described in §3.7. Table 3.8.2 is a summary of the
re results met the criteria of
of nature and areas of note
Business performance
management (input)
44
Table 3.8.2: Engineers – BI and BPM correlations
Questions relationship
Correlation
Coefficient (r)
Significance
(p)
N
Business performance management assist in business goals
- >
Business intelligence assist in reaching the business goals 0.395 0.0128487 39
Business intelligence assist in corrective actions taken
->
Business intelligence assist in reaching the business goals 0.317 0.0492333 39
Business intelligence assist in identifying strategies
->
Business intelligence assist in identifying actions 0.418 0.0080459 39
Business performance management assist in managing
objectives
->
Business intelligence assist in reaching the business goals -0.371 0.0200606 39
Business performance management assist in managing
objectives
->
Business intelligence assist in identifying actions 0.328 0.0413856 39
Business performance management assist in managing plans
->
Business intelligence assist in monitor & analysis processes 0.379 0.0173969 39
Business performance management assist in managing plans
->
Business intelligence assist in creating plans 0.32 0.0473781 39
Business performance management assist in analyse &
monitoring
->
Business intelligence assist in reaching the business goals -0.30345731 0.0603828 39
Business performance management assist in analyse &
monitoring
->
Business intelligence assist in planning processes -0.333 0.0380095 39
Respondents from the NewEngineering level also indicate a medium correlation association
between business performance management and business intelligence as the NewManagers
level. This point will not be laboured more.
Respondents from the NewEngineering level also indicate a correlation association of
medium to large between business intelligence identifying strategies and actions as the
NewManagers level. This point will not be laboured more.
A negative correlation, figure 3.8.2.1, between business performance management assisting
in managing objectives towards business intelligence assisting business goals, (r = -0.371).
In the NewManagement group, the management level indicated a positive correlation
45
association. This phenomenon raises other questions. Is the engineering level exposed to
generating business goals? Are they the receiving end of goals to be met? Is it an indication
of workforce acting upon goals set and achievement of actions is measured through key
performance indicators?
Figure 3.8.2.1: Business Performance Management objectives versus Business
Intelligence supporting goals
There was a strategic significance between business performance management supporting
the planning function and business intelligence assisting the monitor & analysis processes, (p
= 0.0173969).
We also found a practical significance correlation between business performance
management supporting the planning function and business intelligence assisting the monitor
& analysis processes, (r = 0.379).
From figure 3.8.2.2 this medium correlation association between business performance
management supporting the planning function and business intelligence assisting the monitor
& analysis processes is indicated. Respondents who are grouped in the NewEngineers group
seems to have the same agreement of business performance management to assist the plan
function, however the business intelligence was more prominent to be supporting in the
monitor & analysis function. It might be assumed that these two functions are more pertinent
in their daily activities in the business.
Figure 3.8.2.2: Plan versus Monitor & Analysis
3.8.3. Information Relationships
From ad hoc t-tests we found that businesses who were satisfied with their business
performance management system, that is used to steer the business, showed a positive
practical significance (r = 0.325
defining it within the monitor & analysis process, table 3.8.3 indicates significance.
Here is could be argued that the business has some level of business intelligence process
within the business and using business performan
performance metrics/indicators. They are also in some sense agile to business situation in
the milieu it performs.
• Business
Intelligence
(input)
• r=0.379
Corrective
Actions
Monitor &
Analysis
monitor & analysis function. It might be assumed that these two functions are more pertinent
in their daily activities in the business.
Monitor & Analysis
Information Relationships
tests we found that businesses who were satisfied with their business
performance management system, that is used to steer the business, showed a positive
practical significance (r = 0.325 - medium) towards information relationships needed when
defining it within the monitor & analysis process, table 3.8.3 indicates significance.
Here is could be argued that the business has some level of business intelligence process
within the business and using business performance management to support certain key
performance metrics/indicators. They are also in some sense agile to business situation in
• Plans(output)
• Business performance
management (input)
• r= 0.379
Corrective
Actions
Strategise
Plan
Monitor &
Analysis
46
monitor & analysis function. It might be assumed that these two functions are more pertinent
tests we found that businesses who were satisfied with their business
performance management system, that is used to steer the business, showed a positive
ion relationships needed when
defining it within the monitor & analysis process, table 3.8.3 indicates significance.
Here is could be argued that the business has some level of business intelligence process
ce management to support certain key
performance metrics/indicators. They are also in some sense agile to business situation in
Business performance
management (input)
47
Table 3.8.3: Information relationships
Questions relationship
Correlation
Coefficient
(r)
Significance
(p)
N Missing
Defining monitor and analysis to support the plans,
information relationships needed
->
Satisfaction of the business with business
performance management's agility in steering the
business
0.325 0.0000536 149 38
3.9. CONCLUSION
From the above analysis we tried to establish some relationship between business
intelligence and business performance management. From the analysis the following aspects
seems to appear:
• Senior management level of usage of business intelligence do differ from the lower
levels within a business
• Business intelligence is used in a more identification role, to explore possibilities and
to determine the unknown for senior management levels
• Business intelligence is used by lower levels in the business to monitor and analyse
key performance indicators, the goals that were set, and try to define reasoning to it
• It seems there is a relationship for the use of the business performance management
and business intelligence between the strategising and planning function of business
performance management for senior managers
• It seems there is a relationship for the use of the business performance management
and business intelligence between the planning and monitor & analysis function of
business performance management of lower levels in the business
• There was an indication that senior management uses business intelligence for some
sense of guidance to corrective actions, most probably for long term direction
• There is a supporting relationship between business performance management and
business intelligence, which is some cases are very closely interlinked and might pose
a hinder if one of two is not present.
48
We can thus conclude that businesses that do have both frameworks established within the
business, shows supporting relationships between business intelligence and business
performance management and that the level of management has different needs in using it.
3.10. SUMMARY
Chapter 3 was dedicated to the statistical analysis of the questionnaire that was based on the
literature study in chapter 2.
Firstly we looked at the natural resources sector within South Africa. The contribution it has to
our countries GDP and the diversity of natural resources available in South Africa. We
highlighted the external pressures on the mining and manufacturing environment and
appreciate the complexity of the value chain these businesses have. We realised that the
external pressures are not temporarily and that more are to come. The image in managing
these businesses we reflect impacts the investment done in the country.
The second area, we discussed the quantitative research and survey instruments that can be
used in gathering response from the population. The questionnaire was used for this
empirical study and the questionnaire’s layout was grouped with a short description. The
sample group and size were discussed. The response of the sample was detailed in function
perspective and level of management.
The third area, we looked at the demographics of the responses. 49% of the responses were
from engineering level, 33% for middle management, 17% for senior management and 1%
for executive management. The size of the sample group was 467 and a response of 187
questionnaires was received.
The fourth area covered the descriptive statistics and the frequency analysis. The method of
statistical significance was used to test the null hypothesis, indicating the coincidence of the
data reflection. The Cohen’s “d” and the effect size “r” tool were used for indication of
practical significance. Normality and variation tests (parametric and non-parametric) were
conducted on the responses.
49
The fifth area, we discussed the re-coding of the management levels in the response. The t-
tests indicated a substantial correlation when the management levels were grouped.
Executive to middle management was grouped as a new variable and the Engineers variable
was kept the same. It was also found that the businesses that do have business intelligence
systems show correlations with business performance management aspects. Therefore new
variables were created for those who have.
The sixth area, the findings of the analysis was discussed. Some similarities and differences
were found between the NewManagement and NewEngineers variables. The
NewManagement variable indicated a correlation association between business intelligence
and business performance management between the strategising and planning function of
business performance management. For the NewEngineers variable a correlation association
between business intelligence and business performance management between the planning
and monitor & analysis function of business performance management was detected.
The last part, the correlation of businesses that were satisfied with their business
performance management systems showed a positive association towards the relationship of
information used in the analysis & monitor function of it.
The final conclusions were derived from the findings and to build some sense of the
relationships that were found between the NewManagers and NewEngineers variables in the
natural resource sector.
Chapter 4 will be discussing the conclusions and recommendations of the empirical study.
50
CHAPTER 4
CONCLUSION AND RECOMMENDATIONS
4.1. INTRODUCTION
The primary objective of this study was to assess a relationship between business
performance management and business intelligence. During the literature research, the
function of both business performance management and business intelligence was
discussed. The relationship between business intelligence and business performance
management in the mining and manufacturing sector was researched through a literature
study which was discussed in chapter 2. The empirical study was discussed in relations to
the literature study in chapter 3.
As stated in §1.6, chapter 4 is devoted to draw conclusion from the survey and putting
forward recommendations for the establishment of business performance management
and business intelligence within the mining and manufacturing sector to catapult
performance of this industry in South Africa. The relationships between business
performance management and business intelligence in businesses in this sector were
analysed. A practical approach for the successful implementation of business
performance management and business intelligence is proposed to be used by the South
African mining and manufacturing sector to establish a competitive position in the natural
resource market by utilising these spheres to unlock potential in the businesses.
4.2. BUSINESS PERFORMANCE MANAGEMENT AND BUSINESS INTELLIGENCE
The literature and empirical research done in chapter 2 and 3 indicated relationships between
business intelligence and business performance management and the use of it to promote
synchronised efforts in the business to reach the goals. Business performance management
and business intelligence are both needed and it would be very difficult to have only one and
not the other to establish a competitive position in the market.
In figure 4.2.1 the input from business int
performance management processes. The empirical research confirmed relationships
between business intelligence and business performance management; however the
executive to middle management has a different ne
engineering level of the businesses.
Figure 3.8.3.1: Inputs of Business Intelligence
•Business
intelligence used as
input to view
indicators and
analyse situations
•Business
intelligence used
as input to define
strategic actions
Corrective
Actions
Monitor &
Analysis
4.2.1 the input from business intelligence is indicated in each of the business
performance management processes. The empirical research confirmed relationships
between business intelligence and business performance management; however the
executive to middle management has a different need for use of business intelligence to the
engineering level of the businesses.
: Inputs of Business Intelligence
•Business
intelligence used as
input to derive
plans and compile
key indicators
•Busines intellgence
used as input to
decision making,
predictive models
Corrective
Actions
Strategise
Plan
Monitor &
Analysis
51
elligence is indicated in each of the business
performance management processes. The empirical research confirmed relationships
between business intelligence and business performance management; however the
ed for use of business intelligence to the
Busines intellgence
Figure 3.8.3.2: Relationships of Use by Organisational Level
Figure 4.2.2 indicates the use of business intelligence by the organisation level in the
businesses, based on responses of the questionnaire.
The findings are summarized as followed:
• When moving upwards in
changes and this would be agreed that the focus of levels do differ over the planning
horizon
• Business intelligence has the capability to open up the unknown and give a sense of
“what does this mean”, “where are we”, “what can we do” questions
• Business intelligence has got the capability to create the one place to host all
information needs
• Business intelligence on its own will not synchronise all business efforts into reaching
business goals. A formal structured approach is needed to facilitate direction.
• Business intelligence span of use is from short to long term. Real
intelligence is a new addition to the business intelligence space and is more widely
promoted.
Relationships of Use by Organisational Level
Figure 4.2.2 indicates the use of business intelligence by the organisation level in the
businesses, based on responses of the questionnaire.
The findings are summarized as followed:
When moving upwards in the level of management the usage of business intelligence
changes and this would be agreed that the focus of levels do differ over the planning
Business intelligence has the capability to open up the unknown and give a sense of
n”, “where are we”, “what can we do” questions
Business intelligence has got the capability to create the one place to host all
Business intelligence on its own will not synchronise all business efforts into reaching
mal structured approach is needed to facilitate direction.
Business intelligence span of use is from short to long term. Real-time business
intelligence is a new addition to the business intelligence space and is more widely
Executives to middle
management
• Strategising + PLanning
• Corrective actions + Plan
Engineering level
• Planning + Monitor &
Analysis
• Monitor progress
52
Figure 4.2.2 indicates the use of business intelligence by the organisation level in the
the level of management the usage of business intelligence
changes and this would be agreed that the focus of levels do differ over the planning
Business intelligence has the capability to open up the unknown and give a sense of
Business intelligence has got the capability to create the one place to host all
Business intelligence on its own will not synchronise all business efforts into reaching
mal structured approach is needed to facilitate direction.
time business
intelligence is a new addition to the business intelligence space and is more widely
53
• Business intelligence and business performance management are both dependent on
each other to deliver a total performance package to a business.
Based on the above findings, it could be stated that business intelligence and business
performance management are a necessity for businesses and it would be rocky roads ahead
to establish the one could do without the other.
4.3. PRACTICAL DESIGN PRINCIPLES FOR A BUSINESS PERFORMANCE
MANAGEMENT AND BUSINESS INTELLIGENCE PROCESS
In the market there are numerous consulting firms that can assist in the deployment of
business performance management and business intelligence systems and processes. Some
will indicate a preference to a technology supplier, some will not indicate a preference and
will leave it to the business and some will not use a technology to base the processes on.
It might be worthwhile to explore these possibilities and to construct interviews with the
relevant consultants. Arrange current customer visits and try to establish some sense of
project success and effort. The approach discussed in this chapter is based on the author’s
experience of a non-technology approach. Business intelligence was not part of the scope,
deliberately. The approach was to embed the business performance management process
within the business by utilizing excel spreadsheets as predominant technology. This
approach was shot down by many business intelligence vendors. The advantage of this is to
ensure you understand your business’ value chain (value driver tree), information availability
and data structures. The added benefit of this approach, was the development time that were
minimised when the business intelligence project initiated.
Upfront -
1) Corporate objectives signed and agreed upon up front on delivery of the business
performance management solution
2) Establish a roadmap. Indicate the current state of the business and indicate the
end state. Plot down the approach to be taken, i.e. technology specific, any
technology or no technology.
54
3) Establish how the business performance management process will fit on the
current business structure. Are there any natural teams that build the hierarchy to
the top?
4) Select proven consulting (if outsourcing) vendors to assist in the project.
5) Select the best personnel in the business, from different levels, to assist in the
project.
A manufacturing business in Gauteng has partnered with a company from Australia, which
implement business performance management on top of the natural teams that existed on
the safety behaviour philosophy in the business. The project included defining the correct
value driver trees (VDT’s), improvement pipeline and a sustainable review process (business
performance management) to identify, monitor and control satisfying performance levels
constantly.
A mixed approach was decided upon, where the most impact could be derived on the
demarcated area of the business. A long-term plan was developed to indicate the growth of
the deployment. Approaching from a bottom up will create performance silos and putting the
project at risk. To avoid this, corporate objectives were created, with milestones and
priorities.
