Description
Business intelligence (BI) plays a critical role in providing actionable intelligence to enable good business decision-making.
88 Southern African Business Review Volume 13 Number 2 2009
The availability and use of competitive and
business intelligence in South African business
organisations
P. Venter & D. Tustin
A B S T R A C T
Business intelligence (BI) plays a critical role in providing actionable
intelligence to enable good business decision-making. International
research shows clear evidence of the bene?ts of implementing sound
BI practices. However, within a South African business context, an
understanding of the practice, impact and bene?ts of BI is only partly
addressed by existing research. Consequently, this article presents
the most salient ?ndings of a recent BI study, which was one of the
few such studies that have been conducted in South Africa in the
21st century. Although the discussion re?ects fairly high general
satisfaction levels with BI among South African businesses, some
problems related especially to external BI dimensions are highlighted.
An equally important and major concern raised by the article is the
apparent lack of companies capitalising on BI opportunities and
coordinating BI functions e?ectively. Of concern at the general
management level, in particular, are the low satisfaction levels with
BI quality, as well as various aspects of BI collection, analysis and
dissemination. Despite the fact that businesses use BI functions and
planning support software, the survey ?ndings reveal insu? cient
investment in sophisticated BI analysis tools.
Key words: business intelligence, competitive intelligence, marketing intelligence,
business intelligence systems
Prof. P. Venter is at the Graduate School of Business Leadership, University of South Africa, and Prof. D. Tustin is
at the Bureau of Market Research, University of South Africa. E-mail: [email protected]; [email protected]
P. Venter & D. Tustin
89
Background
It would seem that there is no commonly accepted term for referring to internal and
external intelligence required for business decision-making. Market (or marketing)
intelligence, competitive intelligence, business intelligence and other terms are
all used at various times to describe more or less the same concept. Hannula and
Pirttimäki (2003: 593) define business intelligence (BI) broadly as “organized
and systematic processes which are used to acquire, analyse and disseminate
information significant to their business activities”. This definition is similar to
definitions commonly used for competitive intelligence (CI) (for example, Viviers,
Saayman, Muller & Calof 2002: 28; Wright, Pickton & Callow 2002: 350–351), with
a focus on the intelligence processes. Definitions used by Herschel and Jones (2005:
45), who adopted the Gartner definition of BI as a “set of technologies that gather
and analyse data to improve decision-making”, and Harrington (in Nemati 2005:
66), who describes BI as “a suite of tools and technologies to enhance the decision-
making process by transforming data into valuable and actionable knowledge to gain
a competitive advantage” have a stronger focus on the technology. Negash (2004:
178) suggests that BI systems combine data-gathering, data storage and knowledge
management with analytical tools to present complex internal and competitive
information to planners and decision-makers. Several characteristics of BI, in the
context of this article, emerge from these definitions:
• BI refers to both internal and external information.
• It relates to a process of adding value to information: gathering, analysis and
dissemination are all value-adding activities in the information cycle.
• The technologies used in the process of gathering, analysing and disseminating
information are an integral part of the underlying processes.
• The goal of BI is to support management decision-making.
Understanding why BI is important to organisations becomes clear when the
concept of market orientation is examined. The marketing concept is a commonly
accepted notion, namely that if you satisfy your customers’ needs, you will attain
organisational objectives. The marketing concept manifests in organisations as
market orientation (Shoham, Rose & Kropp 2005: 436, citing Deng & Dart 1994;
Walker, Mullins, Boyd & Larréché 2006: 12–13). Shoham et al. (2005: 436) describe
market orientation as the firm’s ability to anticipate, react to and capitalise on
environmental changes, leading to superior performance. BI therefore plays a
critical role in providing actionable intelligence to enhance market orientation.
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Various studies have been conducted over time to establish the impact of market
orientation on performance. For example Kara, Spillan and DeShields (2005) found
a positive correlation between market orientation and the performance of small
service businesses in the USA, while Aldas-Manzano, Küster and Vila (2005) found
a positive relationship between market orientation and certain aspects of innovation
in Spanish firms. A meta-analysis conducted by Shoham et al. (2005) concludes
that market orientation (and by implication, BI) positively affects organisational
performance and behaviour.
Searches of online databases and journals suggest that most of the South African
research published since 2000 focused on the South African CI environment
and practices in various contexts (for example Begg & Du Toit 2007; Brummer,
Badenhorst & Neuland 2006; De Pelsmacker et al. 2005; Viviers, Saayman & Muller
2005; Viviers & Muller 2004, 2005; Du Toit 2003; Viviers, Muller & Du Toit 2005;
Viviers, Saayman & Muller 2002; Viviers, Saayman, Muller & Calof 2002). Sewlal
(2004) investigated the effectiveness of the web as a CI tool. These studies generally
focused on the competitive dimension.
With regard to the application of BI technology, O’Brien and Kok (2006)
reported on the potential of BI to produce higher profits in the South African
telecommunications industry, while other research focused mainly on specific
subsets or applications of BI, for example online analytical processing (OLAP)
(Hart & Porter 2004), data marts (Ponelis & Britz 2003) and data mining (Hart 2006;
Hart, Davies, Barker-Goldie & Theron 2002). Venter (2005) explored the reasons
for success and failure of BI systems, and Conradie and Kruger (2006) investigated
the issue of information quality in BI.
Against this background, a broad research investigation of how BI is practised in
South Africa is timely. More specifically, this paper examines the BI needs, practices
and usage in South African business organisations.
Purpose of the research
The purpose of the research was to conduct a broad overview of the BI practices and
preferences of decision-makers in South African organisations. More specifically,
the study focused on the following research objectives:
• To determine BI requirements and availability
• To assess BI practices in business organisations over a range of industry sectors
and managerial functions
• To determine the usage of BI and CI technologies and methods
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91
• To determine the overall satisfaction with BI and the contribution BI makes to
decision-making in the organisation.
Literature review
Many organisations are faced with unprecedented growth in the sheer amount
of internal and external data available to them. In many instances, organisations
create information systems to deal with business requirements as these develop,
often leading to many disparate systems. As a result, many organisations end up
with voluminous data about their business but relatively little business knowledge
(Harrington, in Nemati 2005: 66). This situation is a direct result of the lack of BI.
In essence, BI provides a means for extracting information from the clutter that
would be useful for reporting and decision-making purposes. Not surprisingly, the
information technology (IT) industry coined the phrase ‘business intelligence’,
popularised by Howard Dresner, a Gartner Research Fellow (circa 1989) to describe
the concepts and methodologies designed to improve decision-making in business
through the use of facts and fact-based systems (Chou, Tripuramallu & Chou 2005:
344).
While the notion of BI has always been inclusive of external sources of
information (for example, competitive information) and unstructured information,
much of the focus during the early years has been on integrating and extracting
structured internal data, for example, data from customer relationship management
(CRM), point-of-sale or billing systems. It could therefore be argued that BI has not
been entirely successful in integrating internal and external data (see, for example,
Cody, Kreulen, Krishna & Spangler 2002).
Components of BI
Figure 1 presents a schematic overview depicting the main components of BI. The
components of BI are discussed in more detail in the following section, after which
information systems (IS) support for BI is discussed.
It is clear from Figure 1 that BI is obtained in the form of structured and
unstructured data from both internal and external sources. Internal sources typically
comprise legacy systems (a term commonly used to describe historical systems that
are still used because the organisation would not, or cannot, redesign them) as well
as various operational systems, such as point-of-sale systems, online transaction
processing (OLTP) systems and customer relationship management systems. Most
internal data are structured or semi-structured.
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Figure 1: Components of business intelligence
External intelligence is typically obtained through competitive intelligence or
market intelligence processes that produce mostly unstructured information about
competitors and customers from primary and secondary sources. In addition,
macro-environmental data from environmental scanning processes could also be an
input into BI systems. Research conducted by Lackman, Saban and Lanasa (2000)
suggests that the most useful primary sources of external intelligence are customers,
manufacturers, dealers and distributors, research and development, the sales force,
physical evidence (for example, a product or prototype) and market research projects.
Several studies have indicated that members of staff are the most critical primary
source of intelligence (for example, Wright & Calof 2006).
The data and information obtained internally and externally from various
disparate sources are usually stored centrally and made available in a format that
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93
allows easy extraction of data. This process could make use of technologies such as
intranets, data warehouses or data marts (subsets of data with a specific functional
focus). Decision-makers or their ‘agents’ (which could be a BI analyst) can extract
data from the central data repositories in order to support decision-making. This
can be done either as reports that are created and disseminated regularly without
a specific request (for example, a weekly or monthly report with detailed sales for
each of the distribution channels) or as an ad hoc requirement, in response to which
the data repositories can be queried, and a once-off report can be compiled.
The BI process
Viviers, Saayman, Muller and Calof (2002) suggest that CI is above all a systematic
process of planning, collection, analysis, communication and process management.
The same process can be applied to BI. Against this background, the most important
process components include the following:
• planning, which suggests that the BI process is not haphazard, but rather focuses
on those issues that are of most importance to the organisation’s management;
• collection of BI from various internal and external sources and in line with the
priorities set during the planning phase;
• analysis, which is generally accepted as the phase where true intelligence is
created; here, ‘raw’ information is converted into actionable intelligence on
which strategic and tactical decisions can be based; and
• communication, which is the phase during which the actionable intelligence is
disseminated to decision-makers to act.
One of the key challenges for CI is to create the process and structures to enable
the organisation to execute these phases as effectively and efficiently as possible.
Walker et al. (2006: 13) suggest that the following are examples of such procedures
and structures:
• more detailed environmental scanning;
• continuous, real-time information systems;
• obtaining feedback from, and doing joint planning with, key suppliers and
customers;
• decentralising strategic decision-making;
• encouraging entrepreneurial thinking among lower levels of management; and
• using interfunctional management teams to analyse issues and develop strategic
initiatives outside the formal planning processes.
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94
BI and organisational culture
It is evident from the previous discussion that there is a strong need for organisational
awareness and market orientation in the organisation to facilitate the BI process as
effectively as possible. Meehan (1999) concludes that virtually all companies are
convinced of the importance of market intelligence and are indeed spending much
time and effort on the rhetoric of ‘being customer focused’. Most companies are also
generating considerable market intelligence. However, a true market orientation
requires more than rhetoric and the mere existence of information. In this regard,
Meehan (1999) suggests the following as important elements in becoming truly
responsive and creating continuous learning about the market (in other words,
being truly market oriented):
• close customer contact to the extent that customer needs dominate the thinking
of all employees;
• measurement and reward systems that are linked to customer satisfaction; and
• leadership (in other words, top management support and commitment).
In summary, the foregoing discussions reflect an organisational culture that is
supportive of customer focus and a learning organisation that shares information
and learning across the organisation. Other guidelines to becoming more market
oriented (in other words, developing a culture that is conducive to BI) are provided
by Hayden (1993: 33–46), Slater and Narver (1994: 25–27), Slater and Narver
(1995: 71) and Herschel and Jones (2005). These guidelines include the following:
• Educate and gain the commitment of top management to a culture of market
orientation. This would also ensure buy-in throughout the organisation. The
views that CEOs hold and how they reward new ways of learning or using BI can
be crucial to the success of a BI programme.
