Description
For many companies, new technologies are causing information overload, leaving decision makers overwhelmed with inadequate, incorrect, inconsistent and misleading information.
Better Decision Making with
Proper Business Intelligence
Quality information is key to making quick, rational business decisions
BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 1
A
s companies focus on growth and business development, the
availability of quality information is crucial to making quick,
rational business decisions. New technologies, however, can
cause information overload, leaving decision makers buried under a
mass of irrelevant, inadequate, and inconsistent data. Some companies
manage to provide their decision makers with precise, relevant data
in an easy-to-grasp format. These companies have discovered the value
of effective business intelligence capabilities.
For many companies, new technologies are causing
information overload, leaving decision makers
overwhelmed with inadequate, incorrect, incon-
sistent and misleading information. Indeed, the
various acts of retrieving and processing this
often useless information can tie up numerous
resources. Yet there are companies that manage
to provide their decision makers with processed
and automatically consolidated raw data, presented
in an understandable, easy-to-grasp format. These
companies provide insightful information for
quick, profound decision making. What do these
companies have that the others don’t? Business
intelligence (BI) capabilities and processes.
Business intelligence is a research ?eld that
focuses on theoretical and practical aspects of
achieving a solid information basis for decision
making. This paper summarizes A.T. Kearney’s
experience in helping companies shape their data
processes to obtain the right information for
rational and quick decision making.
What Is Business Intelligence?
Business intelligence focuses on the particular ?eld
of data processing and consolidation to retrieve
information for decision making. The overarching
objective is to provide—via various solutions —
the right knowledge to the right people at the
right time. Doing this requires the right mix of
IT systems, architectures, data structures, data-
collection processes, and responsibilities for provid-
ing meaningful information. Business intelligence
has a proven impact on key performance indica-
tors (KPIs). For example:
• 60 percent of executive managers state that the
use of a performance management tool has a
positive impact on shareholder value
• Return on equity (ROE) is more than twice
as high in companies that widely use perfor-
mance management tools compared to those
that do not in the same industry
When assessing BI capabilities, there are four
levels to consider:
Reporting. Reporting is a core functionality
of BI tools as the objective is to create recurring,
standard, reports in an ef?cient and user-friendly
manner. Reports are predefned and static by
nature, generated either by request of an end-user
or refreshed periodically through an automatic
scheduler (uploaded on Intranet servers or shared
BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 3 BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 2
Three Phases of Implementation
A successful corporate BI implementation has
three phases (see ?gure 1). In implementing BI sys-
tems, it is important to begin with business
requirements, because projects that are technically
triggered usually fail.
Phase 1: De?ne the necessary KPIs on a
management dashboard. A key activity in the
?rst phase is to de?ne future reports and KPIs,
which often means eliminating some existing
reports, as many are unnecessary and do not truly
re?ect the company’s objectives (see ?gure 2).
1
Next, is assessing data availability to calculate
de?ned KPIs; a sound data basis is a key success
factor for system implementation. External tools
connecting to existing data warehouses and addi-
tional calculations should be kept to a minimum.
Also, the various layers of a BI system are evalu-
ated to de?ne which areas should be addressed
and identify speci?c parts that should be elimi-
nated (see ?gure 3 on page 4).
It is important to clarify at the beginning
which areas shall be covered by the project: Is it
a BI system for ?nance KPIs only or does it also
include supply chain management? Will the proj-
ect integrate other functional areas, departments
or even speci?c business lines within operations?
Often human resources and customer relationship
management (CRM) are the next candidates to
improve ?nance BI and integrate more of the
drives and accessible to a prede?ned group of cor-
porate users). Key functionality is reduced to data
consolidation and aggregation from various
sources in a repetitive approach (automated, ide-
ally) from trusted data sources.
Dashboards. Dashboards contain high-level,
aggregated strategic company data, inclusive com-
parable presentations, and consolidated perfor-
mance indicators. They include both static and
interactive reports with data translated into graph-
ics, charts, gauges and illustrations to simplify the
communication of complex topics. Dashboards
allow basic interactions (such as drill down, slice-
and-dice operations to “play with the data”) and
provide various levels of detail to achieve deeper
insights. However, the explanatory power of dash-
boards relies mostly on users’ interpretations.
Analysis. At the analysis level, BI systems
provide not only consolidated information that
users can detail and ?lter, but also forecasts and
trend analyses to develop new insights (based on
the raw data).
Analytics. At the top level of a BI system is
automated intelligent data analyses based on
sophisticated “fuzzy” logic and “neuro-fuzzy” sys-
tems. Based on user-friendly but powerful func-
tions, the BI system can retrieve meaningful
insights while hiding the underlying complexity
of data interpretation. “What-if ” scenarios and
simulation functionality provide advanced, tai-
lored decision-making support.
The fundamental basis of every BI system,
however, is the data base on which it operates. Basic
systems focus on corporate ?nancial data only,
while advanced systems interconnect internal and
external sources with qualitative and quantitative
data. Advanced systems process the comprehensive
data set using methods perfectly tailored to a ?rm’s
needs and condense the ?ndings into meaningful
knowledge—hiding the complexity and selecting
only the maximum amount of input necessary to
help executives make the right judgments.
The Advantages of Business Intelligence
When analyzing a business intelligence solution,
it is important to consider the business bene?ts,
including improved overall decision making and
increased ef?ciency for business reporting and
analysis. To this ?rst point, BI offers four impor-
tant prerequisites for proper decision making:
• Required information is available
• Data is consistent across organizational units
• Information can be easily analyzed using built-
in analysis functionality
• Reports are presented in a user-friendly format
A well-designed business intelligence solution
ensures that information across the organization is
available in a consistent, reliable manner. Figures
can be aggregated and compared in different
business units, assuring the validity of like-for-
like data comparisons, and that all management
reports provide operations leaders and top man-
agement with the information they need to steer
the business properly.