The business performance management system consists of:
• Dashboards
• Business intelligence reports to drill down into specific information relevant to the level
in which the employee is accountable for
• Task management
• Idea pipeline
• Review and performance meetings
4.3.1. Review and Performance Meeting
The business’ review and performance meeting (RPM), as indicated by figure 4.2.3, is a
process whereby alignment of people to business goals are done through key performance
indicators, task management and idea generation sessions. The measurable targets was
55
developed from the strategic goals and disseminated unto the lowest level within the
business and reviewed periodically (weekly to monthly) for deviations. This process is linked
to the cycle of business performance management for continuous performance.
Figure 3.8.3.1: Review Performance Management with accountability
GM
Manager
Superintendent/ Direct Reports
Manager
Supervisor
Mini-Business
Teams (MBT)
Supervisor
Superintendent/ Direct Reports
Mini-Business
Teams (MBT)
Information flow is 2-way
between each level
KPI complexity and
accountabilities are
tailored for each level
Source: PIP International - Adapted from wiring process
4.3.2. Wiring
Wiring is referred to as the formation of natural teams within the business, where the teams
can be grouped together to facilitate and report upwards the next layer of business key
indicators. The wiring also limits the information available to the team or individual based on
the position held. With this process the goals are broken up in lower levels in the business,
dictated by the value chain of the business and the accountability the position of an individual
are holding, and assigned to the position. This process is linked to the monitoring & analysing
and corrective actions sub-process of business performance management. The process
ensures the teams understand the lower objectives of the business, expectations and
deliverables of actionable tasks to accomplish goals (key performance indicators). The teams
monitor and execute accordingly to obtain good performance levels by guidance from the
dashboards and business intelligence reports.
General Manager
56
4.3.3. Key Performance Indicator Management
When the natural teams were formed, key performance indicators were assigned to them in
accordance to the level in which they are based in the business. These key performance
indicators have targets and are reviewed in the periodic review sessions. The targets are
broken down, just as the actual contribution of the indicator is represented. This section is
referred to the planning sub-process of the business performance management. Informed
actions are assigned to unfavourable outcomes. In figure 4.3.1.1, indicates the teams that are
on the lowest level within the business. The complexity of the key performance indicators
enlarge when moved upwards to higher levels in the business. Teams and individuals are
accountable for the key performance indicator level to which they are assigned to.
4.3.4. Task management
Collaboration between employees follows a structured approach for assignment of tasks to
one another. Actions are tracked within a system and linked to key performance indicators.
This is referred in the business performance management sub-process as corrective actions.
Predefined rule are applicable to allocating tasks to individuals and the re-assignment of it.
The process keeps track of the tasks and notifications of it to the originator, to view progress.
4.3.5. Idea Management
The “turbo” button that was indicated in §2.2.2, called business improvement, is facilitated
through the idea management process. The improvement process is a culture change, due to
the willingness of improvement contributions (ideas) that are needed from employees. The
process has got a “bucket” to receive these improvements, see figure 4.3.5.1 – opportunity
pool. The improvement process needs a continuous feed of ideas that will be reviewed and
prioritised for implementation. The business improvement process will also follow a
structured approach to maintain discipline and consistent measurable outcomes according to
a set standard.
57
Figure 3.8.3.1: Idea pipeline
Evaluation
Implem-
entation
Cash Flowing
(Delivering
Results)
Locked-In
&
Tracking
Idea
Opportunity
Pool
Idea
Idea
4 Gates
Idea
Source: Adapted from operational company
Figure 3.8.3.2 indicates a decline in time if the improvement process is not sustained. This
could be translated into loss of competitiveness. It also indicates the future possibility of
improvement that could be realised if all ideas are taken through to execution or
implementation. A healthy graph will always point in the upwards tendency. This is only
possible if there is an adequate pool of ideas being generated within the business.
Figure 3.8.3.2: Value creation of ideas
Planning Horizon
Avoid
the drop
0
10
20
30
40
50
60
-4 -3 -2 -1 Today 1 2 3 4
R
e
v
e
n
u
e
Historic growth rate
Close
the gap
Growth target
Source: Adapted from an operational company.
Ideas are generated through idea sessions. The idea generation supplies a healthy pipeline,
whereby a pool of ideas could be evaluated to determine the best ROI ideas to be put
58
forward for execution in the pipeline. Ideas are evaluated through a matrix, in the evaluation
process, and prioritised, see figure 3.8.3.1. Ideas put forward are implemented and then
moved on when implementation was completed. The specific value driver tree where the idea
is impacting the business is monitored for quality insurance of the executed work being done,
in the cash flowing stage, see figure 3.8.3.1. When the value of the idea is reaching a certain
milestone, it indicates the idea realised into a culture change and the business has accepted
the new way of performing in the new process. The idea is moved to the next stage of locked-
in and tracking. This stage enforces the value that was forecasted on the idea, to be
evaluated against actuals. All key performance indicators influenced by the idea are changed
and targets are updated to reflect the new standard.
The complete process of idea generation, evaluation, selection, execution, locked-in, and
close are the basic steps for an idea to go through the ranks of imbedding the improvement
into the business.
4.3.6. Impacts
How does this impact the business having a business performance management process
embedded? Transparency of performance is much higher up in the business, available on a
frequent time schedule. Closer relationships are established of moving actions forward.
Closer relationships are established between the business improvement departments and the
information management department.
4.4. RECOMMENDATIONS
It is recommended that all mining and manufacturing businesses to understand the
differences between business performance management and business intelligence as two
different processes and the output each process supply. There are relationships as the two
processes interact. Don’t expect delivery of a business intelligence system to deliver
business performance management, visa versa for expecting data mining capabilities out of a
business performance management process.
59
Understand the value chain of the business, quality of the data, as both business intelligence
and business performance management are information dependent.
The recommended approach if one needs to decide between the two for implementation, the
business performance management would be the author’s first choice. This gives way of
organising the data to information relationships and structures.
4.5. RECOMMENDED FURTHER STUDIES
Further research to be conducted in the field of real-time business intelligence in supporting
the business performance management process. Operational processing is based on
immediate actions to be taken. This makes the normal cycle of costing, normal monthly, to be
too slow for responding to the variability.
Secondly, the predictability of value chain impacts in business intelligence, set by goals
defined for the mining and manufacturing industry. The total value chain as an input to the
predictive model to analyse decisions made on longer horizons.
4.6. CONCLUSION
The aim of the study was to indicate if there are any relationships between business
intelligence and business performance management and the effect the two processes have
on each other within the natural resource sector. The responses were compared against
others in the industry to see if there are similarities to how other businesses perceive the two
processes.
A survey was conducted to determine the affect the two processes (business intelligence and
business performance management) do have on each other. The result indicated that the two
processes are dependent on each other through decisions that need to take place. Different
levels within the organisation have different usage for the processes.
Executive to middle management levels are more dominantly relying on business intelligence
to formalise strategies and converting it into solid plans. There was also a positive correlation
60
between the use of business intelligence in the planning and corrective action processes of
business performance management.
In the engineering level there was a negative correlation between business performance
management assisting in managing objectives towards business intelligence assisting
business goals.
The combination of the two spheres being deployed at an organisation will result in quicker
turn around on reaching goals in the business. Embedment of these processes result in
improved and organised contributions towards the goals in the business.
4.7. SUMMARY
The first part of the chapter was dedicated to discuss the reason why the empirical study was
conducted and drawing the conclusion from the findings in chapter 3. The relationships of the
two systems on each other were highlighted and the use of it by different levels in the
business was indicated.
Secondly, a practical approach of such processes being embedded within a business as
elaborated on. The upfront activities that need to be checked before entering into a project
might save some unnecessary pit fall along the way.
A typical business performance management process was highlighted and gives a clearer
view to how the process and system could look and work. Indication of the improvement
process that’s like a “turbo” button on the business performance management process was
explained.
High level impacts were raised and would differ from organisation to organisation. Most
cases people feel intimidated by the exposure of information being rolled up into higher levels
(Big Brother-effect). Recommendation into the real-time environments was given for further
studies.
Finally it was concluded that the research objectives as set out in §1.6 were met and possible
future research was recommended.
61
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64
ANNEXURE A
65
66
67
68
69
70
71
72
73
74
75
76
77
78
ANNEXURE B
79
ANNEXURE C
Question
Number
Question Description
Valid % (Frequency)
Mean
Std.
Deviation
Number
Missing
Very
Relevant
Relevant
Almost
Relevant
Irrelevant
Q10R Business BPM satisfied - Evidence
21.35 62.36 16.29 1.95 .61316 9
Q11R Business BPM satisfied - KPI's
33.33 47.46 19.21 1.86 .71298 10
Q12R Business BPM satisfied - Integration business
processes
26.75 51.59 21.66 1.95 .69611 30
Q13R Business BPM satisfied - Agility to steer
business
22.29 50.96 26.75 2.04 .70113 30
Q14R Business BPM satisfied - Align strategy and
execution
19.23 60.90 19.87 2.01 .62730 31
Q15R Business BPM satisfied - Learning
organisation
16.45 58.55 25.00 2.09 .64020 35
Q17 Buisness value BPM in business
16.57 49.17 25.41 8.84 2.27 .841 6
Q18 IM value BPM in business
19.78 41.21 31.87 7.14 2.26 .858 5
Q31 BI will help you with decisions?
30.73 33.52 19.55 16.20 2.21 1.055 8
Q33 BI will help you plan tasks?
25.28 36.52 16.85 21.35 2.34 1.079 9
Q34 BI will help you reach business goals?
23.16 35.59 25.99 15.25 2.33 .998 10
Q35 BPM will help you reach business goals?
25.84 37.08 19.66 17.42 2.29 1.037 9
Q36 BI help in strategy?
24.29 38.42 19.77 17.51 2.31 1.027 10
Q37 BI help in planning?
26.40 38.76 14.61 20.22 2.29 1.069 9
Q38 BI help in monitor and analysis?
28.09 34.27 20.22 17.42 2.27 1.055 9
Q39 BI help in corrective actions?
23.60 32.58 24.72 19.10 2.39 1.048 9
Q40 BI help with id of opportunities?
25.71 34.29 17.14 22.86 2.37 1.101 12
Q41 BI help in id of actions?
21.71 37.71 22.86 17.71 2.37 1.013 12
Q42 BI help in creating strategies?
27.43 31.43 22.86 18.29 2.32 1.067 12
Q43 BI help in creating plans?
24.71 32.18 22.99 20.11 2.39 1.068 13
Q44 BPM assist you in managing business
objectives?
24.28 34.68 22.54 18.50 2.35 1.044 14
Q45 BPM manage plans?
20.00 32.57 28.57 18.86 2.46 1.016 12
Q46 BPM help in monitor and analysis?
12.07 28.16 36.21 23.56 2.71 .961 13
Q47 BPM assist in taking corrective actions?
25.14 34.86 23.43 16.57 2.31 1.028 12
Q48 Define business startegy - info for strategy?
25.14 38.86 20.57 15.43 2.26 1.005 12
Q49 Define business plan - info for plan?
28.74 31.03 19.54 20.69 2.32 1.102 13
Q50 Define monitor and analysis - info for it?
29.31 29.31 21.84 19.54 2.32 1.095 13
Q51 Corrective actions - have information
relationship?
25.29 35.06 21.26 18.39 2.33 1.049 13
doc_568813387.pdf
Leveraging business intelligence management to business performance management in a manufacturing environment
Leveraging business intelligence management to
business performance management in a
manufacturing environment
Stephanus Landman
21943486
Mini-dissertation submitted in partial fulfilment of the requirements
for the degree Master in Business Administration at the
Vanderbijlpark campus of the
North-West University
Study leader: Mr. Johan Coetzee
November 2011
ii
ACKNOWLEDGEMENTS
• To my Lord and Saviour. The journey was set and learning’s were made, but getting
closer to You with each step in my life to learn Your ways.
• To my wife Lorianne, my sons Fanie and Christian; your support and willingness to leave
me for several hours a day.
• My study leader Johan Coetzee, for your time and generous insight to support my ideas
and sometimes confusions in some aspects.
• To Mrs. Antoinette Bisschoff, for the language editing
• To Mari Van Reenen, for statistical analysis
iii
ABSTRACT
No business can effectively be managed without the proper management and information
that reflects and creates the milieu it operates in. Business performance management
creates the framework in which a structured approach can be followed in setting the scene
for a predictive and controllable environment. Business intelligence creates the information
structures; information relationships and a reflection of the value chain of the business. By
combining the two methodologies it creates a total business solution that harmonises all
aspects of value creation in an objective manner.
The aim of this study is to conduct a thorough theoretical study on the relevant aspects
involved in business performance management and business intelligence, and to assess the
relationship of business performance management and business intelligence within the South
African natural resource' mining and manufacturing sector.
The various processes of business performance management and business intelligence are
discussed in the literature study. During the literature research several approaches to
business performance management implementations and the pros and cons of business
performance management are discussed. A broad look at business intelligence is done, with
key focus on delivering of information.