• Focus on a strong, open culture in which BI and knowledge are exchanged and
such exchanges are rewarded. In such a culture, trust is crucial. As Hayden
(1993: 37) points out, a strong, open culture leads to relatively uniform attitudes
and behaviour with an external focus. In this regard, some practical guidelines
for establishing such a culture include the following:
— understanding the philosophy of marketing and internal marketing
throughout the organisation;
— using marketing research (as opposed to simply generating it);
— recognising the value of implementing market segmentation for the
organisation;
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95
— working with suppliers to incorporate customer benefits into product and
service specifications;
— making customer benefits part of contractual deliverables alongside financial
control and activity (in other words, customer benefits provided need to be
measurable);
— empowering all levels of consumers by providing them with a way to
communicate with the organisation;
— selecting and rewarding staff on measurable, market orientation-based
criteria;
— taking a marketing approach to strategic planning by making the market
and customer focus the driving force of strategic planning;
— devolving management for service provision by bringing the managers closer
to the customers – this may imply a flattening of traditional service provision
structures; and
— investing in public relations for key stakeholders.
Because of its external focus and interactive nature, marketing in the organisation
plays a vital role in creating an organisation that thrives on generative learning
(in other words, the willingness to question long-held assumptions about its own
beliefs). This in turn creates the most sustainable platform for organisational
survival. In this, the potential role of market orientation as a philosophy based on
learning, and the sharing of BI should be obvious.
BI technologies
Although a detailed technical discussion of BI technologies falls outside of the scope
of this article, the following section serves to identify and put into context some
commonly accepted technologies that support BI. Information technology (IT) in
the form of hardware and especially software plays a key role in ensuring that BI is
gathered, stored, analysed and presented in a simple, useful manner. The software
promotes business performance management and assists in making more informed
business decisions by making accurate, current and relevant information available
as required by managers. Figure 2 outlines the most common IS support elements
for BI.
A brief explanation of the most pertinent technologies reflected in Figure 2 is
presented in the next sections.
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Sources: Chou et al. (2005: 346), Dearstyne (2006), Metaxiotis, Ergazakis, Samoulidis & Psarras
(2003); Daniel, Wilson & McDonald (2003)
Figure 2: Information systems support for business intelligence
Information systems and sources of internal data
Information systems and sources of internal data include the following:
• Legacy systems are systems that are historical and possibly ‘outdated’, but for some
reason are still being used by the organisation (for example, the system may be
too costly to redesign).
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• Enterprise resource planning (ERP) systems are operational systems that have been
developed over years to ‘run a business’ and generate operational information
The focus of ERP is typically supply chain activities (Daniel et al. 2003: 839).
• Customer relationship management (CRM) systems are regarded as the marketing
equivalent of ERP systems and serve to integrate the customer-facing functions
such as marketing, sales and customer service (Daniel et al. 2003: 839).
• Online transaction processing (OLTP) refers to those systems that facilitate and
manage transaction-oriented applications, for example, a bank’s automated
teller machines (ATMs).
• Clickstream data is the record of an internet user’s ‘virtual trail’ that is left while
surfing the Internet. It includes details of activity on the internet, for example,
every website and every page of every website visited. These data are potentially
valuable to internet marketers and advertisers (www.webopedia.com).
Information systems and sources of external data
Both Dearstyne (2006) and Daniel et al. (2003) argue that web activities could be
better utilised for BI purposes. Dearstyne (2006) argues that weblogs (blogs) are
company records and should be properly managed as such, making these a potential
input for BI. Daniel et al. (2003) suggest that the internet is a potential source of
new ideas, for example, through internet-based focus groups or other discussion
forums. Daniel et al. (2003) further suggest that the aggregation and analysis of
market research and research and development projects and findings are further areas
that require IS support.
Integration and storage of data
Some businesses use data warehouses because they are a logical collection of
information gathered from various operational databases for the purpose of creating
business intelligence. The purpose of a data warehouse is to provide rich, timely,
clean and well-structured information to BI analysis tools (Chou et al. 2005: 344).
Similarly, data marts are small-scale data warehouses designed to meet a specific
function or department’s BI needs. (Chou et al. 2005: 347). A further tool is an
intranet, which is a version of the internet confined to a specific organisation and
is used to aggregate and disseminate information of interest to the members of the
organisation. Finally, knowledge management (KM) is also widely implemented.
KM involves “a systematic process of finding, selecting, organizing, distilling and
presenting information in a way that improves an employee’s comprehension in a
specific area of interest. KM helps an organisation to gain insight and understanding
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from its own experience. Specific KM activities help focus the organisation on
acquiring, storing and utilizing knowledge for such things as problem solving,
dynamic learning, strategic planning and decision making” (Herschel & Jones 2005:
45).
Data extraction
Query and reporting tools are the BI tools used to extract targeted information either
on an ad hoc basis (query) or as regular reports in a specific predetermined format.
In turn, online analytical processing (OLAP) is characterised by the fast, dynamic and
multidimensional analysis of aggregate data (for example, from a data warehouse),
and the ability to perform complex modelling with the extracted data to support
managerial decision-making (Hart & Porter 2004: 47). Hart and Porter (2004)
suggest that OLAP conforms to five characteristics:
• fast, referring to OLAP’s goal of delivering user responses in five seconds or less;
• analysis, meaning the system’s ability to handle any relevant business or statistical
analysis for a given user;
• shared, meaning the ability of the system to enable concurrent shared use;
• multidimensionalilty, referring to the provision of a multidimensional, conceptual
data view and supporting multiple data hierarchies; and
• information, meaning all data and calculated information required by the user.
A further useful tool is data mining, which is an analytical process designed to
explore data (usually large amounts of data that are typically business or market
related) in search of consistent patterns and/or systematic relationships between
variables, and then to validate the findings by applying the detected patterns
to new subsets of data. Hart, Davies, Barker-Goldie and Theron (2002: 41) cite
the following definition of data-mining by Bradley: “an information extraction
activity whose goal it is to discover hidden facts contained in databases, using a
combination of machine learning, statistical analysis, modeling techniques and
database technology, which infers rules that allow the prediction of future results”.
The ultimate goal of data-mining is prediction.
Hess, Rubin and West (2004) also advocate the use of geographical information
systems (GIS) as a decision-support system for marketing. By extension, GIS is also
a useful BI tool, as Hess et al. find that one of its strengths is its ability to integrate
information from disparate sources and span multiple decision domains. Finally,
operational executive information systems (OEIS) refer to ERP data summarised in
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the form of charts, tables and reports for the purposes of management (Daniel et al.
2003: 839) and data extraction.
Applications
Planning and decision support tools refer to a variety of tools in several categories that
may be used to support the planning and decision-making processes in organisations.
This may include, for example, simulation tools and planning templates (Daniel et
al. 2003: 839). Furthermore, artificial intelligence (AI) is a category of technology
that simulates human thinking patterns. Metaxiotis et al. (2003) identify three main
categories of application of AI, namely:
• Expert systems are computer systems with a well-organised body of knowledge
that emulates expert human decision-making within an established set of rules.
• Artificial neural networks (ANN) simulate the working of the human brain,
using a large number of interconnected ‘neurons’ to allow a computer system to
‘learn’ by example. One drawback of ANN is that it can only use data that are
numerically presented.
• Intelligent agents are computer systems in some specified environment that are
able to take autonomous action in order to meet design objectives. In the process,
agents act autonomously, can reason about themselves and can be mobile.
The theoretical foundation presented in the literature overview provided a
general overview of BI and BI systems. Findings resulting from this exploratory
phase motivated the study to explore the means in which BI is understood and
practised by South African organisations. The outcome of the research findings and
methodology used to collect data from a sample of 222 medium to large organisations
in South African are discussed in the following sections.
Research methodology
The research study was mainly exploratory and descriptive in nature, with the
objective of providing an overview of the state of BI usage and needs in South
Africa. The study utilised a quantitative survey methodology. Questionnaires were
administered by personal interview. The first step was to design the questionnaire,
and the following research items were included:
• Company and respondent particulars (for example, the size of the business and
core business activity).
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• BI requirements and availability. This section focused on a range of business
intelligence requirements and needs. This included information types from
the macro-environment, the market environment and internal environment.
Firstly, the importance of 12 business intelligence requirements was measured.
Concomitantly, the availability of these BI items to decision-makers was
recorded. Finally, the overall satisfaction with the quality of BI was measured by
the research model.
• BI practices and processes. This section contained 46 items measured on a five-
point Likert scale, with 1 representing ‘totally disagree’ and 5 representing ‘totally
agree’. This section was used to measure BI practices and processes within the
organisation.
• BI tools and functions. Various BI tools and functions were listed, and respondents
had to indicate which were used in their organisations.
• Organisational functions. Finally, a number of organisational functions and the
extent to which these functions benefit from BI were investigated in the research
model.
The next step was to identify a sampling frame and to draw a sample. In the
absence of a single comprehensive sampling frame of business intelligence users,
a list of business organisations with the potential for business intelligence use was
constructed with the assistance of the University of South Africa’s Bureau of Market
Research (BMR) and used for interviewing purposes. Personal interviews were
conducted with respondents (business decision-makers) from various business areas,
targeting businesses with more than 100 full-time employees. The main reason for
excluding smaller businesses was that BI is generally more formal and organised in
larger organisations. A total of 222 usable responses (from business intelligence users)
were obtained from 155 sample units (businesses), with a maximum response of two
business intelligence users (from different departments) per business. Participating
businesses were mainly based in Gauteng (65.8%), while 14.0% were located in the
Western Cape and 13.5% in KwaZulu-Natal. Respondents represented a range of
management levels and business functions (as will be discussed).
To support comparative analysis, the research model design included four
different research variables, which are discussed as follows:
• It is commonly accepted in management theory that the designation of the
respondent plays a role in his/her information needs and usage. For example,
top managers are theoretically more externally focused (and subsequently have
a greater need for external information) than junior managers. In this research
study, the comparison was mainly between top management, namely directors
and senior managers, who comprised 51.8% of the sample, and middle managers
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(37.4%). The remaining 10.8% of the sample (junior managers and functional
specialists) were excluded from this analysis.
• The size of the business could also have an impact on the respondent’s BI needs
and practices. Larger businesses generally have more formalised BI processes
and practices than smaller organisations. In this analysis, businesses with
between 100 and 150 employees (31.1%), 101 to 350 employees (18.5%), 351 to
100 employees (28.4%) and more than 1 000 employees (22.1%) were compared.
• The business or functional area also determines the needs for BI and the way
in which it is used. For example, externally focused functions such as sales and
marketing should theoretically have a greater need for external information than
more inward-looking functions such as operations. For this research study, the
following categorisations were used:
— externally focused functions (including sales, marketing and strategic
planning) (43.7% of respondents);
— internally focused functions (including operations, IT, human resources and
finance) (47.4% of respondents); and
— general management (5.4% of respondents).