Essentially, BI improves effciency on both the
information technology (IT) side and the business
side of the organization. On the IT side, workers
are freed from the recurring task of creating and
changing data reports as end-users are able to create
and change their own reports. On the business
side, less time is spent in data analysis and prepara-
tion as management reports are created directly
from the BI dashboards. Not only is the data in
these reports more up-to-date and credible, but
also they are easier to read and handle. And, impor-
tantly, the information can be downloaded on
smart devices, including the iPhone and iPad. The
sidebar on page 4, What Makes a BI Leader?, offers
a short list of success factors shared by top business
intelligence organizations.
Figure 1
Three phases of a business intelligence solution
Source: A.T. Kearney analysis
Phase 1
Define key performance
indicators and level of business
intelligence to be achieved
Phase 2 Phase 3
Collect requirements, build
prototype and conduct
vendor “proof of concept”
Implement solution
and improve tool
according to release plan
Figure 2
The main tasks in Phase 1
Source: A.T. Kearney analysis
• Evaluate potential key
performance indicators
(KPIs)
• Analyze empiricial findings
related to use of KPIs
• Evaluate simple
profitability metrics
• Assess select KPIs for
appropriateness
• Compare analysis of
value-add KPIs
• Identify potential risks of
making the wrong decision
Perform qualitative
evaluation
Determine value
correlations
Analyze
risks
Make
recommendations
1
Phase 1 should always be completed fully before proceeding with the second phase, as the required reporting and the defined KPIs set the framework for tool selection.
BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 5 BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 4
business. The link to operations is more dif?cult
as KPIs from manufacturing, production or logis-
tics are fairly different from ?nance KPIs and are
often dif?cult to connect to existing KPI trees.
Even between similar business lines, KPIs are
sometimes slightly different because they repre-
sent different business models —for instance,
internal production for intermediate products or
external production for ?nal products. If the long-
term strategy is to analyze operational KPIs, this
should be addressed at the outset. Once these
questions are answered and all affected business
areas are addressed, the second phase can begin.
Phase 2: Create a design and navigation
prototype and build a “proof of concept.” Four
tasks are involved in preparation for system imple-
mentation. The result is a “proof of concept,”
designed before the comprehensive implementa-
tion begins. At this point, software vendor selec-
tion is independent of speci?c design requirements
and often driven by strategic policies or IT land-
scape requirements. Based on IT architecture
rules, a short list can be devised up-front to select
appropriate tools to ?t the company’s require-
ments, IT strategy and IT landscape (see ?gure 4).
Phase 2 is not only about collecting require-
ments regarding the functionality of a future tool
(navigation and analysis deep dives, for example)
but also about report design, dashboards and tool
functionality. One point must be stated very
clearly: A pure management “cockpit” or dash-
board cannot replace the internal or external
reporting. As a ?rst step, it can be seen as a second
channel (always available), but with a different
level of detail (management adequate). All man-
agement cockpit tools offer a reporting function-
ality used to print-out the dashboard content.
Replacing the complete paper-based internal (or
external) reporting requires signi?cant efforts as
the detailed design of every single page is outlined
up-front. Both the dashboard screen design and
the report layouts, which cover all of the depicted
content regarding historic numbers and compari-
sons, among other things, ?nally get de?ned
before the detailed concept is handed over to a
system integrator for implementation. The real-
ization of the screens and the corresponding KPI
visualization are the main drivers of the system
implementation and the testing. Therefore stabil-
ity is required.
Figure 3
Layers of a business intelligence system
Sources: Forrester, A.T. Kearney analysis
Delivery
A
p
p
s
F
o
r
m
f
a
c
t
o
r
P
S
O
Reporting
Performance
management
Support
applications
Analytics
Discovery and
integration
Data
Infrastructure Network
Report mining
DQ – cleansing, profiling EAI / SOA EII ETL / CDC
Discovery accelerators
Adapters / tool kits Accelerators / query optimization
BPM / BRE integration BAM / CEP
Operational data stores (ODS), data warehouses (DW), data marts (DM)
Integration – third party applications
Services registry and repository
Streaming DBMS Search DBMS
RDBMS
In-memory DBMS Hierarchical / XML Columnar DBMS
Multi-value RDBMS Multi-dimensional OLAP
Usage analytics Statistical analysis Web analytics
Data / text mining Guided decisions NLP Guided search
Time series OLAP Operational DSS Predictive analytics
Servers Storage
MDM
S
I
I
n
d
u
s
t
r
y
v
e
r
t
i
c
a
l
a
p
p
l
i
c
a
t
i
o
n
s
S
t
r
a
t
e
g
y
A
p
p
l
i
a
n
c
e
M
e
t
h
o
d
o
l
o
g
y
G
o
v
e
r
n
a
n
c
e
B
I
S
a
a
S
H
o
s
t
e
d
B
I
(
A
S
P
)
b
-
l
a
y
e
r
s
)
M
S
P
/
a
p
p
s
o
u
t
s
o
u
r
c
i
n
g
C
e
n
t
e
r
o
f
E
x
c
e
l
l
e
n
c
e
E
n
t
e
r
p
r
i
s
e
a
p
p
s
:
E
R
P
,
C
R
M
,
S
C
M
,
E
R
M
B
P
O
eLearning ECM Metadata-integration, repositories
Version control
Reporting: ad-hoc, analytical, production Search Geospatial
Advanced data visualization Alerts Dashboards
Collaboration Life-cycle Mgt. Localization QA
Strategy / objectives management
Metrics / KPIs Planning Scorecards
Interactive voice response, ATM, point-of-sale Portals
Desktop gadgets Office suites Mobile Disconnected
O
r
g
What Makes a BI Leader?