KEY WORDS: Business performance management, business intelligence, value chain, out-
strategise, primary activities, supportive activities
iv
TABLE OF CONTENTS
ACKNOWLEDGEMENTS ....................................................................................................... ii
ABSTRACT ............................................................................................................................ iii
LIST OF FIGURES ................................................................................................................ vii
LIST OF TABLES ................................................................................................................. viii
CHAPTER 1 ............................................................................................................................ 1
1.1. INTRODUCTION ..................................................................................................... 1
1.2. BUSINESS PERFORMANCE MANAGEMENT VERSUS BUSINESS
INTELLIGENCE ...................................................................................................... 2
1.3. IMPORTANCE OF THE STUDY ............................................................................. 3
1.4. PROBLEM STATEMENT ........................................................................................ 4
1.5. CAUSAL FACTORS ............................................................................................... 5
1.6. OBJECTIVES OF THE STUDY ............................................................................... 5
1.1.1. Primary objective ..................................................................................................... 5
1.1.2. Secondary objectives .............................................................................................. 5
1.1.3. Theory evaluation: ................................................................................................... 6
1.1.4. Empirical research: .................................................................................................. 6
1.7. SCOPE AND DEMARCATION OF STUDY ............................................................ 7
1.8. LIMITATIONS .......................................................................................................... 7
1.9. RESEARCH METHODOLOGY ............................................................................... 7
1.10. DIVISION OF CHAPTERS ...................................................................................... 8
1.11. CONCLUSION ........................................................................................................ 9
1.12. CHAPTER SUMMARY ............................................................................................ 9
CHAPTER 2 .......................................................................................................................... 10
2.1. INTRODUCTION ................................................................................................... 10
2.2. BUSINESS PERFORMANCE MANAGEMENT .................................................... 11
2.2.1. Business Performance Management Roadmap for Manufacturing ................ 13
2.2.2. Business Improvement ....................................................................................... 14
2.2.3. Why Business Performance Management ........................................................ 15
2.2.3.1. Advantages ............................................................................................................ 15
2.2.3.2. Disadvantages ....................................................................................................... 16
2.3. BUSINESS INTELLIGENCE ................................................................................. 16
v
2.4. DATA COMPILED INTO INFORMATION ............................................................. 17
2.4.1. Investment into Business Intelligence............................................................... 19
2.4.2. Technology .......................................................................................................... 20
2.4.3. Advantages .......................................................................................................... 21
2.4.4. Disadvantages ..................................................................................................... 21
2.4.5. Summary .............................................................................................................. 21
2.5. RELATIONSHIP BETWEEN BUSINESS PERFORMANCE MANAGEMENT AND
BUSINESS INTELLIGENCE ................................................................................. 22
2.5.1. Business Strategic Management ....................................................................... 24
2.5.2. Summary .............................................................................................................. 25
2.6. CONCLUSION ...................................................................................................... 25
2.7. CHAPTER SUMMARY .......................................................................................... 26
CHAPTER 3 .......................................................................................................................... 28
3.1. INTRODUCTION ................................................................................................... 28
3.2. DISCUSSION OF MINING AND MANUFACTURING ENVIRONMENT................ 28
3.3. THE PROCEDURE AND SCOPE OF THE QUANTITATIVE RESEARCH ........... 31
3.3.1. Survey instrument ............................................................................................... 31
3.3.2. Overview of questionnaire.................................................................................. 32
3.3.3. Sample group and size ....................................................................................... 33
3.4. DESCRIPTION OF DEMOGRAPHICAL INFORMATION ..................................... 36
3.5. OVERVIEW OF RESPONSES .............................................................................. 37
3.6. FREQUENCY ANALYSIS AND DESCRIPTIVE STATISTICS ............................. 38
3.7. COMPARISON BETWEEN THE NEW MANAGEMENT LEVELS ....................... 39
3.8. DISCUSSION OF RESULTS ................................................................................ 40
3.8.1. Relationship of NewManagers responses ........................................................ 40
3.8.2. Relationship of NewEngineers responses ........................................................ 43
3.8.3. Information Relationships .................................................................................. 46
3.9. CONCLUSION ...................................................................................................... 47
3.10. SUMMARY ............................................................................................................ 48
CHAPTER 4 .......................................................................................................................... 50
4.1. INTRODUCTION ................................................................................................... 50
4.2. BUSINESS PERFORMANCE MANAGEMENT AND BUSINESS INTELLIGENCE .
.............................................................................................................................. 50
vi
4.3. PRACTICAL DESIGN PRINCIPLES FOR A BUSINESS PERFORMANCE
MANAGEMENT AND BUSINESS INTELLIGENCE PROCESS ........................... 53
4.3.1. Review and Performance Meeting ..................................................................... 54
4.3.2. Wiring ................................................................................................................... 55
4.3.3. Key Performance Indicator Management .......................................................... 56
4.3.4. Task management ............................................................................................... 56
4.3.5. Idea Management ................................................................................................ 56
4.3.6. Impacts ................................................................................................................. 58
4.4. RECOMMENDATIONS ......................................................................................... 58
4.5. RECOMMENDED FURTHER STUDIES ............................................................... 59
4.6. CONCLUSION ...................................................................................................... 59
4.7. SUMMARY ............................................................................................................ 60
ANNEXURE A ....................................................................................................................... 64
ANNEXURE B ....................................................................................................................... 78
ANNEXURE C ....................................................................................................................... 79
vii
LIST OF FIGURES
Figure Page No
Figure 2.2.3.1: Business Performance Management Framework ..................................... 12
Figure 2.2.3.1: Injection of Business Improvement ........................................................... 15
Figure 2.2.3.2.1 Categories of business intelligence ........................................................ 18
Figure 2.2.3.2.1: A holistic view of Business Performance Management ......................... 23
Figure 2.2.3.2.1: Porter’s Value Chain for Mining and Manufacturing .............................. 29
Figure 2.2.3.2.2: Information Technology Supporting Organisations ................................ 30
Figure 3.3.3.1: Respondents per Natural Resource ......................................................... 36
Figure 3.8.1.1: Strategise versus Plan ............................................................................. 42
Figure 3.8.1.2: Plan versus Actions .................................................................................. 43
Figure 3.8.2.1: Business Performance Management objectives versus Business
Intelligence supporting goals .................................................................... 45
Figure 3.8.2.2: Plan versus Monitor & Analysis ................................................................ 46
Figure 3.8.3.1: Inputs of Business Intelligence ................................................................. 51
Figure 3.8.3.2: Relationships of Use by Organisational Level .......................................... 52
Figure 3.8.3.1: Review Performance Management with accountability ............................ 55
Figure 3.8.3.1: Idea pipeline ............................................................................................. 57
Figure 3.8.3.2: Value creation of ideas ............................................................................. 57
viii
LIST OF TABLES
Table Page No
Table 3.3.1: Detail of response size ................................................................................. 33
Table 3.3.2: Summary of response size ........................................................................... 35
Table 3.6.1: Cohen’s guideline to effect size .................................................................... 38
Table 3.7.1: Managers and Engineers re-coded .............................................................. 39
Table 3.7.2: Business Intelligence re-coded ..................................................................... 40
Table 3.8.1: Managers – BI and BPM correlations ........................................................... 41
Table 3.8.2: Engineers – BI and BPM correlations ........................................................... 44
Table 3.8.3: Information relationships .............................................................................. 47
LIST OF EQUATIONS
Equation Page No
Equation 3.1: Sample size determination for the proposition ........................................... 35
1
CHAPTER 1
NATURE AND SCOPE OF STUDY
1.1. INTRODUCTION
Businesses deliver products or services to customers in the market (Baltzan, Phillips & Haag,
2009:23). Staying in business means one needs to out-strategise competitors through
successfully executing the strategy of the business (Frolick & Ariyachandra, 2004:41; Kellen,
2003:2). Businesses need to act faster in the present, to maintain market shares, out run
competitors and adapt to customer needs.
Porter’s value chain model for manufacturing organisations indicates the primary and
supportive activities, which cost leaders focus on when competing in a cost curve market,
(Turban, Leidner, McLean & Wetherbe, 2006:44). When a cost strategy is predominant in the
business, business performance is key to the survival of the business, by staying the lowest
cost producer by creating a wide enough gap between your business’ costs and the highest
cost producer (price setter) in the market; resulting in the profit margin.
Organisations acknowledge business performance management as an enabler, to define
clear goals, actions and to monitor and control the business operations (Baltzan et al.
2009:21). Business performance management is also referred to as a series of processes
and applications to reach the business’s strategic objectives (Mojdeh, 2005:9).
Organisations are expecting improvement through the alignment of business strategies and
knowledge, the most valuable asset of the business. No thorough studies concluded the
relationship of resource alignment to knowledge management and often this is
misunderstood by management and consultants, resulting in poor operational performance
(Asoh, 2004:2).
Applied business processes on data are defined as information or converted data into
reasonable output formats constituting information. This information could be the calculation
of data points to an end result or applied business rules contributing to the information that is
output to the decision processes. Business has plenty of data, but realising it into valuable
2
information that is relevant and could give insight to improve the business performance is
mostly a challenge.
According to the Miles and Snow topology, business could be classified according to the
behaviour it adopts for business strategy (Asoh, 2004:34). The analysers’ profile in business
strategy is those organisations that take minimum risk, but in the same time maximise growth
in stable markets (Asoh, 2004:35).The processing operation could be seen as an analyser,
as they will take calculated risks, while creating market shares and position the business on
the best cost curve possible.
Key metrics or better known as key performance indicators is measurable indicators based
on value driver information which has an effect on the business (Bacalu, 2007:36). Identifying
key performance indicators, one needs to understand the business. What makes it “tick”?
From input, processing and output – what are the internal and external influences effecting
business performance?
1.2. BUSINESS PERFORMANCE MANAGEMENT VERSUS BUSINESS INTELLIGENCE
Business performance management enables business strategic intent to be obtainable
through a series of intertwined processes. Business intelligence enables the function of
addressing identifiable gaps in the business processes.
Some confusion exists to what business performance management and business intelligence
is, and is not. If business performance management provides a process of improving
business and business intelligence leverage the ability to disseminate the information of a
business to support business decisions, it would be true to state that you need business
performance management and business intelligence, but business intelligence supports the
overall process of business performance management. The orchestration of the two
processes advances the business’s ability to improve on the bottom-line. Business
performance management is also the fundamental cohesiveness of all management
processes (Mojdeh, 2005:1). As much as 84% of business indicated using business
intelligence in some form within the business (Miller, Brautigam & Gerlach, 2006:16).
3
In the rapid changing and competitive environment businesses operate in, knowledge
management as leverage is not enough and not the biggest contributor to increase
performance. Knowledge of the business mechanics and applying new avenues to overcome
current performance is more contributing to the bottom-line of the business (Asoh, 2004:1).
1.3. IMPORTANCE OF THE STUDY
One of the most diversified mining companies in the world, consisting of more than 100
operations, across 25 countries around the globe is diversified into 10 customer sector
groups, to illuminate the products offered into the market.
The manganese business is spread across Africa (South Africa and Gabon) and Australia
(Tasmania and Groote Eylandt islands in the South and North of Australia). Raw materials
are mined in the Kalahari Desert and sent to the processing plant in the Gauteng province for
converting the ore to alloy.
This processing operation is to produce high quality, low cost Ferromanganese and Silicon
manganese alloys. By combining manganese ore and other raw materials, it is smelt within
sub-merge arc furnaces to the final products. The business consists of eight sub-merge arc
furnaces, an energy production plant, raw material and final product management
department. The business also has four supporting departments that manage the technical,
health & safety, human resources and financial services.
The business has embarked onto a business improvement road, since 2008 and yet
business intelligence was not focused in the sense of intelligence by means of cubes and
dimensional information nor technology. If business intelligence is used effectively it could
improve performance, by means of leveraging on the insight it offers to make improvement
decisions (Howson, 2008:2).
The processing operation has earned the position of lowest cost producer in the manganese
industry globally. Being on the lowest cost curve also indicates that to stay there, the need to
improve ever more. The processing operation was faced with dead-ends to improve even
further and insight to how the exact measurable key performance indicators are actually
4
measured on the value added processes within the business (Phelps, 2004:4). Business
need to know what makes them do business, what do they know to survive and thrive in the
very quick-changing markets experienced currently (Kellen, 2003:1).
1.4. PROBLEM STATEMENT
A certain amount of confusion does exist, even in the business intelligence world, to what
actually is meant by the terminology. Business intelligence is neither a technology nor the
warehouse in which all the business data is stored. Business intelligence is the way in which
information, across functional areas within the business, is interpreted to give enriched
paradigm shift information that will enable decisions to be made for the better of the business
(Howson, 2008:2). The depths of business intelligence’s enrichment as a tool include
scorecards, dashboards, predictive analysis, and BI search and visualisation of the
information. By exploiting the gaps and relationships of information dimensions bring another
level of insight and knowledge to the business.
Many businesses struggle to disseminate strategic goals into workable set points in the
lowest level of the business. The roll-up of the lowest level measuring points need to total up
to the high level goals of the business. This sometimes does portrait its own challenges. Not
only is the dynamics important but also the collaborative channels between line management
and the workforce.
Businesses usually find themselves in situations where projects do not deliver as expected or
consultants overpromise the deliverables and customers do not get what they had asked for.
To “wire”, aligning business measurement points to organisational positions, a business and
the focus in the initial project start-up is what drives the business. What needs to be
measured and in which frequency? How does this articulate into the strategic goals of the
business? For the consultant to deliver on a real business performance management, the
business sense, measurement dimensions and accountability positions is critical. Fitting all of
this into a collaborative, monitoring and controllable environment is even more challenging.
5
1.5. CAUSAL FACTORS
The causal factors for this study are the following:
• The natural resource industries have become under high pressures around the globe
and cost effectiveness is highly sought after.
• An investigation indicated that the maturity level of the natural teams in the business
has been engrained and possible business improvement processes would be easily
introduced into it and positive return could be capitalised on.
• Operating costs were not on satisfying levels and being on the lowest cost levels will
result in more profits. This was established before the great recession the world
experienced in late 2008 and the first half of 2009.
• Staying competitive is crucial as a business can easily lose market share in the very
dynamic international environment.
• An initial investigation indicated that management strategy is not filtered through to the
lowest level within the business.
• The investigation also indicated that measurements against these strategic goals are
non-existent in some cases.
• No standardised measurements and progress review sessions existed, which
highlighted risk of business continuity to address the strategic goals.
• High level indicators were not possible and countless time was dedicated to align
actual facts to be rolled up to the highest level in the business.
1.6. OBJECTIVES OF THE STUDY
The objectives of the study are split into primary and secondary objectives.
1.1.1. Primary objective
The primary objective of the research is to establish a relationship between business
intelligence and business performance management.
1.1.2. Secondary objectives
Secondary to this, the following will also be investigated:
6
1.1.3. Theory evaluation:
1.1.3.1. Perform a literature study to research the different aspects of business
performance management and business intelligence.
1.1.3.2. Perform a literature study to indicate the relationship of business
intelligence and business performance management.
1.1.3.3. Provide an overview of a business performance management
implementation framework or models found in literature and business
environments where it was implemented.
1.1.3.4. Perform a high level assessment of the current status of business
performance management in the mining and manufacturing sector, with
emphasis on successful implemented processes.
1.1.4. Empirical research:
1.1.4.1. Investigate the opinions of respondents of the maturity levels of different
business performance management and business intelligence principles.
1.1.4.2. Investigate a readiness for implementing a business performance
management process with specific emphasis on information availability to
support a business performance management roll out process.
1.1.4.3. From both the theory and empirical research the final objective is to
recommend practical design principles which can be used to implement a
business performance management programme which will result into a
competitive advantage to the mining and manufacturing sector.
As can be seen from the above objectives, a broad spectrum of aspects will be researched in
business performance management. Based on the literature a survey will be designed to
determine the maturity of the business performance management process, the availability of
information and possible models to utilise for engraining business performance management.
7
1.7. SCOPE AND DEMARCATION OF STUDY
The study is to focus on the mining and manufacturing businesses of South Africa where
business performance management and business intelligence are present. The focus is to
understand the contribution of the correct value drivers that leads into decisions being made
to enhance the performance of the business and to indicate a model for adoption by other
mining and manufacturing businesses.