• It could also be argued that the industry or sector within which a business operates
determines the need for and usage of BI. For example, industries experiencing
volatile change may have different BI needs from industries that are ‘stable’. In
this analysis, the following sectors or industries were compared:
— primary sector (agriculture and mining) (6.8%);
— secondary sector (manufacturing, utilities, construction, transport and
communication) (55.9%); and
— tertiary sector (wholesale, retail, hotels and restaurants, financial and real
estate services, community and personal services) (36.6%)
The discussion of the research findings in this article is devoted largely to
analysis of the research findings according the comparative criteria that have been
highlighted and are discussed in the following sections.
Research ?ndings
BI requirements and availability
The research model was designed to measure the importance and availability of
various categories of information, as will be outlined:
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• macro-environmental information (economic trends, technological trends, social
trends and customer demographics and lifestyle);
• market environment information (direct customer feedback, competitor
intelligence, sales forecasts, information on regulatory bodies and information
on potential business partners); and
• internal information (internal financial information, analysis of sales data and
operational performance data).
Using these categories, respondents were asked to rate the importance of
each type of information and its availability within the organisation. In addition,
respondents were requested to indicate their overall satisfaction with BI within the
organisation. The outcome of these research findings are shown in Table 1 using
both non-parametric and parametric statistical analysis approaches.
Table 1: Comparison of the importance and availability of information categories
a.
Importance
(top-2-box %)
b.
Availability
(top-2-box %)
c.
Gap
(a–b)
d.
Importance
(mean)
e.
Availability
(mean)
f.
Statistical
significance
of d–e
Direct customer feedback 85.6 73.9 11.7 4.27 3.63 .000
Sales forecasts 83.8 71.6 12.2 4.21 3.67 .003
Operational performance
data 83.3 78.8 4.5 4.17 4.02 .153
Competitor intelligence 81.1 63.5 17.6 4.11 3.99 .000
Analysis of sales data 81.1 73.0 8.1 4.09 3.91 .271
Economic trends 75.2 63.5 11.7 3.95 3.65 .000
Internal ?nancial
information 75.2 72.1 3.2 3.99 4.01 .264
Technological trends 74.8 64.0 10.8 3.87 3.68 .009
Information on regulatory
bodies 69.8 52.7 17.1 3.86 4.09 .000
Customer demographics
and lifestyle 69.4 61.3 8.1 3.80 3.45 .017
Information on potential
business partners 61.3 51.8 9.5 3.95 3.55 .026
Social trends 54.1 53.6 0.5 3.52 3.70 .333
Notes:
n = 222
Signi?cance smaller than 0.05 (shaded areas) indicates a di?erence between means signi?cant at a 95% level of
con?dence.
Table 1 compares only top-2-box scores (ratings of 4 and 5 on the five-point Likert
scale). The list reflected in the table is ordered according to the top-2-box scores based
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103
on the importance ratings of respondents. From the first two columns, a ‘gap’ was
computed reflecting the difference between the top-2-box scores for importance and
availability by information type. For comparison purposes, means (average scores)
for the same variables were calculated, and a t-sample test analysis approach was
used to firstly compare the mean scores of importance and availability of information
and finally to measure any statistically significant differences between the variables.
From a statistical point of view, it should be noted that, due to the nature of ordinal
data, parametric statistical analysis should not be the primary analysis approach
followed, although the findings from the use of parametric statistical analysis in this
instance mirrored the findings from non-parametric analysis.
The following results are evident from Table 1:
• The five most important categories of information are dominated by information
from the market environment, such as direct customer feedback, sales forecasts,
competitor intelligence and analysis of sales data. Operational performance data
(internal environment) were also identified as critically import. With the exception
of economic and technological trends, information on the macro-environment
was not considered to be as important as other categories of information.
• The biggest gap between the importance and availability of information is showed
for market environment information. In this regard, competitor intelligence
(17.6%), information on regulatory bodies (17.1%) and sales forecasts (12.2%)
lead the way.
• Statistically significant differences between importance and availability (t <
0.05) were recorded for all variables except operational performance data,
analysis of sales data, external financial information and social trends. In relative
terms, these information categories are thus as important as they are available
among organisations. For the information categories reflecting a statistically
significant difference between importance and availability (t < 0.05), six reflect
a desire for improved information. Categories where mean importance scores
exceed availability scores, and statistically significant differences between means
scores are evident, include direct customer feedback, sales forecasts, competitor
intelligence, economic and technological trends and information and regulatory
bodies. Ultimately, these categories reflect essential future information and BI
demands of South African companies.
In considering the responses to the question regarding the overall quality of BI
within South African organisations, only a few respondents rated this as ‘excellent’
(9.9%). However, 51.8% rated BI quality as ‘very good’, suggesting a relatively
high level of overall satisfaction with a mean score of 3.63. This finding compares
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104
favourably with that of Venter (2000: 233), who reported a mean score of 2.5 on the
overall perceived quality of marketing intelligence among South African marketing
decision-makers.
In order to further broaden the discussion, the next section presents the research
findings across business size, business area, management level and sector. To
determine the presence of statistically significant differences, the analysis applies a
chi-square test for the top-2-box scores (see Table 2).
In comparing the survey findings across organisation size, organisations
with between 150 and 350 employees seemed to express a lower need for certain
categories of information (CI and information on potential business partners).
Similarly (and perhaps for the same reasons), they seemed to be more satisfied
than other cohorts with the availability of internal financial information. Also, and
almost paradoxically, they are not particularly satisfied overall with the quality of BI
available to them (56.1%). Large businesses seemed to be less satisfied than other
cohorts with the BI available to them (49%). When compared by company size,
Table 2 shows statistically significant differences only for the importance of CI. In
fact, businesses with 151 to 350 employees regard CI as far less important when
compared to other business categories.
Considering the fact that tertiary sector businesses (mostly services and trade)
typically have more direct contact with end-users, it is not a surprising finding
that they expressed a higher relative need for information that would help them
understand customer behaviour better (for example, social trends, customer
demographics and lifestyle, and the analysis of sales data). The importance of social
trends, and customer demographics and lifestyle both show statistically significant
differences across economic sectors, with the primary and secondary sectors
recording much lower scores for these items than the tertiary sector. Similarly, and
perhaps due to the greater complexity of service businesses and the measurement
of service delivery, tertiary sector businesses seem to be less satisfied with the
availability of operational performance data.
Counter-intuitively, middle management respondents attached a higher
importance to some categories of macro-environmental data (economic and
technological trends), while top management respondents regarded the analysis of
sales data as relatively important. Middle managers were somewhat more satisfied
with the availability of information on technological trends and sales forecasts than
middle managers.
In considering the different business areas, externally focused functions (such
as sales and marketing) and general management expressed a relatively high need
for information on the market environment, especially customers (customer demo-
P. Venter & D. Tustin
105
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The availability and use of competitive and business intelligence in South African business organisations
106
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P. Venter & D. Tustin
107
graphics and lifestyle, as well as direct customer feedback). General managers
attached less importance to sales forecasts, which arguably constitute a more tactical
category of information. In several categories of information, general managers
were comparatively less satisfied with the availability of information. Similarly, they
were also less satisfied than other business areas with the overall quality of BI. This
may be indicative of a BI quality problem experienced at executive level.
The key findings resulting from the foregoing discussion (see Table 2) suggest
that there are some gaps between the importance and the availability of certain
important categories of information required for decision-making. There are also
some significant differences in the importance and availability of certain categories
of information across respondent and organisation characteristics that may signify
unmet BI needs.
In general, decision-makers seem to be moderately satisfied with the overall
quality of the BI available to them, but there does seem to be a significant proportion
of directors (60%) and general managers (49%) that are less satisfied than other
management categories. This is a potential indication of BI quality problems at
executive level.
The application of BI in the business
The application of BI in the business was measured in the survey research by using
46 different items, which covered the following areas:
• BI quality: accuracy, timeliness and right format;
• the BI process: collection, dissemination and analysis;
• responsiveness to BI: the extent to which BI is used;
• BI and information systems (IS): the extent to which IS support BI; and
• BI and decision-makers: the extent to which decision-makers value BI and apply
it in decision-making.
The outcome of the research findings related to these items is analysed in Table
3. The table indicates the top-2-box scores and means for each item (statement), as
well as the corresponding area category (as already outlined).
When it comes to overall BI quality, the results depicted in Table 3 suggest that
most decision-makers are fairly satisfied with the accuracy of BI (top-2-box score
of 83.3%). However, they were less satisfied with the timeliness of BI, receiving BI
proactively, and the format in which they received it. In particular, they felt that they
often had to process BI before it was useful to them.
The availability and use of competitive and business intelligence in South African business organisations
108
Table 3: The application of BI in the organisation
BI and information systems
Top-2-
box %
Mean
BI overall quality
In our establishment BI is generally accurate 83.3 4.0
BI is usually available to me by the time I need it 69.8 3.7
I routinely receive BI relevant to my responsibilities without asking for it 68.5 3.7
BI is usually available to me in the format that I prefer 66.7 3.7
I often have to process BI before I can make decisions* 81.1 4.0
BI collection
We meet with key customers at least once a year to ?nd out what products or services
they would need in future 84.2 4.1
The establishment has a structured programme to obtain the feedback needed to
understand customers
83.3 4.1
We survey end-users at least once a year to assess the quality of our products/
services
82.4 4.2
Our establishment does a lot of market research 66.7 3.7
BI analysis
We are constantly creating new knowledge about our business 89.2 4.1
This establishment has a good sense of its own strengths and weaknesses compared
to its competition
88.7 4.1
The establishment regularly analyses data on customer satisfaction 86.5 4.1
We periodically review the likely e?ect of changes in our environment on customers 83.3 4.1
The establishment studies underlying trends or patterns in customer behaviour 82.9 4.0
Customer analysis is a key strength of this ?rm 82.9 4.1
This establishment has up-to-date pro?les of key competitors 81.5 4.0
BI dissemination
We have interdepartmental meetings at least once a quarter to discuss market trends
and developments
88.7 4.3
Sta? members at all levels regularly report back on customer needs 84.2 4.1
Senior management regularly discusses competitors’ strengths and weaknesses 84.2 4.1
When one department ?nds out something important about customers or competitors,
it is quick to alert other departments 82.9 4.0
There is a lot of communication between marketing and other departments about
market developments
82.0 4.0
Marketing sta? in our establishment spend time discussing customers’ future needs
with other divisions
80.6 4.1
In this establishment, we exchange a lot of knowledge with business partners (for
example, suppliers)
76.1 3.9
Sta? members at all levels regularly report back on competitor actions 70.7 3.7
I have a single point of contact in the establishment for all the BI I need 63.1 3.5
BI responsiveness
The establishment is quick to respond to factors in?uencing its market 89.6 4.3
We consciously target customers or customer groups where we have or can develop a
competitive advantage
89.2 4.2
A high priority is placed on implementing changes to improve customer satisfaction 88.3 4.2
If a major competitor were to launch an intensive campaign targeted at our customers,
we would implement a response immediately 86.9 4.2
The establishment responds very quickly to negative customer satisfaction data 86.5 4.1
Several departments get together periodically to plan a response to changes in our
business environment
86.5 4.1
The establishment often makes use of information that states customer preferences 83.3 4.1
Our establishment uses BI to gain a competitive edge 80.2 4.0
The establishment responds quickly to changing customer requirements 79.7 4.0
(continued)
P. Venter & D. Tustin
109
Table 3 (continued)
BI and information systems
Top-2-box
%
Mean
We frequently make use of targeted opportunities to exploit competitors’ weaknesses 77.0 3.9
If customers complain, changes are made very quickly 75.2 4.0
Our business strategy drives our information systems strategy 83.3 4.0
Information systems really assist me in making better decisions 86.0 4.1
My BI requirements are always taken into consideration when IS are designed 71.6 3.7
Information technology makes it easy to get access to the BI I require 82.0 4.0
I make the most of information technology in making business decisions 83.8 4.1
Our establishment makes good use of information technology 85.1 4.1
BI and decision-makers
Top management in this establishment attaches great value to BI in making decisions 87.8 4.1
This establishment really values the collective knowledge of the individuals
working here 85.6 4.1
The activities of the di?erent divisions in this establishment are well coordinated 82.0 4.0
In our establishment, BI sta? really understand the information needs of business
decision-makers 75.2 3.9
* = negative question
With regard to the collection of BI, respondents generally felt that their
organisations were doing a lot to collect information from customers in order to
better understand their needs. They were less convinced that their organisations
conducted a substantial amount of market research (66.7% top-2-box score). The
impression is that there are many ‘informal’ surveys and considerable interaction
with customers, but less ‘formal’ market research.