From our experience helping com-
panies implement their business
intelligence projects, we have found
several common characteristics or
“success factors” that differentiate
the BI leaders from the followers.
The BI leaders:
• Defne and optimize corporate
report standards
• Focus on the business not the data
• Establish a balanced scorecard
• Defne clear data dimensions and
structures
• Develop a master data manage-
ment plan
• Establish corporate data gover-
nance and clear ownership of
master data
• Use report visualization in pilots
• Leverage web technologies
• Focus on cross-organizational
efforts
• Distinguish between business-
driven and IT-driven projects
• Defne the long-term BI scope,
from the beginning
• Realize a mobile version of
business intelligence
Figure 4
The tasks in phase 2
Source: A.T. Kearney analysis
• Perform assessment
to ensure the need
for a “cockpit”
• Conduct a brief cost-
benefit analysis of the
area and other potentially
affected areas such as
procurement
• Draw up a short list
of vendors, taking into
account industry reports
and other external
information
• Assess the options from
an internal viewpoint
• Complete a list of
business requirements
and build a first simple
PowerPoint prototype
to develop a “look-and-
feel” of the final product
• Begin company-vendor
discussions
• Help the vendor understand
the client and ensure vendor
receives timely feedback so
to make quick improvements
Assessment
Vendor
selection
Requirements
and prototypes
Proof of concept
BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 7 BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 6
The proof of concept increases the developers’
understanding of the company’s requirements
before starting the real systems implementation.
In our experience, a quick prototype allows a
company to check the design of all possible pre-
selected tools and test the capability of the poten-
tial solution provider. Work packages can also be
tested to assess vendors’ innovation capabilities in
solving design questions. Finally, the ?rm’s
requirements can be tested and challenged.
Phase 3: Implementation. Implementation is
a typical IT project. However, due to high visibil-
ity and management awareness, the implementa-
tion should be fast and provide quick solutions.
A release plan ensures ?rst results are delivered
quickly, while the ?nal and comprehensive solu-
tion is created in several steps, aligned with report-
ing cycles and data availability. The ?rst release
should provide all required dashboard functions
(design, navigation and drill-down) and some of
the reporting requirements, which are detailed in
the follow-on implementation phases and can be
delivered sequentially. Typically, ?rst releases lack
the full data set. An essential activity in the BI
project is to cleanse existing data and establish
a process to record new data in a proper way,
which often requires developing the entire data
architecture, including dimensions, hierarchies
and formulas. Close interaction between system
provider and business departments (as the ?nal
users and clients of the system) is crucial to the
success of the project. The management cockpit
or dashboard ful?lls the design and functional
requirements because it provides clear visibility
to management and the necessary ease of use.
Although all required data or KPIs may not be
included in the beginning, they are provided
throughout the steps.
Governance and the CIO’s Role
Within a BI project, the corporate IT and the
CIO moderate between the different business
departments that are involved, the internal IT
group, and the software provider or implementer.
A BI project is often driven by the ?nance depart-
ment as the key user due to corporate reporting
and corporate management requirements; ?nance
de?nes the main KPIs on a corporate level and
ensures standardization across all different busi-
ness models within the ?rm.
Operational KPIs are provided by the differ-
ent operating units and standardized to ensure
that consistent content is reported to top manage-
ment. The CIO and corporate IT take over the
role of supporting KPI de?nitions by providing
information about data sources, data availability
and data quality. And they start the analysis on
how a business intelligence tool could be used to
ful?ll high-level requirements (see sidebar: Business
Intelligence: A Case Study).
Part of the project involves de?ning future
BI governance. This often means establishing a BI
Business Intelligence: A Case Study
The management team at a large
German company decided to imple-
ment a corporate-wide business
intelligence (BI) process. The com-
pany, involved in heterogeneous
businesses, started with pilot units
in its three business concerns, de?n-
ing ?nancial key performance indi-
cators (KPIs) to manage and direct
the corporation.
The management team knew
that success would depend on cor-
porate-wide de?nitions for its KPIs
so they could be cascaded down to
all business units.
The project began with develop-
ment of a basic management dash-
board that provided a visual KPI tree
to clarify the logical dependencies of
the two main KPIs —and then illus-
trating all the subsequent KPIs that
?owed from them—and how they
navigated through the organization.
Next, business-speci?c operational
KPIs were added to the dashboard,
a simulation tool was developed
to provide units with a business-
planning model to illustrate the
dependencies between KPIs, and
a BI tool-based reporting process
was designed and implemented
The IT work began during the
?nal de?nition of corporate-wide
KPIs and reporting, providing infor-
mation about the availability of exist-
ing data within the data warehouse.
This was followed by the vendor
and tool-selection process. A proto-
type was designed, and software pro-
viders were asked to use the design
and business units’ functional
requirements to develop a rough
proof of concept.
Immediately after the proof-of-
concept presentations, the vendor-
selection process was ?nalized and
implementation began. Within three
months, the company had its ?rst
release, covering main functional-
ities, dashboard design and naviga-
tion, and ?rst-reporting factors. The
release plan took into account the
main reporting cycles, and two sub-
sequent releases were scheduled
within the planned timeframe.
Soon after introduction, the
management team was delighted as
user acceptance proved stronger than
expected throughout the organiza-
tion. When asked about the success
factors, team members were quick to
cite the top two: design and ease of
navigation within the BI tool, and
on-time delivery of the major KPIs.