The study will be limited to primary sources within the mining and manufacturing sector, with
specific reference to the processing operation in Gauteng. Secondary sources of information
were limited to those generally available on the Internet, in the form of English documents
and generally available literature study.
1.8. LIMITATIONS
The surveys will be limited to the mining and manufacturing sector from executive to
engineer’s level in the business. The objectives set out will be covered within the survey only.
1.9. RESEARCH METHODOLOGY
Literature Study
Various publications were reviewed during the completion of the literature review. These
included text books related to the field of information management, business process
management and business intelligence.
Journals and websites were also accessed. The following topics were explored:
• Defining business intelligence and business performance management.
• Frameworks of business performance management used in the industry.
• Relationship to business strategy and value chains of manufacturing and mining operations.
Empirical study
Empirical research was done conducted by means of a structured questionnaire. The study
population included mining and manufacturing businesses, from executive to engineer’s
level. The data was collected in electronic format by means of web based survey services.
8
1.10. DIVISION OF CHAPTERS
Chapter 1 – Introduction and problem statement
Chapter 1 serves to supply the background to the study. Important concepts on business
performance management, business intelligence, the right information, information gaps and
business performance processes within the organisation are touched on, as well as a
discussion on the relationship of business performance management and business
intelligence of an organisation. Thereafter, a short discussion on the implementation road will
follow in business improvement. The reader will be introduced to the organisation as well as
the elements of a typical business improvement process constituting business performance
management.
The problem statement highlights the objectives and strategy of the organisation, and from
this the primary and secondary objectives of the study are derived. The remainder of the
chapter covers the scope of study and research methodology.
Chapter 2 – Literature study
Chapter 2 contains a literature review on business improvement. Some concepts that will be
explored include:
• Defining business performance management
• Defining business intelligence
• Relationship between business performance management and business intelligence
• Define business strategic management
• Explain Porter’s value chain within business performance management
• Creating a business performance management road map, processing operation approach
• Describe in detail the elements, tools and systems utilised as part of a processing operations
review and performance management process.
9
Chapter 3 – Research methodology and findings
Chapter 3 contains a comprehensive explanation of the research methodology that will be
followed to complete the empirical study. This will include the data gathering process, as well
as an analysis of the findings and presentation of results.
Chapter 4 – Conclusion and recommendations
In this final chapter conclusions will be derived from both the literature study as well as the
results of the empirical research. The conclusion will aim to present a response to the
problem statement and objectives as defined in Chapter 1. Practical recommendations for
business performance management to the broader group will be discussed.
1.11. CONCLUSION
It is a fundamental decision to improve a business to stay competitive in the market. Even so,
being more and more proactive, quicker to respond and to understand the complete
environment the business operates and to stay focussed with the business strategy remains
a challenge. Utilising processes, tools and knowledge to attain right of existence in the
market is imperative.
1.12. CHAPTER SUMMARY
The culmination of business performance management and business intelligence to assist
businesses to address the strategic gap within an organisation is of utmost importance.
Insight to the processes and defining and embedding it into the organisation is instrumental
to the success of investments made. Adapting to the way businesses need to run its
operations, focus on the correct measurements that impacts the bottom-line and to actively
control the process to reach the strategic goals will create the gap between competitors.
10
CHAPTER 2
LITERATURE STUDY
2.1. INTRODUCTION
No business can effectively be managed without the proper management and information
that reflects and creates the milieu it operates in. Business performance management
creates the framework in which a structured approach can be followed in setting the scene
for a predictive and controllable environment. Business intelligence creates the information
structures; information relationships and a reflection of the value chain of the business. By
combining the two methodologies it creates a total business solution that harmonises all
aspects of value creation in an objective manner.
Business information requirements are becoming more and more of a necessity to run a
business successfully (Lonnqvist & Pirttimaki, 2006:32). Some businesses have fast amount
of data but it’s not formalised into aggregated management information within the system and
usually gets reported in Microsoft Excel. Due to the high performance that is required in the
business environment, rich information is needed to obtain proper insight into the business
performance and to identify opportunities. Business performance management and business
intelligence facilitate a proper approach to strategic goal setting of a business and to
formulate it into lower levels within the business. Business performance management does
not only facilitate the processes in identification and creation, but also addresses the
planning, monitoring and corrective actions of the business management aspect,
(Ariyachandra & Frolick, 2008:114).
Several invested projects have failed by poor understanding of business intelligence and
business performance management processes. Project sponsors were either confused by
the meaning of the processes and thought the one would deliver the other’s outcome and
resulted in negative perceptions on both side of these investment options.
To understand the processes and getting an understandable representation of what it
purport, an explanation will be supplied on both methodologies and approaches of
implementation. The aspects of only one present in a business will also be distended.
11
2.2. BUSINESS PERFORMANCE MANAGEMENT
To reach the moon (goal), a road needs to be mapped, the flight needs to be monitored and
controlled and the landing on the specific spot is reaching the goal set up front.
In business context the following defined statement describes the reasoning what business
performance management is all about. It is defined as the enabling business process that
aligns business strategy, operational objectives and business activities, to manage
performance through better informed and proactive decision-making actions, resulting in
common organisational objectives (Ballard et al., 2005:3) and (Ariyachandra & Frolick,
2008:113).
To enhance the understanding of Business Performance Management, the framework will be
exploded, as can be seen in figure 2.2.1. The framework indicates the four areas and rotation
the process will follow, starting at the “Strategize” block.
• Strategize – defining the way to identify business strategy, the discovery of key value
drivers to accomplish strategy and create metrics to monitor the performance,
(Ariyachandra & Frolick, 2008:114). To be competitive, one needs to stay competitive.
This is accomplished to challenge the boundaries of performance. To strategise,
owners or executive management of the business, review the past performance of the
business and decide on future intent or direction for the business. This is also
supported by a SWOT analysis.
• Plan – defining a road map that is followed with specific projects, budgets and
activities to fulfil the strategy. Planning to build a bridge from the current status of the
business to the to-be state. If the goals were defined as part of the strategy process,
planning will include the formulation of required key indicators to measure the
progress towards the goals. Identification of gaps on measuring points is normally
done in this process.
12
Figure 2.2.3.1: Business Performance Management Framework
Source: Adapted from Frolick & Ariyachandra, 2006:43
• Monitor and analyse – actual performance against target values are reviewed and
dissected to understand the post actions taken resulting in the current position.
Monitoring is continuously measuring how we are moving towards the target. Think of
the GPS in your car, continuously tracking your move on the road, any deviations,
you’ll get the word. The same with businesses, progress need tracking and alerts to
indicate to decision makers the course taken is not delivering the required results or
we are on track.
• Take corrective actions – by understanding the status quo, rectification with
identifiable reactions to re-align the actions to achieve the desired performance levels.
Adjusting the driving direction will result in you reaching your destination. Available
information will give you insight to what happened. Part of corrective actions is also
tracking the status of the action. Have we done what we said?
These four steps are a continuous loop of processes to be followed, as long as a business
exists. The goals will determine the monitoring focus, while the corrective actions will be
determined by the current status of the business. The planning will follow the goals and map
out the detail of achievement.
Strategize
Plan
Monitor and
analyse
Take
corrective
action
13
The business goals are aligned horizontally and vertically throughout the business, to ensure
the business goals are measured at the source and all are focusing from the lowest level in
the business to the top. This means the contribution, how small that you might have in your
area of accountability, sum to the greater total of the over arching key indicator of the
business.
Actions are taken proactively and directed to the source of rectifications. Employees can view
the correct metrics and have insight into the performances. Business performance
management improves team effectiveness and productivity (Ballard et al., 2005:5).
Business processes and applications need to be in concert with one another, destroying silo
effects and misalignments of data, information and processes. This alignment brings forth the
correct measurable on goals and distribution to all relevant parties. Business needs to
understand what needs to be continuously monitored, how often it needs to be reviewed and
what steps to put in place in order to maintain the necessary performance levels.
The objective of business performance management is to help organisations with
improvement and optimization processes across all aspects of the business. In order to be
rapidly flexible the business needs to understand the playing field, the current situation of the
business and the players in each position to contribute, (Ballard et al., 2005:30).
2.2.1. Business Performance Management Roadmap for Manufacturing
How do we approach a beast like this? It sometimes sound very simple and when we
approach it, we found it to be somewhat difficult and scope creep on the project highlights
this quite quickly.
Types of approaches
Business starts off usually by one of these three approaches:
1. Enterprise wide – the approach will be top-down through strategic change. This
approach has the longest timeline before realisation of benefits will be seen. Much
more planning up front will take place in order to include all operations. This approach
14
will also have several iterations of deployment and upgrades to relevant operations, as
they need to align to the processes and system standards.
2. Cross-functional – smaller approach to the above and includes some functions like
finance and supply processes. It could be smaller like regional based.
3. Functional– based on functional area and will not necessarily mean the
implementation will drive new strategies, but rather control and improve performance
in a certain function like Human Resources.
4. Mixed – this is a combination of all functional areas in the business, but is demarcated
by a section within the business. i.e. a production unit of a production facility, where
costing, human resources, health & safety, maintenance and production are all
present, but at a very small scale of the business.
2.2.2. Business Improvement
Business performance management can include a business improvement process where
innovation is supported until it realises into measurable and cultural change benefit for the
organisation. This is done through an injection of improvement ideas after planning, as a
secondary “planning” process that redefines, in some cases, the key performance indicators
that are monitored in the next process.
Figure 2.2.1.1 indicates the blue block for position of this process into the business
performance management process. Why is this done? Think of your old computer that may
have a turbo button. This is the same. Although the business performance management puts
all effort in concert, this improvement process unlocks stored potential within the business to
be reaped. This is continuously asking the question: “Are we moving fast enough?”
Institutionalise idea generating cultures within the business to create a capacity of
improvements that can be assessed and prioritised for implementation.
15
Figure 2.2.3.1: Injection of Business Improvement
2.2.3. Why Business Performance Management
Business needs to become more responsive and flexible to minimise disruptions to
operations. Business also needs a single place to have a current view of their organisations.
The major drivers for implementing business performance management solutions are the US
Sarbanes Oxley Act and the new European Basel Capital Accord (Base II). Base II is a
critical piece of legislation that will impact how data and processes are integrated and how
risk-management, finance and operations function. It also encourages providing information
for better performance management, risk-management and capital decision-making (Ballard
et al., 2005:17).
2.2.3.1. Advantages
Business performance management gives the business the ability to reduce costs, increase
revenue and ultimately provides a competitive advantage. It also recognises proactive
monitoring, measuring and attaining performance targets. The ability to monitor business
processes also creates the opportunity to improve and manage these processes (Ballard et
al., 2005:24).
Strategize
Plan
Monitor and
analyse
Take
corrective
action
Business
Improvement
16
By unification of the business performance management processing and business
intelligence system it results in business process effectiveness. The result of the unification
also defines the simplification of the data structures in the business performance
management and business intelligence systems. Business performance can be compared,
monitored and aligned with the business strategies, goals and objectives when integration
with business intelligence is done.
2.2.3.2. Disadvantages
The disadvantageous impact of not having business performance management is bullet
below:
• A common threat is information - availability for business performance management
• Silo effect of decentralised information hubs within the business
• Lack of transparency on enterprise level, only departmental or functional area views
available
• Timely activities in aggregating information for higher levels within the business
(Ballard et al., 2005:25).
2.3. BUSINESS INTELLIGENCE
Business Intelligence is defined in more than one way by people, like, the right information to
the right people at the right time, utilising information effectively or to realise business
success by means of accessible information that can be put into action (Howson, 2008:1;
Schauer, 2004:58).
Business intelligence is also referred as the application or technology layer and techniques
used to gather, store, analyse and provide business information in a timely and easily
manner within the technology stack.
Business intelligence enables the business to make more effective decisions with the
information at hand. The technology gathers information systematically, which could be
analysed, disseminated (slice & dice) and compared from internal and external sources of the
17
business environment (Lonnqvist & Pirttimaki, 2006:32; Turban, 2006:423; Baltzan et al.,
2009:11; Howson, 2008:1).
The purpose of the business intelligence process is to identify and gather vast amounts of
data and information within and outside the business into a more condensed format that will
bring richer information trends (intelligence) to the audience.
With the capability to extract information in ways and means that put context and patterns to
information, business intelligence would add value only to the business when acting upon
opportunities identified within the business performance and information patterns (Howson,
2008:4).
2.4. DATA COMPILED INTO INFORMATION
The operational raw data are usually kept in data sources like database systems, electronic
documents and/or physical documents across the business. The information is gathered into
a multi-dimensional data warehouse in order to construct queries, reports or analysis on the
information, for decision-making (Turban, 2006:424). The information can be conducted in
real-time, but is limited to the latest upload of complete data sets to the warehouse. Patterns
are evaluated and meaning is added to the information. A response is formulated based on
the patterns of the information and the knowledge that was added (Baltzan et al., 2009:98).
Applying knowledge to the information viewed, knowledgeable actions are given to improve
processes (Baltzan et al., 2009:98).
Key statistical figures or key performance indicators indicate the perfectness of a process.
The data mining tools could be utilised to slice and dice between different areas in the
business or to identify the underlying issues. Understanding the process failure modes, will
lead to mitigating actions and be verifiable through key performance indicators.
Business intelligence (not the technology), needs to be competitive and is enabled through
fairly available technologies, distribution of intelligent information to all people within the
business and a performance based culture within the business (Baltzan et al., 2009:98, 99).
18
A typical business intelligence environment could be broken into reporting, analysing and
data mining. Figure 2.4.1 below depicts the split of the two major categories in the business
intelligence layer from a business process perspective.
Figure 2.2.3.2.1 Categories of business intelligence
Source: Adopted from Turban, 2006:425.
The “Information and Knowledge Discovery” stream defines the analytical processes of
searching for opportunities within the business environment. The “Decision Support and
Intelligence Systems” stream refers to the analytical result to be put through decision
processes to identify the most valuable option for the business to take. The “Metrics,
scorecard, dashboard, BPI, BPM”-process block is also utilised to perform the monitoring
process in business performance management. This metrics and scorecards are key
performance indicators defined to support the goals of the business. When fully developed,
the metrics and dashboards are deployed to all within the business that has a part of
accountability towards the over arching indicators of the business.
19
For some businesses the products and services delivered by business intelligence is not on
the same level of maturity as some will reflect on it through a single market-project and
others through a continuous process that delivers products and services to different users
(Lonnqvist & Pirttimaki, 2006:33).