Most respondents indicated that their organisations were doing a good job of
analysing BI on both customers and competitors, with a top-2-box score range of
81.5% to 88.7%.
When it came to the dissemination of BI, respondents felt that there was substantial
inter-departmental and intra-organisational sharing of BI. In particular, most
respondents (88.7% top-2-box score) suggested that they have inter-departmental
meetings at least quarterly to discuss market trends. Respondents were less convinced
that they share knowledge with business partners (76.1%), that staff members across
the board report back on competitors’ actions (70.7%) and that they have a single
point of contact for obtaining BI (63.1%).
Respondents generally felt that their organisations are quite responsive to BI
stimuli and use BI to develop a competitive advantage by addressing customer
needs and exploiting competitors’ weaknesses or reacting to competitor initiatives.
The availability and use of competitive and business intelligence in South African business organisations
110
Respondents were also fairly positive about the role of IS in supporting BI, but
were somewhat less convinced that their BI needs are considered when IS are
designed (top-2-box score of 71.6%).
With regard to BI and decision-makers, respondents were positive that top
management makes use of BI, that the knowledge of individuals is valued, and
that the activities of the business are well-coordinated. Although respondents
included members of top management, no significant differences between different
management levels were registered. Respondents were only slightly less optimistic
(75.2%) about the extent to which BI staff understand the information needs of
business users.
In order to broaden the 46-item analysis presented in Table 3, further comparisons
of the item scores were done across business size, industry sector, respondent level
and the business area in which the respondent works. This analysis indicated that
the respondent level and industry sector did not contain many statistically significant
differences, but with regard to business area and business size, some differences
were evident. These are shown in Tables 4 and 5.
Table 4: Scale item di?erences across business area
Externally
focused
functions
%
Internally
focused
functions
%
General
management
%
Pearson
chi-square
coefficient
BI overall quality
I routinely receive BI relevant to my
responsibilities without asking for it
63.9 72.6 66.7 .035
BI is usually available to me in the format
that I prefer
62.9 73.5 33.3 .002
BI collection
Our establishment does a lot of market
research
66.0 69.9 41.7 .067
*
BI analysis
This establishment has up-to-date
pro?les of key competitors
80.4 85.8 50.0 .034
BI dissemination
Senior management regularly discusses
competitors’ strengths and weaknesses
82.5 86.7 75.0 .013
BI and information systems
Our business strategy drives our
information systems strategy
82.5 87.6 50.0 .011
BI and decision makers
Top management in this establishment
attaches great value to BI in making
decisions
87.6 88.5 83.3 .023
* = di?erence at a 90% level of con?dence; all other di?erences are at a 95% level of con?dence
P. Venter & D. Tustin
111
Table 4 seems to indicate that internally focused functions are more satisfied
than externally focused functions with respect to receiving BI without asking for it,
and with respect to the format in which they receive it. This is possibly due to the
fact that most BI systems are better geared to extracting and reporting on internal
data (for example, financial results) than on external data (for example, customer
satisfaction). Furthermore, general management seems far less convinced that their
organisations do a considerable amount of market research, that they have access
to up-to-date profiles of key competitors, or that their business strategy drives their
IT strategy. Ironically, they are also slightly less convinced than other business areas
that top management regularly discusses competitors’ strengths and weaknesses, or
that they attach great value to BI in their decision-making.
Table 5: Scale item di?erences across business size
Up to 150
employees
%
151–350
employees
%
351–1000
employees
%
>1000
employees
%
Pearson
chi-square
coefficient
BI collection
Our establishment does a lot of
market research 55.1 70.7 69.8 75.5 .053
*
Sta? members at all levels regularly
report back on competitor actions 72.5 68.3 77.8 61.2 .095
Sta? members at all levels regularly
report back on customer needs 91.3 87.8 81.0 75.5 .003
BI analysis
This establishment has a good
sense of its own strengths and
weaknesses compared to its
competition
87.0 78.0 95.2 91.8 .053
*
BI responsiveness
We frequently make use of
targeted opportunities to exploit
competitors’ weaknesses 82.6 80.5 81.0 61.2 .046
* = di?erences at a 90% level of con?dence; all other di?erences are at a 95% level of con?dence
It appears from Table 5 that most differences occur in the areas of BI collection.
Here, smaller organisations (less than 150 employees) feel less confident that they
do enough market research (55.1%) compared to organisations with more than 100
employees (75.5%). This is understandable, as larger organisations would conduct
more formal market research projects. However, smaller organisations seem more
likely to receive feedback from staff on competitors and customers than larger
organisations. Furthermore, larger organisations indicated that they have a better
sense of their own strengths and weaknesses, while organisations with more than
The availability and use of competitive and business intelligence in South African business organisations
112
1 000 employees feel less confident that they are frequently launching targeted
campaigns to exploit competitors’ weaknesses.
The use of BI tools and technology
Survey respondents were also asked about the use of tools and technology that
support BI in their organisations. These results are shown in Figure 3.
Figure 3: Importance and availability of information
While there appears to be significant investment in tools and technologies
to collect, store and disseminate information, such as intranets, competitive
intelligence, market research, data warehouses and CRM, the investment in more
powerful analysis tools such as OLAP and data-mining seems to lag somewhat. As
could be expected, larger organisations tend to invest more in tools and technologies,
0 5 10 15 20 25 30 35 40 45 50
%
P. Venter & D. Tustin
113
especially those requiring substantial investments (for example, data warehouses).
Table 6 contains an outline of the tools and technologies where statistically significant
differences occurred.
Table 6: Tools and technology usage by organisation size
Tools and technologies
Up to 150
employees
%
151–350
employees
%
351–1 000
employees
%
>1 000
employees
%
Competitive intelligence 75.4 73.2 69.8 81.6
Market research 62.3 80.5 69.8 91.8
Intranet 73.9 87.8 90.5 95.9
Data warehousing 58.0 63.4 74.6 83.7
Enterprise resource planning systems 37.7 68.3 61.9 77.6
A knowledge management function 50.7 61.0 68.3 67.3
A business intelligence function 65.2 61.0 68.3 71.4
A customer relationship management
(CRM) system 62.3 73.2 69.8 73.5
Online analytical processing (OLAP) 34.8 41.5 38.1 57.1
Data query software (e.g. SQL) 43.5 61.0 52.4 65.3
Data mining tools (e.g. SAS) 30.4 39.0 33.3 34.7
Planning support software 66.7 70.7 66.7 65.3
Executive information systems
(EIS – e.g. performance dashboards) 49.3 48.8 50.8 63.3
The following findings emerge from Table 6:
• The comparatively low frequency of businesses with 350 to 100 employees
indicating that they make use of key intelligence-gathering activities such as CI
and market research is somewhat perplexing, especially when compared with
smaller businesses. This trend was also observed with respect to ERP, OLAP,
data-mining and data-query software.
• Given the current prominence of knowledge management, investment in
establishing a knowledge management function remains comparatively low.
• Overall investment in data-mining tools is low across the board.
The availability and use of competitive and business intelligence in South African business organisations
114
Conclusion
Despite the relatively high level of overall satisfaction with BI and its various aspects,
certain problem areas have been identified in this article. Firstly, when it comes to
the availability of information, it would seem that external information (such as CI)
has the largest gaps between importance and availability, despite its high importance
to decision-makers (especially those in externally focused functions). This finding is
most likely due to the historical focus of BI on internal information and the fact that
external intelligence is generally time-consuming and costly to collect and process.
Furthermore, despite the fact that large organisations have more resources available
to ensure that decision-makers have the information they need, it is worrying that
those businesses with more than 1 000 employees are the least satisfied with the BI
available to them. They also feel that they generally make less use of opportunities
pointed out by BI, and feel less satisfied with certain aspects of BI collection. In
particular, it would seem that coordination in large businesses is a problem (for
example, these businesses are finding it harder than smaller organisations to get
staff members to report back on customer needs and competitor actions).
There are some indications that those decision-makers in general management
positions and those in externally focused functions, such as marketing and strategic
planning, are not served as well by BI as their counterparts in internally focused
functional areas such as HR and operations. They are generally less satisfied with the
availability of certain categories of information, most notably external information
categories. They are also less satisfied than other categories with certain aspects
related to the quality of BI as well as various aspects of BI collection, analysis and
dissemination. General managers (who are mostly in top management in secondary
and tertiary sector organisations) are far less satisfied with the quality of BI available
to them than any other business area. Again, the most obvious explanation for this
is the historical focus of BI on internal information (for example, financial data and
employee records). In addition, internal data are readily available and comparatively
easy to report on. External information requires time, effort and comparatively high
cost to collect, store and make available to decision-makers.
New technologies such as ERP, CRM and data warehousing have seemingly
attracted substantial investment. At the same time, intelligence collection functions
such as CI and market research enjoy high prominence. In addition, relatively
high proportions of respondents indicated that they use BI functions and planning
support software. Despite all of this, businesses seem not to have invested to the
same extent in sophisticated analysis tools.
Overall, decision-makers seem to be relatively happy with BI and the way in
which it is used in their organisations. However, BI quality is influenced by the fact
P. Venter & D. Tustin
115
that decision-makers feel that they often have to process it before it becomes useful
to them, and that it is not proactively available, when they need it and in the format
that they require. This is especially true of general managers and externally focused
functions.
From the research, three key opportunities for future research emerge, including:
• Factors other than business size, industry and decision-maker position play a
role in the way in which BI is deployed in the organisation (for example, cultural
issues). There is an opportunity to explore this further through qualitative
research.
• Further research is required on measuring the value of BI in businesses.
• Finally, research on the integration of BI and knowledge management in the
establishment can enhance the understanding of an emerging field.
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doc_922288955.pdf
Business intelligence (BI) plays a critical role in providing actionable intelligence to enable good business decision-making.