All in all, the company is now
dedicated to using business intelli-
gence to help steer it on a richer
and more successful course.
• Through TOOL 1 WYSIWYG
the dashboard can be handled
• Vendor 1offers functional
building blocks for the
storing of comments in the
SAP BW
• Simulations can be saved;
retraction through vendor 1’s
own functionalities into BW
backend
• Look-and-feel remains the
same
• Comments and simulation
can be executed early
• Either DataMart on machine
two or WebService on
machine one
• BOE Infrastructure for
LiveOffice and reporting tool
(phase2)
• Possible according to the
demonstration; no information
given on the interface builder;
use of all graphic types possible
• Possible according to the
demonstration
• Comments can only be used in
the machine-three environment
• Possible according to the
demonstration; simulations can
be saved and retracted into the
SAP BW
• Look-and-feel remains the same
• Comments and simulation can be
executed early
• According to vendor, it can
communicate with SAP BW 3.5
but not demonstrated
• Basic infrastructure on machine
one has to be built anew
Figure 5
Detailed analysis of BI software vendors
Source: A.T. Kearney analysis Full function
• Only static design possible;
performance critical
• Use of standard BDS
associated with
performance issues
• Generally not simulation
functionality
• Due to low performance on
comments and the illustration
of graphs, no usage possible
in phases 1 to 2
• Executed on machine
one, no export of the cube
data needed
• None
Implementation
design
Implementation
comments
Implementation
simulation
Transition from
prototype to
release I to II
Connectivity to
data
Hardware costs
Category On-board tools Vendor 1 Vendor 2
Very limited function
A.T. Kearney is a global management consulting ?rm that uses strategic
insight, tailored solutions and a collaborative working style to help clients
achieve sustainable results. Since 1926, we have been trusted advisors on
CEO-agenda issues to the world’s leading corporations across all major
industries. A.T. Kearney’s of?ces are located in major business centers
in 37 countries.
AMERICAS Atlanta | Boston | Chicago | Dallas | Detroit | Mexico City
New York | San Francisco | São Paulo | Toronto | Washington, D.C.
EUROPE Amsterdam | Berlin | Brussels | Bucharest | Copenhagen
Düsseldorf | Frankfurt | Helsinki | Kiev | Lisbon | Ljubljana | London
Madrid | Milan | Moscow | Munich | Oslo | Paris | Prague | Rome
Stockholm | Stuttgart | Vienna | Warsaw | Zurich
ASIA PACIFIC Bangkok | Beijing | Hong Kong | Jakarta | Kuala Lumpur
Melbourne | Mumbai | New Delhi | Seoul | Shanghai | Singapore
Sydney | Tokyo
MIDDLE EAST Abu Dhabi | Dubai | Johannesburg | Manama | Riyadh
& AFRICA
For information on obtaining
additional copies, permission
to reprint or translate this work,
and all other correspondence,
please contact:
A.T. Kearney, Inc.
Marketing & Communications
222 West Adams Street
Chicago, Illinois 60606 U.S.A.
1 312 648 0111
email: [email protected]
www.atkearney.com
© 2011, A.T. Kearney, Inc. All rights reserved.
A.T. Kearney Korea LLC is a separate and independent legal entity operating under the A.T. Kearney name in Korea.
BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 8
center of excellence led by the ?nance department
that includes data governance with BI system
maintenance authority. Corporate IT should be
part of the change advisory board that assesses and
evaluates change requests based on the capabilities
of the system solution, while IT maintains tech-
nology authority.
Choosing Tools and an Implementation
Partner
BI tool selection is rarely a “green ?eld” approach.
The corporate IT strategy, system landscape and
the main requirements regarding the BI level to
be achieved are all guidelines in the selection pro-
cess. Market research and analysts’ estimations
can be used as support documents, but in most
cases these analyses are too general and cannot
be adapted to meet company speci?cs. Instead,
external reports are typically used afterwards as
support information to justify the short-list ven-
dors or tools.
The software vendor and implementer are the
same in most cases, as only a few companies are
able to provide a full business intelligence suite,
connected or even integrated somehow to the
main enterprise resource planning (ERP) systems,
such as SAP or Oracle.
A company-speci?c questionnaire and evalua-
tion template allows the ef?cient gathering of key
requirements. The main questions or key evalua-
tion points should be shared in advance with the
short-listed software vendors to give them an
opportunity to prepare the tool presentation and
to answer all questions completely. The clearer the
requirements are documented and described, the
faster the selection process can be executed (see
?gure 5 on page 7).
A rough prototype—such as a PowerPoint
visual of the management cockpit to demonstrate
key navigation functions and design-related
requirements will help both sides understand the
desired outcome and manage expectations. It is
the basis for the later detailed design and concept,
containing the description of each requirement.
This and the more technical description of the
existing landscape and necessary interfaces are
the most relevant documents for the implementa-
tion and build up to the kick-off for the system-
implementation phase.
BI: A Must for Business Success
A proper BI solution is a must have in today’s
world. Companies in all industries are using BI
systems for successful decision making. These
companies beat their competition and identify
new opportunities to optimize their businesses.
They also reduce resources for manual effort and
rededicate people to analyzing data and preparing
decision memos. For companies that grasp the
true potential in business intelligence, they should
take action sooner rather than later —time, as
always, is of the essence.
Authors
Alexander Martin is a principal in the strategic information technology practice. Based in the Düsseldorf of?ce,
he can be reached at [email protected].
Robert Jekel is a consultant based in the Zurich of?ce. He can be reached at [email protected].
Edgar Simons is a consultant in the Düsseldorf of?ce. He can be reached at [email protected].