Performance metrics can be developed for business intelligence to indicate investment
positions of the business intelligence project to executives and to indicate the correctness of
application to the user group, (Lonnqvist & Pirttimaki, 2006:33). Investment costs for a
business intelligence solution and the benefits that it will deliver are pivotal in the success
delivery of the project. Although these measurements are quite challenging to measure, the
proposed benefit of a Business Intelligence solution, is to measure the realised cost saving,
ideas generated from using the intelligent information (Lonnqvist & Pirttimaki, 2006:34).
Business intelligence performance measurements within an organisation could typically
phase:
1. Identification of information needs
2. Information acquisitions
3. Information analysis
4. Storage and information utilisation
The above phases could be defined as what information is needed to be measured and why
it needs to be measured. What information could be combined with other information to
indicate a key relationship of business activities that impacts business performance? The
third is how to analyse the information. Relationships between information groups are in
some cases not relevant at all and knowledge of the business is required to understand the
relationships. Lastly, the period of storage and how often the information is available, on-time
and to the right people making the decisions (Lonnqvist & Pirttimaki, 2006:37).
2.4.1. Investment into Business Intelligence
Some of the very difficult calculations to do are the return on investment (ROI) on information
technology projects. Although ROIs get compared to see viability of investment options to the
business, key project stakeholders do find it very difficult to stick the neck out on a number to
20
indicate for business intelligence, (Howson, 2006:40). The best practice in the business
intelligence space is to rather evaluate the business performance after implementation of
such functionality (Howson, 2008:68).
2.4.2. Technology
Source systems like operational or manufacturing, sales, supply, financial, customer
relationships (CRM) and external sources feed into the data warehouse through the Extract
Transform and Load (ETL) layer of business intelligence. The data warehouse’ data
structures are set up in multi-dimensional tables to give the richness of slicing and dicing of
information to relationships like time dimensions.
The integrity of the data, management of the data in the warehouse and development of
front-end tools to the users will dominate the success of the business intelligence project.
Business intelligence tools like query, reports, analysis and alerts could be set up to view the
information. Business involvement to assist in the selection process and tools that are
available in the technology will support the adoption rate by the users (Howson, 2008:166).
Different levels of users will use different depths of data and tools of the business intelligence
technology. Normally the tool will be able to secure data points to restrict the users access.
The famous Excel spread sheets are not demolished from the environment. Microsoft has
seen the flexibility the product offers by itself and incorporated it as an add-on to the
environment whereby cubes can be refreshed into the sheets and additional slice and dice
power could be added like Microsoft PowerPivot add-ons.
The depth of the tools being deployed into the business and segmentation of the users, will
define the platform of information the user will excel from. It is notable that the production
environment is not to be seen as being utilising analysis or statistical business intelligence
tools, as mentioned in a survey result (Howson, 2008:173). The picture has somewhat
changed due to these gaps being identified by the maturity of the manufacturing execution
system (MES) manufacturers. New products in this space have been developed like Dynamic
Process Management (DPM) and Enterprise Manufacturing Intelligence (EMI) of
21
Wonderware software suite, to give the production user the capability to analyse real-time
financial and production data, (Martin, 2004:1).
2.4.3. Advantages
• Single point of truth is one of the advantages all businesses familiarise themselves
with. Information is scattered all over the business and to try to pinpoint the exact
source or latest update, could be a daunting task. If data is managed within a business
intelligence environment, there is only one source of the data, where everybody gets
their information from. With a matured business intelligence system, it is possible to do
predictive analysis for the business, based on the external pressures. Such
businesses normally are very innovative, flexible and could easily adapt to market and
economic conditions (Miller, 2006:4).
• It also allows people to interact with the same data concluding several different
scenarios, performance measures and information patterns, whereby source data is
aligned and the business picture painted can be trusted (Howson, 2008:2).
• Better decision making to improve the business processes (Schauer, 2004:58).
2.4.4. Disadvantages
• Implementation of such systems are very costly and timely
• Business understanding of deliverables versus consultants promises
• Business’ clear understanding of its value chain and processes – reflects in rework in
the development layer of the project
2.4.5. Summary
Business intelligence is not about having a BI-software suite available in your business, but
it’s the combination of having sensible, structured and representative information available at
the right time to the right people.
Approaching a business intelligence project would not be easy and justification of the ROI
would be very difficult. Businesses would struggle to survive without it, as information is not
22
readily available to the decision makers. This will result in opportunity losses when it count
the most.
2.5. RELATIONSHIP BETWEEN BUSINESS PERFORMANCE MANAGEMENT AND
BUSINESS INTELLIGENCE
With the look at defining business performance management and business intelligence it is
clear that both processes need information. It is also evident that business intelligence
encompasses the workhorse of information, by means of extractions, manipulations to data,
based on the business rules and by reporting and analysing information by means of
dashboards, reports and analytical capabilities (Ballard et al., 2005:28).
Analytical capabilities from a business intelligence perspective, is to build and demonstrate
relationships between entities and to supply the user with rich functionality to explore the
possibilities within the information patterns.
Business performance management on the other hand was defined with some processes not
being built into systems due to the collaborative aspects of outcomes that is finalised
between groups of people. This type of functionality is not technology driven, but is based on
knowledge obtained and available at the individuals to design, agree and monitor objectives
for the business. It is also clear that it would be very difficult to maintain high level of success
with only one of the processes. It is also evident that the one fulfils the other in a relationship
where information is transferred between processes to overcome the obstacles in order to
reach the desired goals.
Business process effectiveness is enhanced by unifying the business performance
management and business intelligence environments. Information is distributed across the
enterprise through the use of information technology.
From the definitions it is apparent that there are two processes and it is aimed at achieving
business performance. Literature confirms this and states that there is a clear differentiation
between business intelligence and business performance management and researchers
generally agree that business performance management is not business intelligence and vice
versa (Ballard et al., 2005:13; Ariyachandra & Frolick, 2008:42, 113). What was also evident
23
is that the business performance management area is still new and not widely distributed as
a product in businesses. For managers it is crucially important to understand the processes,
but more importantly to invest into these processes from an organisational perspective. A
survey done in 2006 indicated a 53% of companies cited budgeting as the leading
component in a business performance management initiative (Stamford, 2006:2).
The integration of business intelligence, business process management, corporate
performance management, business service management and business activity monitoring;
as shown in figure 2.5.1; creates a single view of the business performance management
functions (Ballard et al., 2005:3) that supports it. These functions are interlinked by an
“information band”. It is apparent that business intelligence will contribute to the business with
information structures and dimensions, as previously discussed. By having these insight to
the processes and information, results in better actions to be taken against goals to reach the
business objectives.
Figure 2.2.3.2.1: A holistic view of Business Performance Management
Source: Adapted from Ballard, et al., 2005:3
Business
Performance
Management
Business
Intelligence
Business
Process
Management
Corporate
Performance
Management
Business
Service
Management
Business
Activity
Monitoring
Information Band
24
The strategic goals of a business in not always very well understood within the business, as a
survey result showed, less than 60% of senior managers had a clear understanding of the
goals in the business (Phelps, 2004:6).
The common theme across the functions for business performance management is
information, as can be seen in figure 2.5.1, with the orange band. It is the common ground for
all in the business, to know what is to be monitored and controlled in order to attain
organisational objectives.
2.5.1. Business Strategic Management
Strategy is the action plan that is derived to excel the business into a more favourable
position based on profit, stakeholder interest and strengthening of the business for the future
(Thompson, et al., 2009:6). By having a sustainable competitive advantage will ensure a
lasting customer preference to be formed for your product and your business (Thompson et
al., 2009:7).
The strategy a business’ executives put forward is the best future indication that will influence
investments and market share. This is influenced by a number of approaches:
• “Actions to gain sales and market share via lower prices, more performance features,
more appealing designs, better quality or customer services, wider product selection,
or other such actions.
• Actions to respond to changing market conditions or external factors.
• Actions to enter new geographic or product markets or exit existing ones.
• Actions to capture emerging market opportunities and defend against external threats
to the company’s business prospects.
• Actions to strengthen market standing and competitiveness by acquiring or merging
with other companies.
• Actions to strengthen competitiveness via strategic alliances and collaborative
partnerships.
• Actions and approaches used in managing R&D, production, sales and marketing,
finance and other key activities.
• Actions to strengthen competitive capabilities and correct competitive weakness.
25
• Actions to diversify the company’s revenue and earnings by entering new measures.
(Thompson et al., 2010:10).
These approaches all reflect the need for information to ensure timely decisions.
2.5.2. Summary
The equation reads, good strategy and good strategy execution will result in good
management (Thompson et al., 2010:17). The good strategy plan that is derived based on
intent of moving the business from the current status quo to the future position and executing
against the strategic plan will result in a good performance of the business. In order to obtain
this good performance, the Business Performance Management and Business Intelligence
processes support the capability to be available for management to obtain good results. As
described earlier, Business Performance Management is the culmination of strategy,
performance and actions. Business Intelligence on the other hand will supply the information
available to make strategic decisions.
2.6. CONCLUSION
It is apparent that business performance management is an information “requester” to move
from the one process to the next. Business intelligence is an information workhorse,
extracting, transforming and loading relevant information and supplying it to the appropriate
decision makers.
It is not transparent to what the relationships are between the two spheres.
Business performance management are not based on technology nor information, but the
success of the process is dependent of having information to action against. Business
intelligence on the other hand fulfils the need of the business performance management
processes.
Highlighting some key aspects to both processes:
• Business performance is influenced by the means to have the right information
available to the right people in the organisation at the right time.
26
• Business ability to grow in the respective industry is related to the capability that is
possible to lower the business strategic goals to the lower levels within the business.
• Business Performance Management is a different process that entails strategizing,
planning, monitor and controlling and corrective actions to be taken.
• Business Intelligence is the culmination of data to supply rich information through
queries, reports and analytical tools within the technology.
• Business Performance Management delivers improvement to the business by means
of leveraging on Business Intelligence for informational substance to make decisions.
2.7. CHAPTER SUMMARY
Firstly we discussed what business performance management is and what it is constructed
of. The sphere starts with the strategising, planning, monitor & analysis and finally corrective
actions processes.
Secondly, the approaches for embedment of a business performance management were
discussed. It would be dependable on the business’ approach to which approach is
applicable for their project.
Thirdly, business improvement as a “turbo” button to the business performance management
process was discussed and can be seen as a second planning process delivering inputs into
the business performance management process.
The reason why business performance management is a needed process in today’s
businesses were discussed and the pro’s and con’s were weight up. It is more advantageous
to have it, than not having it.
Business intelligence were discussed in brought context through what it is, how data gets
transformed into sensible information and justifying investment of such a project. The
technology of business intelligence in lower levels of the business like operations is a newly
added dimension in the market. The technology is developed for real-time environments that
27
are quite different to transactional based systems like enterprise resource planning (ERP)
systems.
Advantages and disadvantages are weight up and two major factors on both sides are to be
taken of note: advantage – information availability, disadvantage – return on investment and
delivery of a successful project.
Lastly the relationship between business performance management and business
intelligence are discussed and indication is that there should be. The two spheres are
dependent on each other to produce workable output for the business.
Chapter 3 will cover the research methodology and findings of this literature study and
conclusion of some relationships will be drawn.
28
CHAPTER 3
RESEARCH METHODOLOGY AND FINDINGS
3.1. INTRODUCTION
In chapter 2, Business Performance Management and Business Intelligence were defined
and assumptions were made if the two spherical processes could have some relationship(s)
with one another and in what context. In this chapter the focus is on obtaining evidence for
the research objectives laid out in §1.6. In addition, the survey findings are presented.
The aim of the survey is to understand the relationship of business intelligence on business
performance management within the mining and manufacturing sector. Both these supporting
frameworks have huge benefits to the business, if deployed and understood correctly.
3.2. DISCUSSION OF MINING AND MANUFACTURING ENVIRONMENT
The mining sector of South Africa is the fifth or sixth biggest contributor to the GDP of South
Africa. Also the largest producer of platinum and one of the leading producers of gold,
diamonds, base metals, coal and the best grade in manganese ores in the world. The biggest
natural reserves held in South Africa are gold, platinum-group metals, chrome ore and
manganese ore.
The metals industry, subset of the manufacturing sector, makes up a third of South Africa’s
manufacturing. As this is seen as a beneficiated process or processing of primary resources
to a final or semi-finished product for the market. The manufacturing environment is running
under utilisation due to raw material input constraints, caused by rail capacities. South Africa
is a net exporter of steel products.
The value chain of the mining and manufacturing industry could be summarised as the
acquiring, mining and supplying of natural resources to the market in raw or processed into
semi - or final product format. Manufacturing downstream in the same commodity is usually
considered due to supply chain constraints and/or better value propositions for units of
29
products sold or placed through the value chain. Figure 3.2.1 indicates a common value
chain for mining and manufacturing.
Figure 2.2.3.2.1: Porter’s Value Chain for Mining and Manufacturing
Source: Adapted from Turban, 2006:515
It could be considered a given to understand the internal operation of a business and in
today’s milieu external factors or pressures are having more impact on high performance.
The macro-economic policy is the major driving force behind economic activity and also
environmental impacts. The policy aims at economic growth, increasing employment, positive
trade balances, combating inflation and equity.
As earlier stated, mining and manufacturing can only be profitable if the cost to produce is
kept to the minimum. From Figure3.2.1 it is also visible that the value chain can become
complex and management spans across a wide range of functions to support it.
30
When external pressures; indicated by Figure 3.2.2; like societal and external market are
forced onto the business, it would require synchronised efforts in the right direction, to keep
the boat afloat, (Turban, 2006:13).
Figure 2.2.3.2.2: Information Technology Supporting Organisations
Source: Adapted from Turban, 2006:12
These external pressures in respect to South African context are rail constraints that impacts
mine production output to terminals for exports; unskilled worker class, stable and adequate
energy supplies to feed production facilities, environmental impacts currently experienced
around the globe and equity imbalances within the mining industry.
The aim of the questionnaire is to establish an understanding of the relationships between
business performance management and business intelligence’s level of application within the
natural resource sector.
31
3.3. THE PROCEDURE AND SCOPE OF THE QUANTITATIVE RESEARCH
The empirical study focuses on the mining and manufacturing, of natural resources industry.
It spanned across a range of natural resource sectors and across the management levels
within the businesses. The usage of business intelligence and business performance
management were analysed, based on sub-processes of business performance
management, as well as the relationship in which business intelligence assisted the
businesses through information.