88 Southern African Business Review Volume 13 Number 2 2009
The availability and use of competitive and
business intelligence in South African business
organisations
P. Venter & D. Tustin
A B S T R A C T
Business intelligence (BI) plays a critical role in providing actionable
intelligence to enable good business decision-making. International
research shows clear evidence of the bene?ts of implementing sound
BI practices. However, within a South African business context, an
understanding of the practice, impact and bene?ts of BI is only partly
addressed by existing research. Consequently, this article presents
the most salient ?ndings of a recent BI study, which was one of the
few such studies that have been conducted in South Africa in the
21st century. Although the discussion re?ects fairly high general
satisfaction levels with BI among South African businesses, some
problems related especially to external BI dimensions are highlighted.
An equally important and major concern raised by the article is the
apparent lack of companies capitalising on BI opportunities and
coordinating BI functions e?ectively. Of concern at the general
management level, in particular, are the low satisfaction levels with
BI quality, as well as various aspects of BI collection, analysis and
dissemination. Despite the fact that businesses use BI functions and
planning support software, the survey ?ndings reveal insu? cient
investment in sophisticated BI analysis tools.
Key words: business intelligence, competitive intelligence, marketing intelligence,
business intelligence systems
Prof. P. Venter is at the Graduate School of Business Leadership, University of South Africa, and Prof. D. Tustin is
at the Bureau of Market Research, University of South Africa. E-mail: [email protected]; [email protected]
P. Venter & D. Tustin
89
Background
It would seem that there is no commonly accepted term for referring to internal and
external intelligence required for business decision-making. Market (or marketing)
intelligence, competitive intelligence, business intelligence and other terms are
all used at various times to describe more or less the same concept. Hannula and
Pirttimäki (2003: 593) define business intelligence (BI) broadly as “organized
and systematic processes which are used to acquire, analyse and disseminate
information significant to their business activities”. This definition is similar to
definitions commonly used for competitive intelligence (CI) (for example, Viviers,
Saayman, Muller & Calof 2002: 28; Wright, Pickton & Callow 2002: 350–351), with
a focus on the intelligence processes. Definitions used by Herschel and Jones (2005:
45), who adopted the Gartner definition of BI as a “set of technologies that gather
and analyse data to improve decision-making”, and Harrington (in Nemati 2005:
66), who describes BI as “a suite of tools and technologies to enhance the decision-
making process by transforming data into valuable and actionable knowledge to gain
a competitive advantage” have a stronger focus on the technology. Negash (2004:
178) suggests that BI systems combine data-gathering, data storage and knowledge
management with analytical tools to present complex internal and competitive
information to planners and decision-makers. Several characteristics of BI, in the
context of this article, emerge from these definitions:
• BI refers to both internal and external information.
• It relates to a process of adding value to information: gathering, analysis and
dissemination are all value-adding activities in the information cycle.
• The technologies used in the process of gathering, analysing and disseminating
information are an integral part of the underlying processes.
• The goal of BI is to support management decision-making.
Understanding why BI is important to organisations becomes clear when the
concept of market orientation is examined. The marketing concept is a commonly
accepted notion, namely that if you satisfy your customers’ needs, you will attain
organisational objectives. The marketing concept manifests in organisations as
market orientation (Shoham, Rose & Kropp 2005: 436, citing Deng & Dart 1994;
Walker, Mullins, Boyd & Larréché 2006: 12–13). Shoham et al. (2005: 436) describe
market orientation as the firm’s ability to anticipate, react to and capitalise on
environmental changes, leading to superior performance. BI therefore plays a
critical role in providing actionable intelligence to enhance market orientation.
The availability and use of competitive and business intelligence in South African business organisations
90
Various studies have been conducted over time to establish the impact of market
orientation on performance. For example Kara, Spillan and DeShields (2005) found
a positive correlation between market orientation and the performance of small
service businesses in the USA, while Aldas-Manzano, Küster and Vila (2005) found
a positive relationship between market orientation and certain aspects of innovation
in Spanish firms. A meta-analysis conducted by Shoham et al. (2005) concludes
that market orientation (and by implication, BI) positively affects organisational
performance and behaviour.
Searches of online databases and journals suggest that most of the South African
research published since 2000 focused on the South African CI environment
and practices in various contexts (for example Begg & Du Toit 2007; Brummer,
Badenhorst & Neuland 2006; De Pelsmacker et al. 2005; Viviers, Saayman & Muller
2005; Viviers & Muller 2004, 2005; Du Toit 2003; Viviers, Muller & Du Toit 2005;
Viviers, Saayman & Muller 2002; Viviers, Saayman, Muller & Calof 2002). Sewlal
(2004) investigated the effectiveness of the web as a CI tool. These studies generally
focused on the competitive dimension.
With regard to the application of BI technology, O’Brien and Kok (2006)
reported on the potential of BI to produce higher profits in the South African
telecommunications industry, while other research focused mainly on specific
subsets or applications of BI, for example online analytical processing (OLAP)
(Hart & Porter 2004), data marts (Ponelis & Britz 2003) and data mining (Hart 2006;
Hart, Davies, Barker-Goldie & Theron 2002). Venter (2005) explored the reasons
for success and failure of BI systems, and Conradie and Kruger (2006) investigated
the issue of information quality in BI.
Against this background, a broad research investigation of how BI is practised in
South Africa is timely. More specifically, this paper examines the BI needs, practices
and usage in South African business organisations.
Purpose of the research
The purpose of the research was to conduct a broad overview of the BI practices and
preferences of decision-makers in South African organisations. More specifically,
the study focused on the following research objectives:
• To determine BI requirements and availability
• To assess BI practices in business organisations over a range of industry sectors
and managerial functions
• To determine the usage of BI and CI technologies and methods
P. Venter & D. Tustin
91
• To determine the overall satisfaction with BI and the contribution BI makes to
decision-making in the organisation.
Literature review
Many organisations are faced with unprecedented growth in the sheer amount
of internal and external data available to them. In many instances, organisations
create information systems to deal with business requirements as these develop,
often leading to many disparate systems. As a result, many organisations end up
with voluminous data about their business but relatively little business knowledge
(Harrington, in Nemati 2005: 66). This situation is a direct result of the lack of BI.
In essence, BI provides a means for extracting information from the clutter that
would be useful for reporting and decision-making purposes. Not surprisingly, the
information technology (IT) industry coined the phrase ‘business intelligence’,
popularised by Howard Dresner, a Gartner Research Fellow (circa 1989) to describe
the concepts and methodologies designed to improve decision-making in business
through the use of facts and fact-based systems (Chou, Tripuramallu & Chou 2005:
344).
While the notion of BI has always been inclusive of external sources of
information (for example, competitive information) and unstructured information,
much of the focus during the early years has been on integrating and extracting
structured internal data, for example, data from customer relationship management
(CRM), point-of-sale or billing systems. It could therefore be argued that BI has not
been entirely successful in integrating internal and external data (see, for example,
Cody, Kreulen, Krishna & Spangler 2002).
Components of BI
Figure 1 presents a schematic overview depicting the main components of BI. The
components of BI are discussed in more detail in the following section, after which
information systems (IS) support for BI is discussed.
It is clear from Figure 1 that BI is obtained in the form of structured and
unstructured data from both internal and external sources. Internal sources typically
comprise legacy systems (a term commonly used to describe historical systems that
are still used because the organisation would not, or cannot, redesign them) as well
as various operational systems, such as point-of-sale systems, online transaction
processing (OLTP) systems and customer relationship management systems. Most
internal data are structured or semi-structured.
The availability and use of competitive and business intelligence in South African business organisations
92
Figure 1: Components of business intelligence
External intelligence is typically obtained through competitive intelligence or
market intelligence processes that produce mostly unstructured information about
competitors and customers from primary and secondary sources. In addition,
macro-environmental data from environmental scanning processes could also be an
input into BI systems. Research conducted by Lackman, Saban and Lanasa (2000)
suggests that the most useful primary sources of external intelligence are customers,
manufacturers, dealers and distributors, research and development, the sales force,
physical evidence (for example, a product or prototype) and market research projects.
Several studies have indicated that members of staff are the most critical primary
source of intelligence (for example, Wright & Calof 2006).
The data and information obtained internally and externally from various
disparate sources are usually stored centrally and made available in a format that
P. Venter & D. Tustin
93
allows easy extraction of data. This process could make use of technologies such as
intranets, data warehouses or data marts (subsets of data with a specific functional
focus). Decision-makers or their ‘agents’ (which could be a BI analyst) can extract
data from the central data repositories in order to support decision-making. This
can be done either as reports that are created and disseminated regularly without
a specific request (for example, a weekly or monthly report with detailed sales for
each of the distribution channels) or as an ad hoc requirement, in response to which
the data repositories can be queried, and a once-off report can be compiled.
The BI process
Viviers, Saayman, Muller and Calof (2002) suggest that CI is above all a systematic
process of planning, collection, analysis, communication and process management.
The same process can be applied to BI. Against this background, the most important
process components include the following:
• planning, which suggests that the BI process is not haphazard, but rather focuses
on those issues that are of most importance to the organisation’s management;
• collection of BI from various internal and external sources and in line with the
priorities set during the planning phase;
• analysis, which is generally accepted as the phase where true intelligence is
created; here, ‘raw’ information is converted into actionable intelligence on
which strategic and tactical decisions can be based; and
• communication, which is the phase during which the actionable intelligence is
disseminated to decision-makers to act.
One of the key challenges for CI is to create the process and structures to enable
the organisation to execute these phases as effectively and efficiently as possible.
Walker et al. (2006: 13) suggest that the following are examples of such procedures
and structures:
• more detailed environmental scanning;
• continuous, real-time information systems;
• obtaining feedback from, and doing joint planning with, key suppliers and
customers;
• decentralising strategic decision-making;
• encouraging entrepreneurial thinking among lower levels of management; and
• using interfunctional management teams to analyse issues and develop strategic
initiatives outside the formal planning processes.
The availability and use of competitive and business intelligence in South African business organisations
94
BI and organisational culture
It is evident from the previous discussion that there is a strong need for organisational
awareness and market orientation in the organisation to facilitate the BI process as
effectively as possible. Meehan (1999) concludes that virtually all companies are
convinced of the importance of market intelligence and are indeed spending much
time and effort on the rhetoric of ‘being customer focused’. Most companies are also
generating considerable market intelligence. However, a true market orientation
requires more than rhetoric and the mere existence of information. In this regard,
Meehan (1999) suggests the following as important elements in becoming truly
responsive and creating continuous learning about the market (in other words,
being truly market oriented):
• close customer contact to the extent that customer needs dominate the thinking
of all employees;
• measurement and reward systems that are linked to customer satisfaction; and
• leadership (in other words, top management support and commitment).
In summary, the foregoing discussions reflect an organisational culture that is
supportive of customer focus and a learning organisation that shares information
and learning across the organisation. Other guidelines to becoming more market
oriented (in other words, developing a culture that is conducive to BI) are provided
by Hayden (1993: 33–46), Slater and Narver (1994: 25–27), Slater and Narver
(1995: 71) and Herschel and Jones (2005). These guidelines include the following:
• Educate and gain the commitment of top management to a culture of market
orientation. This would also ensure buy-in throughout the organisation. The
views that CEOs hold and how they reward new ways of learning or using BI can
be crucial to the success of a BI programme.