ATK.0211.172
doc_355078347.pdf
For many companies, new technologies are causing information overload, leaving decision makers overwhelmed with inadequate, incorrect, inconsistent and misleading information.
Better Decision Making with
Proper Business Intelligence
Quality information is key to making quick, rational business decisions
BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 1
A
s companies focus on growth and business development, the
availability of quality information is crucial to making quick,
rational business decisions. New technologies, however, can
cause information overload, leaving decision makers buried under a
mass of irrelevant, inadequate, and inconsistent data. Some companies
manage to provide their decision makers with precise, relevant data
in an easy-to-grasp format. These companies have discovered the value
of effective business intelligence capabilities.
For many companies, new technologies are causing
information overload, leaving decision makers
overwhelmed with inadequate, incorrect, incon-
sistent and misleading information. Indeed, the
various acts of retrieving and processing this
often useless information can tie up numerous
resources. Yet there are companies that manage
to provide their decision makers with processed
and automatically consolidated raw data, presented
in an understandable, easy-to-grasp format. These
companies provide insightful information for
quick, profound decision making. What do these
companies have that the others don’t? Business
intelligence (BI) capabilities and processes.
Business intelligence is a research ?eld that
focuses on theoretical and practical aspects of
achieving a solid information basis for decision
making. This paper summarizes A.T. Kearney’s
experience in helping companies shape their data
processes to obtain the right information for
rational and quick decision making.
What Is Business Intelligence?
Business intelligence focuses on the particular ?eld
of data processing and consolidation to retrieve
information for decision making. The overarching
objective is to provide—via various solutions —
the right knowledge to the right people at the
right time. Doing this requires the right mix of
IT systems, architectures, data structures, data-
collection processes, and responsibilities for provid-
ing meaningful information. Business intelligence
has a proven impact on key performance indica-
tors (KPIs). For example:
• 60 percent of executive managers state that the
use of a performance management tool has a
positive impact on shareholder value
• Return on equity (ROE) is more than twice
as high in companies that widely use perfor-
mance management tools compared to those
that do not in the same industry
When assessing BI capabilities, there are four
levels to consider:
Reporting. Reporting is a core functionality
of BI tools as the objective is to create recurring,
standard, reports in an ef?cient and user-friendly
manner. Reports are predefned and static by
nature, generated either by request of an end-user
or refreshed periodically through an automatic
scheduler (uploaded on Intranet servers or shared
BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 3 BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 2
Three Phases of Implementation
A successful corporate BI implementation has
three phases (see ?gure 1). In implementing BI sys-
tems, it is important to begin with business
requirements, because projects that are technically
triggered usually fail.
Phase 1: De?ne the necessary KPIs on a
management dashboard. A key activity in the
?rst phase is to de?ne future reports and KPIs,
which often means eliminating some existing
reports, as many are unnecessary and do not truly
re?ect the company’s objectives (see ?gure 2).
1
Next, is assessing data availability to calculate
de?ned KPIs; a sound data basis is a key success
factor for system implementation. External tools
connecting to existing data warehouses and addi-
tional calculations should be kept to a minimum.
Also, the various layers of a BI system are evalu-
ated to de?ne which areas should be addressed
and identify speci?c parts that should be elimi-
nated (see ?gure 3 on page 4).
It is important to clarify at the beginning
which areas shall be covered by the project: Is it
a BI system for ?nance KPIs only or does it also
include supply chain management? Will the proj-
ect integrate other functional areas, departments
or even speci?c business lines within operations?
Often human resources and customer relationship
management (CRM) are the next candidates to
improve ?nance BI and integrate more of the
drives and accessible to a prede?ned group of cor-
porate users). Key functionality is reduced to data
consolidation and aggregation from various
sources in a repetitive approach (automated, ide-
ally) from trusted data sources.
Dashboards. Dashboards contain high-level,
aggregated strategic company data, inclusive com-
parable presentations, and consolidated perfor-
mance indicators. They include both static and
interactive reports with data translated into graph-
ics, charts, gauges and illustrations to simplify the
communication of complex topics. Dashboards
allow basic interactions (such as drill down, slice-
and-dice operations to “play with the data”) and
provide various levels of detail to achieve deeper
insights. However, the explanatory power of dash-
boards relies mostly on users’ interpretations.
Analysis. At the analysis level, BI systems
provide not only consolidated information that
users can detail and ?lter, but also forecasts and
trend analyses to develop new insights (based on
the raw data).
Analytics. At the top level of a BI system is
automated intelligent data analyses based on
sophisticated “fuzzy” logic and “neuro-fuzzy” sys-
tems. Based on user-friendly but powerful func-
tions, the BI system can retrieve meaningful
insights while hiding the underlying complexity
of data interpretation. “What-if ” scenarios and
simulation functionality provide advanced, tai-
lored decision-making support.
The fundamental basis of every BI system,
however, is the data base on which it operates. Basic
systems focus on corporate ?nancial data only,
while advanced systems interconnect internal and
external sources with qualitative and quantitative
data. Advanced systems process the comprehensive
data set using methods perfectly tailored to a ?rm’s
needs and condense the ?ndings into meaningful
knowledge—hiding the complexity and selecting
only the maximum amount of input necessary to
help executives make the right judgments.
The Advantages of Business Intelligence
When analyzing a business intelligence solution,
it is important to consider the business bene?ts,
including improved overall decision making and
increased ef?ciency for business reporting and
analysis. To this ?rst point, BI offers four impor-
tant prerequisites for proper decision making:
• Required information is available
• Data is consistent across organizational units
• Information can be easily analyzed using built-
in analysis functionality
• Reports are presented in a user-friendly format
A well-designed business intelligence solution
ensures that information across the organization is
available in a consistent, reliable manner. Figures
can be aggregated and compared in different
business units, assuring the validity of like-for-
like data comparisons, and that all management
reports provide operations leaders and top man-
agement with the information they need to steer
the business properly.