The reason for the study was due to the most minuscule study in the manufacturing and
mining for these two aspects. Other studies are starting to develop in this area and software
vendors are aligning their products to deliver on some aspects. Some studies now starting to
surface, indicates the need for real-time business intelligence within a production
environment. These industries are real-time based, which enlarge, are captive to quick
response against negative impacts in the business. This indicates a far more robust and
enhanced business intelligence system to support such quick response times.
3.3.1. Survey instrument
Conducting data collection through surveying is one of four data sources that are used in
gathering data from the sample in a population. The other three: distribution of data by
organisations, designed experiments and observational studies are the other three data
sources, (Levine, Stephan, Krehbiel & Berenson, 2008:6,7).
Research can be grouped into two categories: quantitative and qualitative. Quantitative, also
known as positivist can be summarised as the natural-scientific method in human behavioural
research. It is limited to what can be observed and measured objectively. Qualitative, also
known as anti-positivist, can be summarised as the inverse of human behavioural research,
also seen as the experience of the human behaviour for specific humans researched,
(Welman, Kruger & Mitchell, 2007:6).
A quantitative approach was chosen by the author to objectively meet the research
objectives. The sampling approach was non-randomly (voluntarily).
32
3.3.2. Overview of questionnaire
A questionnaire was chosen for data collection and other instruments were also considered.
The advantage and disadvantage was considered and found more favourable due to the
timing and cost to gather the data. The sources used for the compilation of the questionnaire
included the following sources: Vlerick Leuven Gent Management School (2007:17-26); plus
author experience within the business performance management and business intelligence
area. The primary objective was not visible within previous studies and interpretation of
literature and experience was used to formulise some of the questions. The questionnaire’s
questions compose of 42 questions with the following answering methods:
• Questions (31,33 to 47) were based on a 4-point Likert scale, 1 (Very relevant) to 4
(Irrelevant)
• Questions (17, 18, and 20 to 27) were based on a 4-point Likert scale, 1 (Completely)
to 4 (Not at all).
• Questions (10 to 15) - The fourth option don’t allow for analysis beyond the frequency.
Therefore the second variable which only includes responses of participants, who had
an opinion, was included. The new scale was re-coded with the answers 1 (Exceeds
expectations) to 3 (Below expectations) and is referred to after this as 10R to 15R,
annexure B.
• Questions 16 and 19 are multiple selection criteria questions and would be used in
frequencies.
The layout of the questionnaire can be grouped as follow:
1. Questions 1 – 6 demographics
2. Questions 7 – 9 background of business performance management within the
business
3. Questions 10 – 15 satisfaction of business performance management within the
business
4. Questions 16 – 19 values and challenges of business performance management
within the business
5. Questions 20 – 27 usage of business intelligence within the business
6. Questions 28 – 30, 32 usage of reports for processes within the business
33
7. Questions 31, 33, 34, 36 – 43 business intelligence support of business
performance management processes
8. Questions 35, 47 – business performance management support of business
performance management processes
9. Questions 48 – 51 information relationships within business performance
management processes
The questionnaire was developed within an electronic web based system hosted on an
external environment plus hard copies were also printed for companies close to the author’s
base of work. The questionnaire is included in annexure A. The distribution was done through
an electronic link in a web group and physical delivery of hard copies to companies. A time
frame of three weeks was given for respondents.
3.3.3. Sample group and size
The main target group of the study was from executive level down to engineering. All
functions within the business were included finance, production, maintenance, human
resources, technical, health and safety, strategic and general management. The reason for
the wide spread, is due to the value chain depicted in figure 3.2.1, indicating a complex
interlinked processes that needs orchestration by all. The sample composition was a broad
spectrum in regards to gender, experience, levels and functions within the mining and
manufacturing of natural resources.
The number of returns from a population of 467 was 187. Table 3.2.3 indicates the sample
response. Table 3.2.4 summarises the response according to management level within he
business. The major groups contributing to the questionnaire were engineering and middle
management levels, contributing 81% of the response.
Table 3.3.1: Detail of response size
Area of responsibility Number
(N) Position Level
Engineering
Middle Management 6
Senior Management 4
Engineering 15
Financial
34
Middle Management 10
Senior Management 2
Executive
Management 1
Engineering 21
General Management
Middle Management 2
Senior Management 4
Executive
Management 1
Engineering 6
Health & Safety
Middle Management 2
Senior Management 1
Engineering 4
Human Resources
Middle Management 8
Senior Management 5
Engineering 7
Other
Missing 1
Middle Management 7
Engineering 2
Production
Middle Management 12
Senior Management 6
Engineering 16
Technical
Middle Management 6
Senior Management 7
Engineering 16
Missing
Missing 1
Middle Management 2
Strategic
Middle Management 7
Senior Management 2
Engineering 3
35
Table 3.3.2: Summary of response size
Area of responsibility Number
(N)
Percentage
of response
Position Level
Summary
Middle Management 62 33%
Senior Management 31 17%
Executive Management 2 1%
Engineering 90 48%
(blank) 2 1%
Grand Total 187 100%
Sample sizes are determinable on the collection of the data to ensure that the confidence
levels are marginal enough to make decisions on the statistics. To determine the sample
size three aspects need to be considered; the confidence level desired, acceptable sampling
error and the population proportion.
The following equation is used to determine the sample size for the proportion in equation 3.1
below:
Equation 3.1: Sample size determination for the proposition
? =
?
?
?(1 ? ?)
?
?
Where:
n = sample size
Z = desired confidence level (1.96 for 95% confidence level)
? = population proportion (no prior estimate of the population proportion select 0.5 for
maximum result)
e = sampling error, in this case 10%
Source: Levine, et al. (2008:303)
From equation 3.1 above, it was calculated with the set values to have a sample of 97
questionnaires to be returned. The total received was 187, for which is above the minimum
requirement and we can conclude that it is representative of the opinion of the population.
36
3.4. DESCRIPTION OF DEMOGRAPHICAL INFORMATION
Percentage of respondents per natural resource sector is summarised below in figure 3.4.1.
The manganese, coal and aluminium sectors were more responsive 25%, 19% and 19%
respectively. Other demographics of the respondents are summarised below in figure 3.2.
The position level responded were mostly the engineering level, with a total of 49%, followed
by middle management of 33% and senior management on 17%. Executive management
contributed 1% of all respondents.
Figure 3.3.3.1: Respondents per Natural Resource
On the gender, the female constituted a 40% of the total. The functional area for
representation was widely spread across all functions, with the highest respondents of
financial (18%), technical (16%), production (18%) and engineering (13%).
The working experiences of the respondents are also distributed across the categories of
years, with a 30% response rate to the 10 – 15 years working experience.
37
Figure 3.2: Respondents’ other demographics
3.5. OVERVIEW OF RESPONSES
There was a relative good response from respondents on questions indicated for
correlations. A range of 5 to 14 missing answers were counted on these questions. Question
10R to 15R there was a range of 9 to 35 taken out of the data set, as the questions were re-
coded to eliminate irrelevant aspects from the analysis. See annexure C for detail of
response.
38
3.6. FREQUENCY ANALYSIS AND DESCRIPTIVE STATISTICS
We use analytics to get an idea of why we see a variation in the responses. To identify the
sources of variation on the data set [questions 10R to 15R, 17, 18, 31, and 33 to 51]; the
author looked at statistical significance and practical significance.
The null hypothesis test is done through methods of statistical significance indicating the
coincidence of what is being seen in the data set. The question is if the population will also
show this difference or correlation which is indicated by the sample. We use the p-value with
a value of ? 0.05 to state a 95% probability that the correlation or difference will also be
reflected in the population.
The practical significance indicates the effect size of this correlation or difference to have an
impact in reality, (Steyn, 2002: 10-15).
The tool - Cohen's “d” and the effect size “r” was used to indicate the practical significance.
Consideration will be given for r-value to be >= to 0.3 for practically visible and a 0.5 will be
considered as a practical significance. See table 3.5.1 for r-value.
Table 3.6.1: Cohen’s guideline to effect size
Test Value Small Medium Large
Compare groups d 0.2 0.5 0.8
Correlation associations
(effect size)
r 0.1 0.3 0.5
Source: adapted from Cohen, 1988:20-27
Parametric and non-parametric tests were conducted on the responses. Parametric tests are
more powerful but it requires the data to be normally distributed and groups to have variation.
The following tests for normality were conducted: Kolmogorov-Smirnoff (non-parametric),
Shapiro-Wilk (parametric) and the (quantile-quantile) QQ-plots were used for assessing this
normality.
To conclude, we tested for deviations from assumptions as indicated above. However, no
severe deviations were found. Also to be noted, to ensure accurate representation both non-
39
parametric (Spearman’s rho test) and parametric tests were performed against the sample
data.
The SPSS software package was used for the frequency analysis and descriptive statistics.
3.7. COMPARISON BETWEEN THE NEW MANAGEMENT LEVELS
The management levels were re-coded into two levels, namely NewManagement and
NewEngineers. NewManagement re-code consists of executive management, senior
management and middle management. NewEngineers consist of the engineering level.
The responses are divided in a half position by these new groups. The NewManagement and
NewEngineers groups respectively had 52.4% and 48.6%, see table 3.8.1, of the frequency
of 95 and 90 responses. There were 2 responses missing from the total response count.
Table 3.7.1: Managers and Engineers re-coded
Frequency Percent
Valid
Percent
Cumulative
Percent Frequency Percent
Valid
Percent
Cumulative
Percent
1 2 1.1 1.1 1.1 95 50.8 51.4 51.4
2 31 16.6 16.8 17.8 90 48.1 48.6 100.0
3 62 33.2 33.5 51.4
4 90 48.1 48.6 100.0
Total 185 98.9 100.0 185 98.9 100.0
Missing System 2 1.1 2 1.1
187 100.0 187 100.0
Q2 Q2New
Valid
Total
To find a more suitable correlation between business performance management and
business intelligence, the positive reply on businesses making use of a business intelligence
system within the business, were narrowed down, in order to keep only intelligence owners
where they have business intelligence totally used in the business or where it is used in 2 or
more departments within the business. Table 3.8.2 indicates the distribution of the 96
respondents divided in only 12.5% having business intelligence used totally within the
business. The remainder of 87.5% are businesses using business intelligence in 2 or more
areas within the business.
40
Table 3.7.2: Business Intelligence re-coded
Frequency Percent
Valid
Percent
Cumulative
Percent Frequency Percent
Valid
Percent
Cumulative
Percent
1 12 6.4 6.6 6.6 12 6.4 12.5 12.5
2 84 44.9 46.4 53.0 84 44.9 87.5 100.0
3 80 42.8 44.2 97.2
4 5 2.7 2.8 100.0
Total 181 96.8 100.0 96 51.3 100.0
Missing System 6 3.2 91 48.7
187 100.0 187 100.0
Q20 Q20_1and2
Valid
Total
These applied re-codes and filtered criteria are applied to the responses that will be
discussed within the result discussion.
3.8. DISCUSSION OF RESULTS
3.8.1. Relationship of NewManagers responses
The following statistical- and practical significances, see table 3.8.1, were detected on the
responses, with the applied filtered criteria described in §3.7. Table 3.8.1 is a summary of the
defined (post hoc t-tests) and the corresponding effect sizes where results met the criteria of
table 3.6.1. All effect sizes (correlations) are positive of nature and vary from medium to
large. The focus will be placed on the large effect sizes.
Respondents, who indicated to have in use business intelligence systems, were
acknowledging business performance management and business intelligence has a
correlating association in assisting them in reaching business objectives, (r = 0.658). In the
literature, figure 2.2.2 indicates the business performance management, with business
intelligence as a sub-process supporting it. The correlation coefficient is positive, indicating
some relationship between business performance management and business intelligence in
support of business objectives.
41
Table 3.8.1: Managers – BI and BPM correlations
Questions relationship
Correlation
Coefficient (r)
Significance
(p)
N
Business performance management assist in business goals
- >
Business intelligence assist in reaching the business goals
0.658 0.0000001 54
Business intelligence assist in corrective actions taken
->
Business intelligence assist in strategizing processes
0.363 0.0075427 53
Business intelligence assist in identifying strategies
->
Business intelligence assist in identifying actions
0.555 0.0000158 53
Business intelligence assist in creating plans
->
Business intelligence assist in reaching the business goals
0.526 0.0000527 53
Business intelligence assist in creating plans
->
Business performance management assist in business goals
0.422 0.0016512 53
Business performance management assist in managing
objectives
->
Business intelligence assist in reaching the business goals
0.417 0.0020989 52
Business performance management assist in managing
objectives
->
Business performance management assist in business goals
0.355 0.0097780 52
Business performance management assist in managing plans
->
Business intelligence assist in identifying actions
0.53 0.0000448 53
Business performance management assist in managing plans
->
Business intelligence assist in identifying strategies
0.429 0.0013570 53
Business performance management assist in managing plans
->
Business performance management assist in managing
objectives
0.359 0.0090116 52
The identification of strategies and corrective actions has however have a high correlation
association. This could be seen somewhat controversial to the above paragraph on a lower
correlation association between using business intelligence in these processes. With an r-
value of 0.555, it seems that the business intelligence is used for some data mining activities,
to explore identification of corrective actions and strategies.
Business goals defined in this perspective are as follow: it is time-based measurements that
are a resultant of the strategy that will be implemented, (PlanWare, 2011). From the
correlation coefficient on the questions posed to the respondents, if business intelligence is
assisting in planning and the business goals; as well as business performance management
the 0.526 indicates a high level of correlation. From the
formalising the strategy of a business
more focus where you want to be. This is creating a cavity to the norm that exists on
performance. The setting of goals creates
competitive level. Goals are measurable and in order to define it with the current level
performance, a tool is needed to supply the data.
highlights the business performance management process (strategise, plan, monit
analyse and corrective actions) with two blocks indicating a
questionnaire results from the respondents. In the top right, goals are an output of the
function strategy and business intelligence is an input to the process
function (right bottom), indicates the achievable measurements as an output, supportive of
business intelligence to the process.
Figure 3.8.1.1: Strategise versus Plan
From figure 3.8.2 there is a high correlation association between business performance
management supporting the planning function and business intelligence supporting the
actions to be identified, (r = 0.53).
Corrective
Actions
Monitor &
Analysis
on the questions posed to the respondents, if business intelligence is
assisting in planning and the business goals; as well as business performance management
the 0.526 indicates a high level of correlation. From the executive blue-sky ideas to
ing the strategy of a business, less emphasis is on internal business status, with
where you want to be. This is creating a cavity to the norm that exists on
setting of goals creates the bridge to leap from the norm to the new
Goals are measurable and in order to define it with the current level
performance, a tool is needed to supply the data. To indicate this crisper, figure 3.8.1
the business performance management process (strategise, plan, monit
analyse and corrective actions) with two blocks indicating an in/out put perspective to the
questionnaire results from the respondents. In the top right, goals are an output of the
function strategy and business intelligence is an input to the process. Moving to the plan
function (right bottom), indicates the achievable measurements as an output, supportive of
to the process.