• Focus on a strong, open culture in which BI and knowledge are exchanged and
such exchanges are rewarded. In such a culture, trust is crucial. As Hayden
(1993: 37) points out, a strong, open culture leads to relatively uniform attitudes
and behaviour with an external focus. In this regard, some practical guidelines
for establishing such a culture include the following:
— understanding the philosophy of marketing and internal marketing
throughout the organisation;
— using marketing research (as opposed to simply generating it);
— recognising the value of implementing market segmentation for the
organisation;
P. Venter & D. Tustin
95
— working with suppliers to incorporate customer benefits into product and
service specifications;
— making customer benefits part of contractual deliverables alongside financial
control and activity (in other words, customer benefits provided need to be
measurable);
— empowering all levels of consumers by providing them with a way to
communicate with the organisation;
— selecting and rewarding staff on measurable, market orientation-based
criteria;
— taking a marketing approach to strategic planning by making the market
and customer focus the driving force of strategic planning;
— devolving management for service provision by bringing the managers closer
to the customers – this may imply a flattening of traditional service provision
structures; and
— investing in public relations for key stakeholders.
Because of its external focus and interactive nature, marketing in the organisation
plays a vital role in creating an organisation that thrives on generative learning
(in other words, the willingness to question long-held assumptions about its own
beliefs). This in turn creates the most sustainable platform for organisational
survival. In this, the potential role of market orientation as a philosophy based on
learning, and the sharing of BI should be obvious.
BI technologies
Although a detailed technical discussion of BI technologies falls outside of the scope
of this article, the following section serves to identify and put into context some
commonly accepted technologies that support BI. Information technology (IT) in
the form of hardware and especially software plays a key role in ensuring that BI is
gathered, stored, analysed and presented in a simple, useful manner. The software
promotes business performance management and assists in making more informed
business decisions by making accurate, current and relevant information available
as required by managers. Figure 2 outlines the most common IS support elements
for BI.
A brief explanation of the most pertinent technologies reflected in Figure 2 is
presented in the next sections.
The availability and use of competitive and business intelligence in South African business organisations
96
Sources: Chou et al. (2005: 346), Dearstyne (2006), Metaxiotis, Ergazakis, Samoulidis & Psarras
(2003); Daniel, Wilson & McDonald (2003)
Figure 2: Information systems support for business intelligence
Information systems and sources of internal data
Information systems and sources of internal data include the following:
• Legacy systems are systems that are historical and possibly ‘outdated’, but for some
reason are still being used by the organisation (for example, the system may be
too costly to redesign).
P. Venter & D. Tustin
97
• Enterprise resource planning (ERP) systems are operational systems that have been
developed over years to ‘run a business’ and generate operational information
The focus of ERP is typically supply chain activities (Daniel et al. 2003: 839).
• Customer relationship management (CRM) systems are regarded as the marketing
equivalent of ERP systems and serve to integrate the customer-facing functions
such as marketing, sales and customer service (Daniel et al. 2003: 839).
• Online transaction processing (OLTP) refers to those systems that facilitate and
manage transaction-oriented applications, for example, a bank’s automated
teller machines (ATMs).
• Clickstream data is the record of an internet user’s ‘virtual trail’ that is left while
surfing the Internet. It includes details of activity on the internet, for example,
every website and every page of every website visited. These data are potentially
valuable to internet marketers and advertisers (www.webopedia.com).
Information systems and sources of external data
Both Dearstyne (2006) and Daniel et al. (2003) argue that web activities could be
better utilised for BI purposes. Dearstyne (2006) argues that weblogs (blogs) are
company records and should be properly managed as such, making these a potential
input for BI. Daniel et al. (2003) suggest that the internet is a potential source of
new ideas, for example, through internet-based focus groups or other discussion
forums. Daniel et al. (2003) further suggest that the aggregation and analysis of
market research and research and development projects and findings are further areas
that require IS support.
Integration and storage of data
Some businesses use data warehouses because they are a logical collection of
information gathered from various operational databases for the purpose of creating
business intelligence. The purpose of a data warehouse is to provide rich, timely,
clean and well-structured information to BI analysis tools (Chou et al. 2005: 344).
Similarly, data marts are small-scale data warehouses designed to meet a specific
function or department’s BI needs. (Chou et al. 2005: 347). A further tool is an
intranet, which is a version of the internet confined to a specific organisation and
is used to aggregate and disseminate information of interest to the members of the
organisation. Finally, knowledge management (KM) is also widely implemented.
KM involves “a systematic process of finding, selecting, organizing, distilling and
presenting information in a way that improves an employee’s comprehension in a
specific area of interest. KM helps an organisation to gain insight and understanding
The availability and use of competitive and business intelligence in South African business organisations
98
from its own experience. Specific KM activities help focus the organisation on
acquiring, storing and utilizing knowledge for such things as problem solving,
dynamic learning, strategic planning and decision making” (Herschel & Jones 2005:
45).
Data extraction
Query and reporting tools are the BI tools used to extract targeted information either
on an ad hoc basis (query) or as regular reports in a specific predetermined format.
In turn, online analytical processing (OLAP) is characterised by the fast, dynamic and
multidimensional analysis of aggregate data (for example, from a data warehouse),
and the ability to perform complex modelling with the extracted data to support
managerial decision-making (Hart & Porter 2004: 47). Hart and Porter (2004)
suggest that OLAP conforms to five characteristics:
• fast, referring to OLAP’s goal of delivering user responses in five seconds or less;
• analysis, meaning the system’s ability to handle any relevant business or statistical
analysis for a given user;
• shared, meaning the ability of the system to enable concurrent shared use;
• multidimensionalilty, referring to the provision of a multidimensional, conceptual
data view and supporting multiple data hierarchies; and
• information, meaning all data and calculated information required by the user.
A further useful tool is data mining, which is an analytical process designed to
explore data (usually large amounts of data that are typically business or market
related) in search of consistent patterns and/or systematic relationships between
variables, and then to validate the findings by applying the detected patterns
to new subsets of data. Hart, Davies, Barker-Goldie and Theron (2002: 41) cite
the following definition of data-mining by Bradley: “an information extraction
activity whose goal it is to discover hidden facts contained in databases, using a
combination of machine learning, statistical analysis, modeling techniques and
database technology, which infers rules that allow the prediction of future results”.
The ultimate goal of data-mining is prediction.
Hess, Rubin and West (2004) also advocate the use of geographical information
systems (GIS) as a decision-support system for marketing. By extension, GIS is also
a useful BI tool, as Hess et al. find that one of its strengths is its ability to integrate
information from disparate sources and span multiple decision domains. Finally,
operational executive information systems (OEIS) refer to ERP data summarised in
P. Venter & D. Tustin
99
the form of charts, tables and reports for the purposes of management (Daniel et al.
2003: 839) and data extraction.
Applications
Planning and decision support tools refer to a variety of tools in several categories that
may be used to support the planning and decision-making processes in organisations.
This may include, for example, simulation tools and planning templates (Daniel et
al. 2003: 839). Furthermore, artificial intelligence (AI) is a category of technology
that simulates human thinking patterns. Metaxiotis et al. (2003) identify three main
categories of application of AI, namely:
• Expert systems are computer systems with a well-organised body of knowledge
that emulates expert human decision-making within an established set of rules.
• Artificial neural networks (ANN) simulate the working of the human brain,
using a large number of interconnected ‘neurons’ to allow a computer system to
‘learn’ by example. One drawback of ANN is that it can only use data that are
numerically presented.
• Intelligent agents are computer systems in some specified environment that are
able to take autonomous action in order to meet design objectives. In the process,
agents act autonomously, can reason about themselves and can be mobile.
The theoretical foundation presented in the literature overview provided a
general overview of BI and BI systems. Findings resulting from this exploratory
phase motivated the study to explore the means in which BI is understood and
practised by South African organisations. The outcome of the research findings and
methodology used to collect data from a sample of 222 medium to large organisations
in South African are discussed in the following sections.
Research methodology
The research study was mainly exploratory and descriptive in nature, with the
objective of providing an overview of the state of BI usage and needs in South
Africa. The study utilised a quantitative survey methodology. Questionnaires were
administered by personal interview. The first step was to design the questionnaire,
and the following research items were included:
• Company and respondent particulars (for example, the size of the business and
core business activity).
The availability and use of competitive and business intelligence in South African business organisations
100
• BI requirements and availability. This section focused on a range of business
intelligence requirements and needs. This included information types from
the macro-environment, the market environment and internal environment.
Firstly, the importance of 12 business intelligence requirements was measured.
Concomitantly, the availability of these BI items to decision-makers was
recorded. Finally, the overall satisfaction with the quality of BI was measured by
the research model.
• BI practices and processes. This section contained 46 items measured on a five-
point Likert scale, with 1 representing ‘totally disagree’ and 5 representing ‘totally
agree’. This section was used to measure BI practices and processes within the
organisation.
• BI tools and functions. Various BI tools and functions were listed, and respondents
had to indicate which were used in their organisations.
• Organisational functions. Finally, a number of organisational functions and the
extent to which these functions benefit from BI were investigated in the research
model.
The next step was to identify a sampling frame and to draw a sample. In the
absence of a single comprehensive sampling frame of business intelligence users,
a list of business organisations with the potential for business intelligence use was
constructed with the assistance of the University of South Africa’s Bureau of Market
Research (BMR) and used for interviewing purposes. Personal interviews were
conducted with respondents (business decision-makers) from various business areas,
targeting businesses with more than 100 full-time employees. The main reason for
excluding smaller businesses was that BI is generally more formal and organised in
larger organisations. A total of 222 usable responses (from business intelligence users)
were obtained from 155 sample units (businesses), with a maximum response of two
business intelligence users (from different departments) per business. Participating
businesses were mainly based in Gauteng (65.8%), while 14.0% were located in the
Western Cape and 13.5% in KwaZulu-Natal. Respondents represented a range of
management levels and business functions (as will be discussed).
To support comparative analysis, the research model design included four
different research variables, which are discussed as follows:
• It is commonly accepted in management theory that the designation of the
respondent plays a role in his/her information needs and usage. For example,
top managers are theoretically more externally focused (and subsequently have
a greater need for external information) than junior managers. In this research
study, the comparison was mainly between top management, namely directors
and senior managers, who comprised 51.8% of the sample, and middle managers
P. Venter & D. Tustin
101
(37.4%). The remaining 10.8% of the sample (junior managers and functional
specialists) were excluded from this analysis.
• The size of the business could also have an impact on the respondent’s BI needs
and practices. Larger businesses generally have more formalised BI processes
and practices than smaller organisations. In this analysis, businesses with
between 100 and 150 employees (31.1%), 101 to 350 employees (18.5%), 351 to
100 employees (28.4%) and more than 1 000 employees (22.1%) were compared.
• The business or functional area also determines the needs for BI and the way
in which it is used. For example, externally focused functions such as sales and
marketing should theoretically have a greater need for external information than
more inward-looking functions such as operations. For this research study, the
following categorisations were used:
— externally focused functions (including sales, marketing and strategic
planning) (43.7% of respondents);
— internally focused functions (including operations, IT, human resources and
finance) (47.4% of respondents); and
— general management (5.4% of respondents).