Essentially, BI improves effciency on both the
information technology (IT) side and the business
side of the organization. On the IT side, workers
are freed from the recurring task of creating and
changing data reports as end-users are able to create
and change their own reports. On the business
side, less time is spent in data analysis and prepara-
tion as management reports are created directly
from the BI dashboards. Not only is the data in
these reports more up-to-date and credible, but
also they are easier to read and handle. And, impor-
tantly, the information can be downloaded on
smart devices, including the iPhone and iPad. The
sidebar on page 4, What Makes a BI Leader?, offers
a short list of success factors shared by top business
intelligence organizations.
Figure 1
Three phases of a business intelligence solution
Source: A.T. Kearney analysis
Phase 1
Define key performance
indicators and level of business
intelligence to be achieved
Phase 2 Phase 3
Collect requirements, build
prototype and conduct
vendor “proof of concept”
Implement solution
and improve tool
according to release plan
Figure 2
The main tasks in Phase 1
Source: A.T. Kearney analysis
• Evaluate potential key
performance indicators
(KPIs)
• Analyze empiricial findings
related to use of KPIs
• Evaluate simple
profitability metrics
• Assess select KPIs for
appropriateness
• Compare analysis of
value-add KPIs
• Identify potential risks of
making the wrong decision
Perform qualitative
evaluation
Determine value
correlations
Analyze
risks
Make
recommendations
1
Phase 1 should always be completed fully before proceeding with the second phase, as the required reporting and the defined KPIs set the framework for tool selection.
BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 5 BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 4
business. The link to operations is more dif?cult
as KPIs from manufacturing, production or logis-
tics are fairly different from ?nance KPIs and are
often dif?cult to connect to existing KPI trees.
Even between similar business lines, KPIs are
sometimes slightly different because they repre-
sent different business models —for instance,
internal production for intermediate products or
external production for ?nal products. If the long-
term strategy is to analyze operational KPIs, this
should be addressed at the outset. Once these
questions are answered and all affected business
areas are addressed, the second phase can begin.
Phase 2: Create a design and navigation
prototype and build a “proof of concept.” Four
tasks are involved in preparation for system imple-
mentation. The result is a “proof of concept,”
designed before the comprehensive implementa-
tion begins. At this point, software vendor selec-
tion is independent of speci?c design requirements
and often driven by strategic policies or IT land-
scape requirements. Based on IT architecture
rules, a short list can be devised up-front to select
appropriate tools to ?t the company’s require-
ments, IT strategy and IT landscape (see ?gure 4).
Phase 2 is not only about collecting require-
ments regarding the functionality of a future tool
(navigation and analysis deep dives, for example)
but also about report design, dashboards and tool
functionality. One point must be stated very
clearly: A pure management “cockpit” or dash-
board cannot replace the internal or external
reporting. As a ?rst step, it can be seen as a second
channel (always available), but with a different
level of detail (management adequate). All man-
agement cockpit tools offer a reporting function-
ality used to print-out the dashboard content.
Replacing the complete paper-based internal (or
external) reporting requires signi?cant efforts as
the detailed design of every single page is outlined
up-front. Both the dashboard screen design and
the report layouts, which cover all of the depicted
content regarding historic numbers and compari-
sons, among other things, ?nally get de?ned
before the detailed concept is handed over to a
system integrator for implementation. The real-
ization of the screens and the corresponding KPI
visualization are the main drivers of the system
implementation and the testing. Therefore stabil-
ity is required.
Figure 3
Layers of a business intelligence system
Sources: Forrester, A.T. Kearney analysis
Delivery
A
p
p
s
F
o
r
m
f
a
c
t
o
r
P
S
O
Reporting
Performance
management
Support
applications
Analytics
Discovery and
integration
Data
Infrastructure Network
Report mining
DQ – cleansing, profiling EAI / SOA EII ETL / CDC
Discovery accelerators
Adapters / tool kits Accelerators / query optimization
BPM / BRE integration BAM / CEP
Operational data stores (ODS), data warehouses (DW), data marts (DM)
Integration – third party applications
Services registry and repository
Streaming DBMS Search DBMS
RDBMS
In-memory DBMS Hierarchical / XML Columnar DBMS
Multi-value RDBMS Multi-dimensional OLAP
Usage analytics Statistical analysis Web analytics
Data / text mining Guided decisions NLP Guided search
Time series OLAP Operational DSS Predictive analytics
Servers Storage
MDM
S
I
I
n
d
u
s
t
r
y
v
e
r
t
i
c
a
l
a
p
p
l
i
c
a
t
i
o
n
s
S
t
r
a
t
e
g
y
A
p
p
l
i
a
n
c
e
M
e
t
h
o
d
o
l
o
g
y
G
o
v
e
r
n
a
n
c
e
B
I
S
a
a
S
H
o
s
t
e
d
B
I
(
A
S
P
)
b
-
l
a
y
e
r
s
)
M
S
P
/
a
p
p
s
o
u
t
s
o
u
r
c
i
n
g
C
e
n
t
e
r
o
f
E
x
c
e
l
l
e
n
c
e
E
n
t
e
r
p
r
i
s
e
a
p
p
s
:
E
R
P
,
C
R
M
,
S
C
M
,
E
R
M
B
P
O
eLearning ECM Metadata-integration, repositories
Version control
Reporting: ad-hoc, analytical, production Search Geospatial
Advanced data visualization Alerts Dashboards
Collaboration Life-cycle Mgt. Localization QA
Strategy / objectives management
Metrics / KPIs Planning Scorecards
Interactive voice response, ATM, point-of-sale Portals
Desktop gadgets Office suites Mobile Disconnected
O
r
g
What Makes a BI Leader?