Strategise versus Plan
3.8.2 there is a high correlation association between business performance
management supporting the planning function and business intelligence supporting the
actions to be identified, (r = 0.53).
• Achievable
Measurements (output)
• Business Intelligence
(input)
• r= 0.422
• Goals (output)
• Business Intelligence
(input)
• r=0.526
Corrective
Actions
Strategise
Plan
Monitor &
Analysis
42
on the questions posed to the respondents, if business intelligence is
assisting in planning and the business goals; as well as business performance management,
sky ideas to
, less emphasis is on internal business status, with
where you want to be. This is creating a cavity to the norm that exists on
the bridge to leap from the norm to the new
Goals are measurable and in order to define it with the current level
To indicate this crisper, figure 3.8.1
the business performance management process (strategise, plan, monitor &
perspective to the
questionnaire results from the respondents. In the top right, goals are an output of the
. Moving to the plan
function (right bottom), indicates the achievable measurements as an output, supportive of
3.8.2 there is a high correlation association between business performance
management supporting the planning function and business intelligence supporting the
Measurements (output)
Business Intelligence
Due to the re-coding of the management levels, it seems th
described on basis of putting plans into actions. As business performance management
drives the process from strategising to corrective actions, it seems the planning to corrective
actions is dictated by this process. On the othe
formalise a view of what the current status quo is and what could be the problem area where
action is required. Once again this is not a daily action of tasks but more focused on strategic
actions.
Figure 3.8.1.2: Plan versus Actions
3.8.2. Relationship of NewEngineers responses
The following statistical- and practical significances, see table 3.8.2, were detected on the
responses, with the applied filtered criteria described in §3.7. Table 3.8.2 is a summary of the
defined (post hoc t-tests) and the corresponding effect sizes whe
table 3.6.1. One finding of effect size (correlations)
vary from medium to mid-large positions
• Actions (output)
• Business Intelligence
(input)
• r=0.53
Corrective
Actions
Monitor &
Analysis
coding of the management levels, it seems that the relationship can be
described on basis of putting plans into actions. As business performance management
drives the process from strategising to corrective actions, it seems the planning to corrective
actions is dictated by this process. On the other hand business intelligence is used to
formalise a view of what the current status quo is and what could be the problem area where
action is required. Once again this is not a daily action of tasks but more focused on strategic
: Plan versus Actions
Relationship of NewEngineers responses
and practical significances, see table 3.8.2, were detected on the
responses, with the applied filtered criteria described in §3.7. Table 3.8.2 is a summary of the
tests) and the corresponding effect sizes where results met the criteria of
effect size (correlations) is negative of nature and
large positions.
• Plans(output)
• Business performance
management (input)
• r= 0.53
Corrective
Actions
Strategise
Plan
Monitor &
Analysis
43
at the relationship can be
described on basis of putting plans into actions. As business performance management
drives the process from strategising to corrective actions, it seems the planning to corrective
r hand business intelligence is used to
formalise a view of what the current status quo is and what could be the problem area where
action is required. Once again this is not a daily action of tasks but more focused on strategic
and practical significances, see table 3.8.2, were detected on the
responses, with the applied filtered criteria described in §3.7. Table 3.8.2 is a summary of the
re results met the criteria of
of nature and areas of note
Business performance
management (input)
44
Table 3.8.2: Engineers – BI and BPM correlations
Questions relationship
Correlation
Coefficient (r)
Significance
(p)
N
Business performance management assist in business goals
- >
Business intelligence assist in reaching the business goals 0.395 0.0128487 39
Business intelligence assist in corrective actions taken
->
Business intelligence assist in reaching the business goals 0.317 0.0492333 39
Business intelligence assist in identifying strategies
->
Business intelligence assist in identifying actions 0.418 0.0080459 39
Business performance management assist in managing
objectives
->
Business intelligence assist in reaching the business goals -0.371 0.0200606 39
Business performance management assist in managing
objectives
->
Business intelligence assist in identifying actions 0.328 0.0413856 39
Business performance management assist in managing plans
->
Business intelligence assist in monitor & analysis processes 0.379 0.0173969 39
Business performance management assist in managing plans
->
Business intelligence assist in creating plans 0.32 0.0473781 39
Business performance management assist in analyse &
monitoring
->
Business intelligence assist in reaching the business goals -0.30345731 0.0603828 39
Business performance management assist in analyse &
monitoring
->
Business intelligence assist in planning processes -0.333 0.0380095 39
Respondents from the NewEngineering level also indicate a medium correlation association
between business performance management and business intelligence as the NewManagers
level. This point will not be laboured more.
Respondents from the NewEngineering level also indicate a correlation association of
medium to large between business intelligence identifying strategies and actions as the
NewManagers level. This point will not be laboured more.
A negative correlation, figure 3.8.2.1, between business performance management assisting
in managing objectives towards business intelligence assisting business goals, (r = -0.371).
In the NewManagement group, the management level indicated a positive correlation
45
association. This phenomenon raises other questions. Is the engineering level exposed to
generating business goals? Are they the receiving end of goals to be met? Is it an indication
of workforce acting upon goals set and achievement of actions is measured through key
performance indicators?
Figure 3.8.2.1: Business Performance Management objectives versus Business
Intelligence supporting goals
There was a strategic significance between business performance management supporting
the planning function and business intelligence assisting the monitor & analysis processes, (p
= 0.0173969).
We also found a practical significance correlation between business performance
management supporting the planning function and business intelligence assisting the monitor
& analysis processes, (r = 0.379).
From figure 3.8.2.2 this medium correlation association between business performance
management supporting the planning function and business intelligence assisting the monitor
& analysis processes is indicated. Respondents who are grouped in the NewEngineers group
seems to have the same agreement of business performance management to assist the plan
function, however the business intelligence was more prominent to be supporting in the
monitor & analysis function. It might be assumed that these two functions are more pertinent
in their daily activities in the business.
Figure 3.8.2.2: Plan versus Monitor & Analysis
3.8.3. Information Relationships
From ad hoc t-tests we found that businesses who were satisfied with their business
performance management system, that is used to steer the business, showed a positive
practical significance (r = 0.325
defining it within the monitor & analysis process, table 3.8.3 indicates significance.
Here is could be argued that the business has some level of business intelligence process
within the business and using business performan
performance metrics/indicators. They are also in some sense agile to business situation in
the milieu it performs.
• Business
Intelligence
(input)
• r=0.379
Corrective
Actions
Monitor &
Analysis
monitor & analysis function. It might be assumed that these two functions are more pertinent
in their daily activities in the business.
Monitor & Analysis
Information Relationships
tests we found that businesses who were satisfied with their business
performance management system, that is used to steer the business, showed a positive
practical significance (r = 0.325 - medium) towards information relationships needed when
defining it within the monitor & analysis process, table 3.8.3 indicates significance.
Here is could be argued that the business has some level of business intelligence process
within the business and using business performance management to support certain key
performance metrics/indicators. They are also in some sense agile to business situation in
• Plans(output)
• Business performance
management (input)
• r= 0.379
Corrective
Actions
Strategise
Plan
Monitor &
Analysis
46
monitor & analysis function. It might be assumed that these two functions are more pertinent
tests we found that businesses who were satisfied with their business
performance management system, that is used to steer the business, showed a positive
ion relationships needed when
defining it within the monitor & analysis process, table 3.8.3 indicates significance.
Here is could be argued that the business has some level of business intelligence process
ce management to support certain key
performance metrics/indicators. They are also in some sense agile to business situation in
Business performance
management (input)
47
Table 3.8.3: Information relationships
Questions relationship
Correlation
Coefficient
(r)
Significance
(p)
N Missing
Defining monitor and analysis to support the plans,
information relationships needed
->
Satisfaction of the business with business
performance management's agility in steering the
business
0.325 0.0000536 149 38
3.9. CONCLUSION
From the above analysis we tried to establish some relationship between business
intelligence and business performance management. From the analysis the following aspects
seems to appear:
• Senior management level of usage of business intelligence do differ from the lower
levels within a business
• Business intelligence is used in a more identification role, to explore possibilities and
to determine the unknown for senior management levels
• Business intelligence is used by lower levels in the business to monitor and analyse
key performance indicators, the goals that were set, and try to define reasoning to it
• It seems there is a relationship for the use of the business performance management
and business intelligence between the strategising and planning function of business
performance management for senior managers
• It seems there is a relationship for the use of the business performance management
and business intelligence between the planning and monitor & analysis function of
business performance management of lower levels in the business
• There was an indication that senior management uses business intelligence for some
sense of guidance to corrective actions, most probably for long term direction
• There is a supporting relationship between business performance management and
business intelligence, which is some cases are very closely interlinked and might pose
a hinder if one of two is not present.
48
We can thus conclude that businesses that do have both frameworks established within the
business, shows supporting relationships between business intelligence and business
performance management and that the level of management has different needs in using it.
3.10. SUMMARY
Chapter 3 was dedicated to the statistical analysis of the questionnaire that was based on the
literature study in chapter 2.
Firstly we looked at the natural resources sector within South Africa. The contribution it has to
our countries GDP and the diversity of natural resources available in South Africa. We
highlighted the external pressures on the mining and manufacturing environment and
appreciate the complexity of the value chain these businesses have. We realised that the
external pressures are not temporarily and that more are to come. The image in managing
these businesses we reflect impacts the investment done in the country.
The second area, we discussed the quantitative research and survey instruments that can be
used in gathering response from the population. The questionnaire was used for this
empirical study and the questionnaire’s layout was grouped with a short description. The
sample group and size were discussed. The response of the sample was detailed in function
perspective and level of management.
The third area, we looked at the demographics of the responses. 49% of the responses were
from engineering level, 33% for middle management, 17% for senior management and 1%
for executive management. The size of the sample group was 467 and a response of 187
questionnaires was received.
The fourth area covered the descriptive statistics and the frequency analysis. The method of
statistical significance was used to test the null hypothesis, indicating the coincidence of the
data reflection. The Cohen’s “d” and the effect size “r” tool were used for indication of
practical significance. Normality and variation tests (parametric and non-parametric) were
conducted on the responses.
49
The fifth area, we discussed the re-coding of the management levels in the response. The t-
tests indicated a substantial correlation when the management levels were grouped.
Executive to middle management was grouped as a new variable and the Engineers variable
was kept the same. It was also found that the businesses that do have business intelligence
systems show correlations with business performance management aspects. Therefore new
variables were created for those who have.
The sixth area, the findings of the analysis was discussed. Some similarities and differences
were found between the NewManagement and NewEngineers variables. The
NewManagement variable indicated a correlation association between business intelligence
and business performance management between the strategising and planning function of
business performance management. For the NewEngineers variable a correlation association
between business intelligence and business performance management between the planning
and monitor & analysis function of business performance management was detected.
The last part, the correlation of businesses that were satisfied with their business
performance management systems showed a positive association towards the relationship of
information used in the analysis & monitor function of it.
The final conclusions were derived from the findings and to build some sense of the
relationships that were found between the NewManagers and NewEngineers variables in the
natural resource sector.
Chapter 4 will be discussing the conclusions and recommendations of the empirical study.
50
CHAPTER 4
CONCLUSION AND RECOMMENDATIONS
4.1. INTRODUCTION
The primary objective of this study was to assess a relationship between business
performance management and business intelligence. During the literature research, the
function of both business performance management and business intelligence was
discussed. The relationship between business intelligence and business performance
management in the mining and manufacturing sector was researched through a literature
study which was discussed in chapter 2. The empirical study was discussed in relations to
the literature study in chapter 3.
As stated in §1.6, chapter 4 is devoted to draw conclusion from the survey and putting
forward recommendations for the establishment of business performance management
and business intelligence within the mining and manufacturing sector to catapult
performance of this industry in South Africa. The relationships between business
performance management and business intelligence in businesses in this sector were
analysed. A practical approach for the successful implementation of business
performance management and business intelligence is proposed to be used by the South
African mining and manufacturing sector to establish a competitive position in the natural
resource market by utilising these spheres to unlock potential in the businesses.
4.2. BUSINESS PERFORMANCE MANAGEMENT AND BUSINESS INTELLIGENCE
The literature and empirical research done in chapter 2 and 3 indicated relationships between
business intelligence and business performance management and the use of it to promote
synchronised efforts in the business to reach the goals. Business performance management
and business intelligence are both needed and it would be very difficult to have only one and
not the other to establish a competitive position in the market.
In figure 4.2.1 the input from business int
performance management processes. The empirical research confirmed relationships
between business intelligence and business performance management; however the
executive to middle management has a different ne
engineering level of the businesses.
Figure 3.8.3.1: Inputs of Business Intelligence
•Business
intelligence used as
input to view
indicators and
analyse situations
•Business
intelligence used
as input to define
strategic actions
Corrective
Actions
Monitor &
Analysis
4.2.1 the input from business intelligence is indicated in each of the business
performance management processes. The empirical research confirmed relationships
between business intelligence and business performance management; however the
executive to middle management has a different need for use of business intelligence to the
engineering level of the businesses.
: Inputs of Business Intelligence
•Business
intelligence used as
input to derive
plans and compile
key indicators
•Busines intellgence
used as input to
decision making,
predictive models
Corrective
Actions
Strategise
Plan
Monitor &
Analysis
51
elligence is indicated in each of the business
performance management processes. The empirical research confirmed relationships
between business intelligence and business performance management; however the
ed for use of business intelligence to the
Busines intellgence
Figure 3.8.3.2: Relationships of Use by Organisational Level
Figure 4.2.2 indicates the use of business intelligence by the organisation level in the
businesses, based on responses of the questionnaire.
The findings are summarized as followed:
• When moving upwards in
changes and this would be agreed that the focus of levels do differ over the planning
horizon
• Business intelligence has the capability to open up the unknown and give a sense of
“what does this mean”, “where are we”, “what can we do” questions
• Business intelligence has got the capability to create the one place to host all
information needs
• Business intelligence on its own will not synchronise all business efforts into reaching
business goals. A formal structured approach is needed to facilitate direction.
• Business intelligence span of use is from short to long term. Real
intelligence is a new addition to the business intelligence space and is more widely
promoted.
Relationships of Use by Organisational Level
Figure 4.2.2 indicates the use of business intelligence by the organisation level in the
businesses, based on responses of the questionnaire.