• It could also be argued that the industry or sector within which a business operates
determines the need for and usage of BI. For example, industries experiencing
volatile change may have different BI needs from industries that are ‘stable’. In
this analysis, the following sectors or industries were compared:
— primary sector (agriculture and mining) (6.8%);
— secondary sector (manufacturing, utilities, construction, transport and
communication) (55.9%); and
— tertiary sector (wholesale, retail, hotels and restaurants, financial and real
estate services, community and personal services) (36.6%)
The discussion of the research findings in this article is devoted largely to
analysis of the research findings according the comparative criteria that have been
highlighted and are discussed in the following sections.
Research ?ndings
BI requirements and availability
The research model was designed to measure the importance and availability of
various categories of information, as will be outlined:
The availability and use of competitive and business intelligence in South African business organisations
102
• macro-environmental information (economic trends, technological trends, social
trends and customer demographics and lifestyle);
• market environment information (direct customer feedback, competitor
intelligence, sales forecasts, information on regulatory bodies and information
on potential business partners); and
• internal information (internal financial information, analysis of sales data and
operational performance data).
Using these categories, respondents were asked to rate the importance of
each type of information and its availability within the organisation. In addition,
respondents were requested to indicate their overall satisfaction with BI within the
organisation. The outcome of these research findings are shown in Table 1 using
both non-parametric and parametric statistical analysis approaches.
Table 1: Comparison of the importance and availability of information categories
a.
Importance
(top-2-box %)
b.
Availability
(top-2-box %)
c.
Gap
(a–b)
d.
Importance
(mean)
e.
Availability
(mean)
f.
Statistical
significance
of d–e
Direct customer feedback 85.6 73.9 11.7 4.27 3.63 .000
Sales forecasts 83.8 71.6 12.2 4.21 3.67 .003
Operational performance
data 83.3 78.8 4.5 4.17 4.02 .153
Competitor intelligence 81.1 63.5 17.6 4.11 3.99 .000
Analysis of sales data 81.1 73.0 8.1 4.09 3.91 .271
Economic trends 75.2 63.5 11.7 3.95 3.65 .000
Internal ?nancial
information 75.2 72.1 3.2 3.99 4.01 .264
Technological trends 74.8 64.0 10.8 3.87 3.68 .009
Information on regulatory
bodies 69.8 52.7 17.1 3.86 4.09 .000
Customer demographics
and lifestyle 69.4 61.3 8.1 3.80 3.45 .017
Information on potential
business partners 61.3 51.8 9.5 3.95 3.55 .026
Social trends 54.1 53.6 0.5 3.52 3.70 .333
Notes:
n = 222
Signi?cance smaller than 0.05 (shaded areas) indicates a di?erence between means signi?cant at a 95% level of
con?dence.
Table 1 compares only top-2-box scores (ratings of 4 and 5 on the five-point Likert
scale). The list reflected in the table is ordered according to the top-2-box scores based
P. Venter & D. Tustin
103
on the importance ratings of respondents. From the first two columns, a ‘gap’ was
computed reflecting the difference between the top-2-box scores for importance and
availability by information type. For comparison purposes, means (average scores)
for the same variables were calculated, and a t-sample test analysis approach was
used to firstly compare the mean scores of importance and availability of information
and finally to measure any statistically significant differences between the variables.
From a statistical point of view, it should be noted that, due to the nature of ordinal
data, parametric statistical analysis should not be the primary analysis approach
followed, although the findings from the use of parametric statistical analysis in this
instance mirrored the findings from non-parametric analysis.
The following results are evident from Table 1:
• The five most important categories of information are dominated by information
from the market environment, such as direct customer feedback, sales forecasts,
competitor intelligence and analysis of sales data. Operational performance data
(internal environment) were also identified as critically import. With the exception
of economic and technological trends, information on the macro-environment
was not considered to be as important as other categories of information.
• The biggest gap between the importance and availability of information is showed
for market environment information. In this regard, competitor intelligence
(17.6%), information on regulatory bodies (17.1%) and sales forecasts (12.2%)
lead the way.
• Statistically significant differences between importance and availability (t <
0.05) were recorded for all variables except operational performance data,
analysis of sales data, external financial information and social trends. In relative
terms, these information categories are thus as important as they are available
among organisations. For the information categories reflecting a statistically
significant difference between importance and availability (t < 0.05), six reflect
a desire for improved information. Categories where mean importance scores
exceed availability scores, and statistically significant differences between means
scores are evident, include direct customer feedback, sales forecasts, competitor
intelligence, economic and technological trends and information and regulatory
bodies. Ultimately, these categories reflect essential future information and BI
demands of South African companies.
In considering the responses to the question regarding the overall quality of BI
within South African organisations, only a few respondents rated this as ‘excellent’
(9.9%). However, 51.8% rated BI quality as ‘very good’, suggesting a relatively
high level of overall satisfaction with a mean score of 3.63. This finding compares
The availability and use of competitive and business intelligence in South African business organisations
104
favourably with that of Venter (2000: 233), who reported a mean score of 2.5 on the
overall perceived quality of marketing intelligence among South African marketing
decision-makers.
In order to further broaden the discussion, the next section presents the research
findings across business size, business area, management level and sector. To
determine the presence of statistically significant differences, the analysis applies a
chi-square test for the top-2-box scores (see Table 2).
In comparing the survey findings across organisation size, organisations
with between 150 and 350 employees seemed to express a lower need for certain
categories of information (CI and information on potential business partners).
Similarly (and perhaps for the same reasons), they seemed to be more satisfied
than other cohorts with the availability of internal financial information. Also, and
almost paradoxically, they are not particularly satisfied overall with the quality of BI
available to them (56.1%). Large businesses seemed to be less satisfied than other
cohorts with the BI available to them (49%). When compared by company size,
Table 2 shows statistically significant differences only for the importance of CI. In
fact, businesses with 151 to 350 employees regard CI as far less important when
compared to other business categories.
Considering the fact that tertiary sector businesses (mostly services and trade)
typically have more direct contact with end-users, it is not a surprising finding
that they expressed a higher relative need for information that would help them
understand customer behaviour better (for example, social trends, customer
demographics and lifestyle, and the analysis of sales data). The importance of social
trends, and customer demographics and lifestyle both show statistically significant
differences across economic sectors, with the primary and secondary sectors
recording much lower scores for these items than the tertiary sector. Similarly, and
perhaps due to the greater complexity of service businesses and the measurement
of service delivery, tertiary sector businesses seem to be less satisfied with the
availability of operational performance data.
Counter-intuitively, middle management respondents attached a higher
importance to some categories of macro-environmental data (economic and
technological trends), while top management respondents regarded the analysis of
sales data as relatively important. Middle managers were somewhat more satisfied
with the availability of information on technological trends and sales forecasts than
middle managers.
In considering the different business areas, externally focused functions (such
as sales and marketing) and general management expressed a relatively high need
for information on the market environment, especially customers (customer demo-
P. Venter & D. Tustin
105
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The availability and use of competitive and business intelligence in South African business organisations
106
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P. Venter & D. Tustin
107
graphics and lifestyle, as well as direct customer feedback). General managers
attached less importance to sales forecasts, which arguably constitute a more tactical
category of information. In several categories of information, general managers
were comparatively less satisfied with the availability of information. Similarly, they
were also less satisfied than other business areas with the overall quality of BI. This
may be indicative of a BI quality problem experienced at executive level.
The key findings resulting from the foregoing discussion (see Table 2) suggest
that there are some gaps between the importance and the availability of certain
important categories of information required for decision-making. There are also
some significant differences in the importance and availability of certain categories
of information across respondent and organisation characteristics that may signify
unmet BI needs.
In general, decision-makers seem to be moderately satisfied with the overall
quality of the BI available to them, but there does seem to be a significant proportion
of directors (60%) and general managers (49%) that are less satisfied than other
management categories. This is a potential indication of BI quality problems at
executive level.
The application of BI in the business
The application of BI in the business was measured in the survey research by using
46 different items, which covered the following areas:
• BI quality: accuracy, timeliness and right format;
• the BI process: collection, dissemination and analysis;
• responsiveness to BI: the extent to which BI is used;
• BI and information systems (IS): the extent to which IS support BI; and
• BI and decision-makers: the extent to which decision-makers value BI and apply
it in decision-making.
The outcome of the research findings related to these items is analysed in Table
3. The table indicates the top-2-box scores and means for each item (statement), as
well as the corresponding area category (as already outlined).
When it comes to overall BI quality, the results depicted in Table 3 suggest that
most decision-makers are fairly satisfied with the accuracy of BI (top-2-box score
of 83.3%). However, they were less satisfied with the timeliness of BI, receiving BI
proactively, and the format in which they received it. In particular, they felt that they
often had to process BI before it was useful to them.
The availability and use of competitive and business intelligence in South African business organisations
108
Table 3: The application of BI in the organisation
BI and information systems
Top-2-
box %
Mean
BI overall quality
In our establishment BI is generally accurate 83.3 4.0
BI is usually available to me by the time I need it 69.8 3.7
I routinely receive BI relevant to my responsibilities without asking for it 68.5 3.7
BI is usually available to me in the format that I prefer 66.7 3.7
I often have to process BI before I can make decisions* 81.1 4.0
BI collection
We meet with key customers at least once a year to ?nd out what products or services
they would need in future 84.2 4.1
The establishment has a structured programme to obtain the feedback needed to
understand customers
83.3 4.1
We survey end-users at least once a year to assess the quality of our products/
services
82.4 4.2
Our establishment does a lot of market research 66.7 3.7
BI analysis
We are constantly creating new knowledge about our business 89.2 4.1
This establishment has a good sense of its own strengths and weaknesses compared
to its competition
88.7 4.1
The establishment regularly analyses data on customer satisfaction 86.5 4.1
We periodically review the likely e?ect of changes in our environment on customers 83.3 4.1
The establishment studies underlying trends or patterns in customer behaviour 82.9 4.0
Customer analysis is a key strength of this ?rm 82.9 4.1
This establishment has up-to-date pro?les of key competitors 81.5 4.0
BI dissemination
We have interdepartmental meetings at least once a quarter to discuss market trends
and developments
88.7 4.3
Sta? members at all levels regularly report back on customer needs 84.2 4.1
Senior management regularly discusses competitors’ strengths and weaknesses 84.2 4.1
When one department ?nds out something important about customers or competitors,
it is quick to alert other departments 82.9 4.0
There is a lot of communication between marketing and other departments about
market developments
82.0 4.0
Marketing sta? in our establishment spend time discussing customers’ future needs
with other divisions
80.6 4.1
In this establishment, we exchange a lot of knowledge with business partners (for
example, suppliers)
76.1 3.9
Sta? members at all levels regularly report back on competitor actions 70.7 3.7
I have a single point of contact in the establishment for all the BI I need 63.1 3.5
BI responsiveness
The establishment is quick to respond to factors in?uencing its market 89.6 4.3
We consciously target customers or customer groups where we have or can develop a
competitive advantage
89.2 4.2
A high priority is placed on implementing changes to improve customer satisfaction 88.3 4.2
If a major competitor were to launch an intensive campaign targeted at our customers,
we would implement a response immediately 86.9 4.2
The establishment responds very quickly to negative customer satisfaction data 86.5 4.1
Several departments get together periodically to plan a response to changes in our
business environment
86.5 4.1
The establishment often makes use of information that states customer preferences 83.3 4.1
Our establishment uses BI to gain a competitive edge 80.2 4.0
The establishment responds quickly to changing customer requirements 79.7 4.0
(continued)
P. Venter & D. Tustin
109
Table 3 (continued)
BI and information systems
Top-2-box
%
Mean
We frequently make use of targeted opportunities to exploit competitors’ weaknesses 77.0 3.9
If customers complain, changes are made very quickly 75.2 4.0
Our business strategy drives our information systems strategy 83.3 4.0
Information systems really assist me in making better decisions 86.0 4.1
My BI requirements are always taken into consideration when IS are designed 71.6 3.7
Information technology makes it easy to get access to the BI I require 82.0 4.0
I make the most of information technology in making business decisions 83.8 4.1
Our establishment makes good use of information technology 85.1 4.1
BI and decision-makers
Top management in this establishment attaches great value to BI in making decisions 87.8 4.1
This establishment really values the collective knowledge of the individuals
working here 85.6 4.1
The activities of the di?erent divisions in this establishment are well coordinated 82.0 4.0
In our establishment, BI sta? really understand the information needs of business
decision-makers 75.2 3.9
* = negative question
With regard to the collection of BI, respondents generally felt that their
organisations were doing a lot to collect information from customers in order to
better understand their needs. They were less convinced that their organisations
conducted a substantial amount of market research (66.7% top-2-box score). The
impression is that there are many ‘informal’ surveys and considerable interaction
with customers, but less ‘formal’ market research.