From our experience helping com-
panies implement their business
intelligence projects, we have found
several common characteristics or
“success factors” that differentiate
the BI leaders from the followers.
The BI leaders:
• Defne and optimize corporate
report standards
• Focus on the business not the data
• Establish a balanced scorecard
• Defne clear data dimensions and
structures
• Develop a master data manage-
ment plan
• Establish corporate data gover-
nance and clear ownership of
master data
• Use report visualization in pilots
• Leverage web technologies
• Focus on cross-organizational
efforts
• Distinguish between business-
driven and IT-driven projects
• Defne the long-term BI scope,
from the beginning
• Realize a mobile version of
business intelligence
Figure 4
The tasks in phase 2
Source: A.T. Kearney analysis
• Perform assessment
to ensure the need
for a “cockpit”
• Conduct a brief cost-
benefit analysis of the
area and other potentially
affected areas such as
procurement
• Draw up a short list
of vendors, taking into
account industry reports
and other external
information
• Assess the options from
an internal viewpoint
• Complete a list of
business requirements
and build a first simple
PowerPoint prototype
to develop a “look-and-
feel” of the final product
• Begin company-vendor
discussions
• Help the vendor understand
the client and ensure vendor
receives timely feedback so
to make quick improvements
Assessment
Vendor
selection
Requirements
and prototypes
Proof of concept
BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 7 BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 6
The proof of concept increases the developers’
understanding of the company’s requirements
before starting the real systems implementation.
In our experience, a quick prototype allows a
company to check the design of all possible pre-
selected tools and test the capability of the poten-
tial solution provider. Work packages can also be
tested to assess vendors’ innovation capabilities in
solving design questions. Finally, the ?rm’s
requirements can be tested and challenged.
Phase 3: Implementation. Implementation is
a typical IT project. However, due to high visibil-
ity and management awareness, the implementa-
tion should be fast and provide quick solutions.
A release plan ensures ?rst results are delivered
quickly, while the ?nal and comprehensive solu-
tion is created in several steps, aligned with report-
ing cycles and data availability. The ?rst release
should provide all required dashboard functions
(design, navigation and drill-down) and some of
the reporting requirements, which are detailed in
the follow-on implementation phases and can be
delivered sequentially. Typically, ?rst releases lack
the full data set. An essential activity in the BI
project is to cleanse existing data and establish
a process to record new data in a proper way,
which often requires developing the entire data
architecture, including dimensions, hierarchies
and formulas. Close interaction between system
provider and business departments (as the ?nal
users and clients of the system) is crucial to the
success of the project. The management cockpit
or dashboard ful?lls the design and functional
requirements because it provides clear visibility
to management and the necessary ease of use.
Although all required data or KPIs may not be
included in the beginning, they are provided
throughout the steps.
Governance and the CIO’s Role
Within a BI project, the corporate IT and the
CIO moderate between the different business
departments that are involved, the internal IT
group, and the software provider or implementer.
A BI project is often driven by the ?nance depart-
ment as the key user due to corporate reporting
and corporate management requirements; ?nance
de?nes the main KPIs on a corporate level and
ensures standardization across all different busi-
ness models within the ?rm.
Operational KPIs are provided by the differ-
ent operating units and standardized to ensure
that consistent content is reported to top manage-
ment. The CIO and corporate IT take over the
role of supporting KPI de?nitions by providing
information about data sources, data availability
and data quality. And they start the analysis on
how a business intelligence tool could be used to
ful?ll high-level requirements (see sidebar: Business
Intelligence: A Case Study).
Part of the project involves de?ning future
BI governance. This often means establishing a BI
Business Intelligence: A Case Study
The management team at a large
German company decided to imple-
ment a corporate-wide business
intelligence (BI) process. The com-
pany, involved in heterogeneous
businesses, started with pilot units
in its three business concerns, de?n-
ing ?nancial key performance indi-
cators (KPIs) to manage and direct
the corporation.
The management team knew
that success would depend on cor-
porate-wide de?nitions for its KPIs
so they could be cascaded down to
all business units.
The project began with develop-
ment of a basic management dash-
board that provided a visual KPI tree
to clarify the logical dependencies of
the two main KPIs —and then illus-
trating all the subsequent KPIs that
?owed from them—and how they
navigated through the organization.
Next, business-speci?c operational
KPIs were added to the dashboard,
a simulation tool was developed
to provide units with a business-
planning model to illustrate the
dependencies between KPIs, and
a BI tool-based reporting process
was designed and implemented
The IT work began during the
?nal de?nition of corporate-wide
KPIs and reporting, providing infor-
mation about the availability of exist-
ing data within the data warehouse.
This was followed by the vendor
and tool-selection process. A proto-
type was designed, and software pro-
viders were asked to use the design
and business units’ functional
requirements to develop a rough
proof of concept.
Immediately after the proof-of-
concept presentations, the vendor-
selection process was ?nalized and
implementation began. Within three
months, the company had its ?rst
release, covering main functional-
ities, dashboard design and naviga-
tion, and ?rst-reporting factors. The
release plan took into account the
main reporting cycles, and two sub-
sequent releases were scheduled
within the planned timeframe.
Soon after introduction, the
management team was delighted as
user acceptance proved stronger than
expected throughout the organiza-
tion. When asked about the success
factors, team members were quick to
cite the top two: design and ease of
navigation within the BI tool, and
on-time delivery of the major KPIs.