The findings are summarized as followed:
When moving upwards in the level of management the usage of business intelligence
changes and this would be agreed that the focus of levels do differ over the planning
Business intelligence has the capability to open up the unknown and give a sense of
n”, “where are we”, “what can we do” questions
Business intelligence has got the capability to create the one place to host all
Business intelligence on its own will not synchronise all business efforts into reaching
mal structured approach is needed to facilitate direction.
Business intelligence span of use is from short to long term. Real-time business
intelligence is a new addition to the business intelligence space and is more widely
Executives to middle
management
• Strategising + PLanning
• Corrective actions + Plan
Engineering level
• Planning + Monitor &
Analysis
• Monitor progress
52
Figure 4.2.2 indicates the use of business intelligence by the organisation level in the
the level of management the usage of business intelligence
changes and this would be agreed that the focus of levels do differ over the planning
Business intelligence has the capability to open up the unknown and give a sense of
Business intelligence has got the capability to create the one place to host all
Business intelligence on its own will not synchronise all business efforts into reaching
mal structured approach is needed to facilitate direction.
time business
intelligence is a new addition to the business intelligence space and is more widely
53
• Business intelligence and business performance management are both dependent on
each other to deliver a total performance package to a business.
Based on the above findings, it could be stated that business intelligence and business
performance management are a necessity for businesses and it would be rocky roads ahead
to establish the one could do without the other.
4.3. PRACTICAL DESIGN PRINCIPLES FOR A BUSINESS PERFORMANCE
MANAGEMENT AND BUSINESS INTELLIGENCE PROCESS
In the market there are numerous consulting firms that can assist in the deployment of
business performance management and business intelligence systems and processes. Some
will indicate a preference to a technology supplier, some will not indicate a preference and
will leave it to the business and some will not use a technology to base the processes on.
It might be worthwhile to explore these possibilities and to construct interviews with the
relevant consultants. Arrange current customer visits and try to establish some sense of
project success and effort. The approach discussed in this chapter is based on the author’s
experience of a non-technology approach. Business intelligence was not part of the scope,
deliberately. The approach was to embed the business performance management process
within the business by utilizing excel spreadsheets as predominant technology. This
approach was shot down by many business intelligence vendors. The advantage of this is to
ensure you understand your business’ value chain (value driver tree), information availability
and data structures. The added benefit of this approach, was the development time that were
minimised when the business intelligence project initiated.
Upfront -
1) Corporate objectives signed and agreed upon up front on delivery of the business
performance management solution
2) Establish a roadmap. Indicate the current state of the business and indicate the
end state. Plot down the approach to be taken, i.e. technology specific, any
technology or no technology.
54
3) Establish how the business performance management process will fit on the
current business structure. Are there any natural teams that build the hierarchy to
the top?
4) Select proven consulting (if outsourcing) vendors to assist in the project.
5) Select the best personnel in the business, from different levels, to assist in the
project.
A manufacturing business in Gauteng has partnered with a company from Australia, which
implement business performance management on top of the natural teams that existed on
the safety behaviour philosophy in the business. The project included defining the correct
value driver trees (VDT’s), improvement pipeline and a sustainable review process (business
performance management) to identify, monitor and control satisfying performance levels
constantly.
A mixed approach was decided upon, where the most impact could be derived on the
demarcated area of the business. A long-term plan was developed to indicate the growth of
the deployment. Approaching from a bottom up will create performance silos and putting the
project at risk. To avoid this, corporate objectives were created, with milestones and
priorities.
The business performance management system consists of:
• Dashboards
• Business intelligence reports to drill down into specific information relevant to the level
in which the employee is accountable for
• Task management
• Idea pipeline
• Review and performance meetings
4.3.1. Review and Performance Meeting
The business’ review and performance meeting (RPM), as indicated by figure 4.2.3, is a
process whereby alignment of people to business goals are done through key performance
indicators, task management and idea generation sessions. The measurable targets was
55
developed from the strategic goals and disseminated unto the lowest level within the
business and reviewed periodically (weekly to monthly) for deviations. This process is linked
to the cycle of business performance management for continuous performance.
Figure 3.8.3.1: Review Performance Management with accountability
GM
Manager
Superintendent/ Direct Reports
Manager
Supervisor
Mini-Business
Teams (MBT)
Supervisor
Superintendent/ Direct Reports
Mini-Business
Teams (MBT)
Information flow is 2-way
between each level
KPI complexity and
accountabilities are
tailored for each level
Source: PIP International - Adapted from wiring process
4.3.2. Wiring
Wiring is referred to as the formation of natural teams within the business, where the teams
can be grouped together to facilitate and report upwards the next layer of business key
indicators. The wiring also limits the information available to the team or individual based on
the position held. With this process the goals are broken up in lower levels in the business,
dictated by the value chain of the business and the accountability the position of an individual
are holding, and assigned to the position. This process is linked to the monitoring & analysing
and corrective actions sub-process of business performance management. The process
ensures the teams understand the lower objectives of the business, expectations and
deliverables of actionable tasks to accomplish goals (key performance indicators). The teams
monitor and execute accordingly to obtain good performance levels by guidance from the
dashboards and business intelligence reports.
General Manager
56
4.3.3. Key Performance Indicator Management
When the natural teams were formed, key performance indicators were assigned to them in
accordance to the level in which they are based in the business. These key performance
indicators have targets and are reviewed in the periodic review sessions. The targets are
broken down, just as the actual contribution of the indicator is represented. This section is
referred to the planning sub-process of the business performance management. Informed
actions are assigned to unfavourable outcomes. In figure 4.3.1.1, indicates the teams that are
on the lowest level within the business. The complexity of the key performance indicators
enlarge when moved upwards to higher levels in the business. Teams and individuals are
accountable for the key performance indicator level to which they are assigned to.
4.3.4. Task management
Collaboration between employees follows a structured approach for assignment of tasks to
one another. Actions are tracked within a system and linked to key performance indicators.
This is referred in the business performance management sub-process as corrective actions.
Predefined rule are applicable to allocating tasks to individuals and the re-assignment of it.
The process keeps track of the tasks and notifications of it to the originator, to view progress.
4.3.5. Idea Management
The “turbo” button that was indicated in §2.2.2, called business improvement, is facilitated
through the idea management process. The improvement process is a culture change, due to
the willingness of improvement contributions (ideas) that are needed from employees. The
process has got a “bucket” to receive these improvements, see figure 4.3.5.1 – opportunity
pool. The improvement process needs a continuous feed of ideas that will be reviewed and
prioritised for implementation. The business improvement process will also follow a
structured approach to maintain discipline and consistent measurable outcomes according to
a set standard.
57
Figure 3.8.3.1: Idea pipeline
Evaluation
Implem-
entation
Cash Flowing
(Delivering
Results)
Locked-In
&
Tracking
Idea
Opportunity
Pool
Idea
Idea
4 Gates
Idea
Source: Adapted from operational company
Figure 3.8.3.2 indicates a decline in time if the improvement process is not sustained. This
could be translated into loss of competitiveness. It also indicates the future possibility of
improvement that could be realised if all ideas are taken through to execution or
implementation. A healthy graph will always point in the upwards tendency. This is only
possible if there is an adequate pool of ideas being generated within the business.
Figure 3.8.3.2: Value creation of ideas
Planning Horizon
Avoid
the drop
0
10
20
30
40
50
60
-4 -3 -2 -1 Today 1 2 3 4
R
e
v
e
n
u
e
Historic growth rate
Close
the gap
Growth target
Source: Adapted from an operational company.
Ideas are generated through idea sessions. The idea generation supplies a healthy pipeline,
whereby a pool of ideas could be evaluated to determine the best ROI ideas to be put
58
forward for execution in the pipeline. Ideas are evaluated through a matrix, in the evaluation
process, and prioritised, see figure 3.8.3.1. Ideas put forward are implemented and then
moved on when implementation was completed. The specific value driver tree where the idea
is impacting the business is monitored for quality insurance of the executed work being done,
in the cash flowing stage, see figure 3.8.3.1. When the value of the idea is reaching a certain
milestone, it indicates the idea realised into a culture change and the business has accepted
the new way of performing in the new process. The idea is moved to the next stage of locked-
in and tracking. This stage enforces the value that was forecasted on the idea, to be
evaluated against actuals. All key performance indicators influenced by the idea are changed
and targets are updated to reflect the new standard.
The complete process of idea generation, evaluation, selection, execution, locked-in, and
close are the basic steps for an idea to go through the ranks of imbedding the improvement
into the business.
4.3.6. Impacts
How does this impact the business having a business performance management process
embedded? Transparency of performance is much higher up in the business, available on a
frequent time schedule. Closer relationships are established of moving actions forward.
Closer relationships are established between the business improvement departments and the
information management department.
4.4. RECOMMENDATIONS
It is recommended that all mining and manufacturing businesses to understand the
differences between business performance management and business intelligence as two
different processes and the output each process supply. There are relationships as the two
processes interact. Don’t expect delivery of a business intelligence system to deliver
business performance management, visa versa for expecting data mining capabilities out of a
business performance management process.
59
Understand the value chain of the business, quality of the data, as both business intelligence
and business performance management are information dependent.
The recommended approach if one needs to decide between the two for implementation, the
business performance management would be the author’s first choice. This gives way of
organising the data to information relationships and structures.
4.5. RECOMMENDED FURTHER STUDIES
Further research to be conducted in the field of real-time business intelligence in supporting
the business performance management process. Operational processing is based on
immediate actions to be taken. This makes the normal cycle of costing, normal monthly, to be
too slow for responding to the variability.
Secondly, the predictability of value chain impacts in business intelligence, set by goals
defined for the mining and manufacturing industry. The total value chain as an input to the
predictive model to analyse decisions made on longer horizons.
4.6. CONCLUSION
The aim of the study was to indicate if there are any relationships between business
intelligence and business performance management and the effect the two processes have
on each other within the natural resource sector. The responses were compared against
others in the industry to see if there are similarities to how other businesses perceive the two
processes.
A survey was conducted to determine the affect the two processes (business intelligence and
business performance management) do have on each other. The result indicated that the two
processes are dependent on each other through decisions that need to take place. Different
levels within the organisation have different usage for the processes.
Executive to middle management levels are more dominantly relying on business intelligence
to formalise strategies and converting it into solid plans. There was also a positive correlation
60
between the use of business intelligence in the planning and corrective action processes of
business performance management.
In the engineering level there was a negative correlation between business performance
management assisting in managing objectives towards business intelligence assisting
business goals.
The combination of the two spheres being deployed at an organisation will result in quicker
turn around on reaching goals in the business. Embedment of these processes result in
improved and organised contributions towards the goals in the business.
4.7. SUMMARY
The first part of the chapter was dedicated to discuss the reason why the empirical study was
conducted and drawing the conclusion from the findings in chapter 3. The relationships of the
two systems on each other were highlighted and the use of it by different levels in the
business was indicated.
Secondly, a practical approach of such processes being embedded within a business as
elaborated on. The upfront activities that need to be checked before entering into a project
might save some unnecessary pit fall along the way.
A typical business performance management process was highlighted and gives a clearer
view to how the process and system could look and work. Indication of the improvement
process that’s like a “turbo” button on the business performance management process was
explained.
High level impacts were raised and would differ from organisation to organisation. Most
cases people feel intimidated by the exposure of information being rolled up into higher levels
(Big Brother-effect). Recommendation into the real-time environments was given for further
studies.
Finally it was concluded that the research objectives as set out in §1.6 were met and possible
future research was recommended.
61
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ANNEXURE A
65
66
67
68
69
70
71
72
73
74
75
76
77
78
ANNEXURE B
79
ANNEXURE C
Question
Number
Question Description
Valid % (Frequency)
Mean
Std.
Deviation
Number
Missing
Very
Relevant
Relevant
Almost
Relevant
Irrelevant
Q10R Business BPM satisfied - Evidence
21.35 62.36 16.29 1.95 .61316 9
Q11R Business BPM satisfied - KPI's
33.33 47.46 19.21 1.86 .71298 10
Q12R Business BPM satisfied - Integration business
processes
26.75 51.59 21.66 1.95 .69611 30
Q13R Business BPM satisfied - Agility to steer
business
22.29 50.96 26.75 2.04 .70113 30
Q14R Business BPM satisfied - Align strategy and
execution
19.23 60.90 19.87 2.01 .62730 31
Q15R Business BPM satisfied - Learning
organisation
16.45 58.55 25.00 2.09 .64020 35
Q17 Buisness value BPM in business
16.57 49.17 25.41 8.84 2.27 .841 6
Q18 IM value BPM in business
19.78 41.21 31.87 7.14 2.26 .858 5
Q31 BI will help you with decisions?
30.73 33.52 19.55 16.20 2.21 1.055 8
Q33 BI will help you plan tasks?
25.28 36.52 16.85 21.35 2.34 1.079 9
Q34 BI will help you reach business goals?
23.16 35.59 25.99 15.25 2.33 .998 10
Q35 BPM will help you reach business goals?
25.84 37.08 19.66 17.42 2.29 1.037 9
Q36 BI help in strategy?
24.29 38.42 19.77 17.51 2.31 1.027 10
Q37 BI help in planning?
26.40 38.76 14.61 20.22 2.29 1.069 9
Q38 BI help in monitor and analysis?
28.09 34.27 20.22 17.42 2.27 1.055 9
Q39 BI help in corrective actions?
23.60 32.58 24.72 19.10 2.39 1.048 9
Q40 BI help with id of opportunities?
25.71 34.29 17.14 22.86 2.37 1.101 12
Q41 BI help in id of actions?
21.71 37.71 22.86 17.71 2.37 1.013 12
Q42 BI help in creating strategies?
27.43 31.43 22.86 18.29 2.32 1.067 12
Q43 BI help in creating plans?
24.71 32.18 22.99 20.11 2.39 1.068 13
Q44 BPM assist you in managing business
objectives?
24.28 34.68 22.54 18.50 2.35 1.044 14
Q45 BPM manage plans?
20.00 32.57 28.57 18.86 2.46 1.016 12
Q46 BPM help in monitor and analysis?
12.07 28.16 36.21 23.56 2.71 .961 13
Q47 BPM assist in taking corrective actions?
25.14 34.86 23.43 16.57 2.31 1.028 12
Q48 Define business startegy - info for strategy?
25.14 38.86 20.57 15.43 2.26 1.005 12
Q49 Define business plan - info for plan?
28.74 31.03 19.54 20.69 2.32 1.102 13
Q50 Define monitor and analysis - info for it?
29.31 29.31 21.84 19.54 2.32 1.095 13
Q51 Corrective actions - have information
relationship?
25.29 35.06 21.26 18.39 2.33 1.049 13
doc_568813387.pdf