Most respondents indicated that their organisations were doing a good job of
analysing BI on both customers and competitors, with a top-2-box score range of
81.5% to 88.7%.
When it came to the dissemination of BI, respondents felt that there was substantial
inter-departmental and intra-organisational sharing of BI. In particular, most
respondents (88.7% top-2-box score) suggested that they have inter-departmental
meetings at least quarterly to discuss market trends. Respondents were less convinced
that they share knowledge with business partners (76.1%), that staff members across
the board report back on competitors’ actions (70.7%) and that they have a single
point of contact for obtaining BI (63.1%).
Respondents generally felt that their organisations are quite responsive to BI
stimuli and use BI to develop a competitive advantage by addressing customer
needs and exploiting competitors’ weaknesses or reacting to competitor initiatives.
The availability and use of competitive and business intelligence in South African business organisations
110
Respondents were also fairly positive about the role of IS in supporting BI, but
were somewhat less convinced that their BI needs are considered when IS are
designed (top-2-box score of 71.6%).
With regard to BI and decision-makers, respondents were positive that top
management makes use of BI, that the knowledge of individuals is valued, and
that the activities of the business are well-coordinated. Although respondents
included members of top management, no significant differences between different
management levels were registered. Respondents were only slightly less optimistic
(75.2%) about the extent to which BI staff understand the information needs of
business users.
In order to broaden the 46-item analysis presented in Table 3, further comparisons
of the item scores were done across business size, industry sector, respondent level
and the business area in which the respondent works. This analysis indicated that
the respondent level and industry sector did not contain many statistically significant
differences, but with regard to business area and business size, some differences
were evident. These are shown in Tables 4 and 5.
Table 4: Scale item di?erences across business area
Externally
focused
functions
%
Internally
focused
functions
%
General
management
%
Pearson
chi-square
coefficient
BI overall quality
I routinely receive BI relevant to my
responsibilities without asking for it
63.9 72.6 66.7 .035
BI is usually available to me in the format
that I prefer
62.9 73.5 33.3 .002
BI collection
Our establishment does a lot of market
research
66.0 69.9 41.7 .067
*
BI analysis
This establishment has up-to-date
pro?les of key competitors
80.4 85.8 50.0 .034
BI dissemination
Senior management regularly discusses
competitors’ strengths and weaknesses
82.5 86.7 75.0 .013
BI and information systems
Our business strategy drives our
information systems strategy
82.5 87.6 50.0 .011
BI and decision makers
Top management in this establishment
attaches great value to BI in making
decisions
87.6 88.5 83.3 .023
* = di?erence at a 90% level of con?dence; all other di?erences are at a 95% level of con?dence
P. Venter & D. Tustin
111
Table 4 seems to indicate that internally focused functions are more satisfied
than externally focused functions with respect to receiving BI without asking for it,
and with respect to the format in which they receive it. This is possibly due to the
fact that most BI systems are better geared to extracting and reporting on internal
data (for example, financial results) than on external data (for example, customer
satisfaction). Furthermore, general management seems far less convinced that their
organisations do a considerable amount of market research, that they have access
to up-to-date profiles of key competitors, or that their business strategy drives their
IT strategy. Ironically, they are also slightly less convinced than other business areas
that top management regularly discusses competitors’ strengths and weaknesses, or
that they attach great value to BI in their decision-making.
Table 5: Scale item di?erences across business size
Up to 150
employees
%
151–350
employees
%
351–1000
employees
%
>1000
employees
%
Pearson
chi-square
coefficient
BI collection
Our establishment does a lot of
market research 55.1 70.7 69.8 75.5 .053
*
Sta? members at all levels regularly
report back on competitor actions 72.5 68.3 77.8 61.2 .095
Sta? members at all levels regularly
report back on customer needs 91.3 87.8 81.0 75.5 .003
BI analysis
This establishment has a good
sense of its own strengths and
weaknesses compared to its
competition
87.0 78.0 95.2 91.8 .053
*
BI responsiveness
We frequently make use of
targeted opportunities to exploit
competitors’ weaknesses 82.6 80.5 81.0 61.2 .046
* = di?erences at a 90% level of con?dence; all other di?erences are at a 95% level of con?dence
It appears from Table 5 that most differences occur in the areas of BI collection.
Here, smaller organisations (less than 150 employees) feel less confident that they
do enough market research (55.1%) compared to organisations with more than 100
employees (75.5%). This is understandable, as larger organisations would conduct
more formal market research projects. However, smaller organisations seem more
likely to receive feedback from staff on competitors and customers than larger
organisations. Furthermore, larger organisations indicated that they have a better
sense of their own strengths and weaknesses, while organisations with more than
The availability and use of competitive and business intelligence in South African business organisations
112
1 000 employees feel less confident that they are frequently launching targeted
campaigns to exploit competitors’ weaknesses.
The use of BI tools and technology
Survey respondents were also asked about the use of tools and technology that
support BI in their organisations. These results are shown in Figure 3.
Figure 3: Importance and availability of information
While there appears to be significant investment in tools and technologies
to collect, store and disseminate information, such as intranets, competitive
intelligence, market research, data warehouses and CRM, the investment in more
powerful analysis tools such as OLAP and data-mining seems to lag somewhat. As
could be expected, larger organisations tend to invest more in tools and technologies,
0 5 10 15 20 25 30 35 40 45 50
%
P. Venter & D. Tustin
113
especially those requiring substantial investments (for example, data warehouses).
Table 6 contains an outline of the tools and technologies where statistically significant
differences occurred.
Table 6: Tools and technology usage by organisation size
Tools and technologies
Up to 150
employees
%
151–350
employees
%
351–1 000
employees
%
>1 000
employees
%
Competitive intelligence 75.4 73.2 69.8 81.6
Market research 62.3 80.5 69.8 91.8
Intranet 73.9 87.8 90.5 95.9
Data warehousing 58.0 63.4 74.6 83.7
Enterprise resource planning systems 37.7 68.3 61.9 77.6
A knowledge management function 50.7 61.0 68.3 67.3
A business intelligence function 65.2 61.0 68.3 71.4
A customer relationship management
(CRM) system 62.3 73.2 69.8 73.5
Online analytical processing (OLAP) 34.8 41.5 38.1 57.1
Data query software (e.g. SQL) 43.5 61.0 52.4 65.3
Data mining tools (e.g. SAS) 30.4 39.0 33.3 34.7
Planning support software 66.7 70.7 66.7 65.3
Executive information systems
(EIS – e.g. performance dashboards) 49.3 48.8 50.8 63.3
The following findings emerge from Table 6:
• The comparatively low frequency of businesses with 350 to 100 employees
indicating that they make use of key intelligence-gathering activities such as CI
and market research is somewhat perplexing, especially when compared with
smaller businesses. This trend was also observed with respect to ERP, OLAP,
data-mining and data-query software.
• Given the current prominence of knowledge management, investment in
establishing a knowledge management function remains comparatively low.
• Overall investment in data-mining tools is low across the board.
The availability and use of competitive and business intelligence in South African business organisations
114
Conclusion
Despite the relatively high level of overall satisfaction with BI and its various aspects,
certain problem areas have been identified in this article. Firstly, when it comes to
the availability of information, it would seem that external information (such as CI)
has the largest gaps between importance and availability, despite its high importance
to decision-makers (especially those in externally focused functions). This finding is
most likely due to the historical focus of BI on internal information and the fact that
external intelligence is generally time-consuming and costly to collect and process.
Furthermore, despite the fact that large organisations have more resources available
to ensure that decision-makers have the information they need, it is worrying that
those businesses with more than 1 000 employees are the least satisfied with the BI
available to them. They also feel that they generally make less use of opportunities
pointed out by BI, and feel less satisfied with certain aspects of BI collection. In
particular, it would seem that coordination in large businesses is a problem (for
example, these businesses are finding it harder than smaller organisations to get
staff members to report back on customer needs and competitor actions).
There are some indications that those decision-makers in general management
positions and those in externally focused functions, such as marketing and strategic
planning, are not served as well by BI as their counterparts in internally focused
functional areas such as HR and operations. They are generally less satisfied with the
availability of certain categories of information, most notably external information
categories. They are also less satisfied than other categories with certain aspects
related to the quality of BI as well as various aspects of BI collection, analysis and
dissemination. General managers (who are mostly in top management in secondary
and tertiary sector organisations) are far less satisfied with the quality of BI available
to them than any other business area. Again, the most obvious explanation for this
is the historical focus of BI on internal information (for example, financial data and
employee records). In addition, internal data are readily available and comparatively
easy to report on. External information requires time, effort and comparatively high
cost to collect, store and make available to decision-makers.
New technologies such as ERP, CRM and data warehousing have seemingly
attracted substantial investment. At the same time, intelligence collection functions
such as CI and market research enjoy high prominence. In addition, relatively
high proportions of respondents indicated that they use BI functions and planning
support software. Despite all of this, businesses seem not to have invested to the
same extent in sophisticated analysis tools.
Overall, decision-makers seem to be relatively happy with BI and the way in
which it is used in their organisations. However, BI quality is influenced by the fact
P. Venter & D. Tustin
115
that decision-makers feel that they often have to process it before it becomes useful
to them, and that it is not proactively available, when they need it and in the format
that they require. This is especially true of general managers and externally focused
functions.
From the research, three key opportunities for future research emerge, including:
• Factors other than business size, industry and decision-maker position play a
role in the way in which BI is deployed in the organisation (for example, cultural
issues). There is an opportunity to explore this further through qualitative
research.
• Further research is required on measuring the value of BI in businesses.
• Finally, research on the integration of BI and knowledge management in the
establishment can enhance the understanding of an emerging field.
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