All in all, the company is now
dedicated to using business intelli-
gence to help steer it on a richer
and more successful course.
• Through TOOL 1 WYSIWYG
the dashboard can be handled
• Vendor 1offers functional
building blocks for the
storing of comments in the
SAP BW
• Simulations can be saved;
retraction through vendor 1’s
own functionalities into BW
backend
• Look-and-feel remains the
same
• Comments and simulation
can be executed early
• Either DataMart on machine
two or WebService on
machine one
• BOE Infrastructure for
LiveOffice and reporting tool
(phase2)
• Possible according to the
demonstration; no information
given on the interface builder;
use of all graphic types possible
• Possible according to the
demonstration
• Comments can only be used in
the machine-three environment
• Possible according to the
demonstration; simulations can
be saved and retracted into the
SAP BW
• Look-and-feel remains the same
• Comments and simulation can be
executed early
• According to vendor, it can
communicate with SAP BW 3.5
but not demonstrated
• Basic infrastructure on machine
one has to be built anew
Figure 5
Detailed analysis of BI software vendors
Source: A.T. Kearney analysis Full function
• Only static design possible;
performance critical
• Use of standard BDS
associated with
performance issues
• Generally not simulation
functionality
• Due to low performance on
comments and the illustration
of graphs, no usage possible
in phases 1 to 2
• Executed on machine
one, no export of the cube
data needed
• None
Implementation
design
Implementation
comments
Implementation
simulation
Transition from
prototype to
release I to II
Connectivity to
data
Hardware costs
Category On-board tools Vendor 1 Vendor 2
Very limited function
A.T. Kearney is a global management consulting ?rm that uses strategic
insight, tailored solutions and a collaborative working style to help clients
achieve sustainable results. Since 1926, we have been trusted advisors on
CEO-agenda issues to the world’s leading corporations across all major
industries. A.T. Kearney’s of?ces are located in major business centers
in 37 countries.
AMERICAS Atlanta | Boston | Chicago | Dallas | Detroit | Mexico City
New York | San Francisco | São Paulo | Toronto | Washington, D.C.
EUROPE Amsterdam | Berlin | Brussels | Bucharest | Copenhagen
Düsseldorf | Frankfurt | Helsinki | Kiev | Lisbon | Ljubljana | London
Madrid | Milan | Moscow | Munich | Oslo | Paris | Prague | Rome
Stockholm | Stuttgart | Vienna | Warsaw | Zurich
ASIA PACIFIC Bangkok | Beijing | Hong Kong | Jakarta | Kuala Lumpur
Melbourne | Mumbai | New Delhi | Seoul | Shanghai | Singapore
Sydney | Tokyo
MIDDLE EAST Abu Dhabi | Dubai | Johannesburg | Manama | Riyadh
& AFRICA
For information on obtaining
additional copies, permission
to reprint or translate this work,
and all other correspondence,
please contact:
A.T. Kearney, Inc.
Marketing & Communications
222 West Adams Street
Chicago, Illinois 60606 U.S.A.
1 312 648 0111
email: [email protected]
www.atkearney.com
© 2011, A.T. Kearney, Inc. All rights reserved.
A.T. Kearney Korea LLC is a separate and independent legal entity operating under the A.T. Kearney name in Korea.
BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 8
center of excellence led by the ?nance department
that includes data governance with BI system
maintenance authority. Corporate IT should be
part of the change advisory board that assesses and
evaluates change requests based on the capabilities
of the system solution, while IT maintains tech-
nology authority.
Choosing Tools and an Implementation
Partner
BI tool selection is rarely a “green ?eld” approach.
The corporate IT strategy, system landscape and
the main requirements regarding the BI level to
be achieved are all guidelines in the selection pro-
cess. Market research and analysts’ estimations
can be used as support documents, but in most
cases these analyses are too general and cannot
be adapted to meet company speci?cs. Instead,
external reports are typically used afterwards as
support information to justify the short-list ven-
dors or tools.
The software vendor and implementer are the
same in most cases, as only a few companies are
able to provide a full business intelligence suite,
connected or even integrated somehow to the
main enterprise resource planning (ERP) systems,
such as SAP or Oracle.
A company-speci?c questionnaire and evalua-
tion template allows the ef?cient gathering of key
requirements. The main questions or key evalua-
tion points should be shared in advance with the
short-listed software vendors to give them an
opportunity to prepare the tool presentation and
to answer all questions completely. The clearer the
requirements are documented and described, the
faster the selection process can be executed (see
?gure 5 on page 7).
A rough prototype—such as a PowerPoint
visual of the management cockpit to demonstrate
key navigation functions and design-related
requirements will help both sides understand the
desired outcome and manage expectations. It is
the basis for the later detailed design and concept,
containing the description of each requirement.
This and the more technical description of the
existing landscape and necessary interfaces are
the most relevant documents for the implementa-
tion and build up to the kick-off for the system-
implementation phase.
BI: A Must for Business Success
A proper BI solution is a must have in today’s
world. Companies in all industries are using BI
systems for successful decision making. These
companies beat their competition and identify
new opportunities to optimize their businesses.
They also reduce resources for manual effort and
rededicate people to analyzing data and preparing
decision memos. For companies that grasp the
true potential in business intelligence, they should
take action sooner rather than later —time, as
always, is of the essence.
Authors
Alexander Martin is a principal in the strategic information technology practice. Based in the Düsseldorf of?ce,
he can be reached at [email protected].
Robert Jekel is a consultant based in the Zurich of?ce. He can be reached at [email protected].
Edgar Simons is a consultant in the Düsseldorf of?ce. He can be reached at [email protected].
ATK.0211.172
doc_355078347.pdf