Description
Business intelligence is often seen as a software solution designed to serve up data on executive dashboards.
Unleashing
the true value
of business
intelligence
Beyond the
dashboard
2 Strategy&
Contacts
Amsterdam
Marco Kesteloo
Partner
+31-20-504-1942
marco.kesteloo
@strategyand.pwc.com
Chicago
Tom Casey
Parner
+1-312-578-4627
tom.casey
@strategyand.pwc.com
Düsseldorf
Dietmar Ahlemann
Partner
+49-211-3890-287
dietmar.ahlemann
@strategyand.pwc.com
Frankfurt
Andreas Späne
Partner
+49-69-97167-408
andreas.spaene
@strategyand.pwc.com
London
Alan Gemes
Senior Partner
+44-20-7393-3290
alan.gemes
@strategyand.pwc.com
Moscow
Dr. Stefen Leistner
Partner
+7-985-368-7888
stefen.leistner
@strategyand.pwc.com
San Francisco
Douglas Hardman
Partner
+1-415-653-3537
douglas.hardman
@strategyand.pwc.com
São Paulo
Ivan De Souza
Senior Partner
+55-11-5501-6368
ivan.desouza
@strategyand.pwc.com
Stockholm
Per-Ola Karlsson
Partner
+46-8-506-190-49
per-ola.karlsson
@strategyand.pwc.com
This report was originally published by Booz & Company in 2010.
3 Strategy&
Executive summary
Business intelligence is often seen as a software solution designed to
serve up data on executive dashboards. But this is a wasteful and costly
misunderstanding of the value of true business intelligence. When
deployed properly, business intelligence should help de?ne strategy,
drive pro?tability, and develop a performance-oriented culture
throughout an organization. It is much more than a reporting tool.
Using business intelligence is a way of doing business.
To work in this way, the approach to business intelligence implementation
must be comprehensive and must focus on thoughtful, custom-crafted
metrics that will measure progress toward speci?c goals. Conceiving
these metrics is among the most important, and most difcult, aspects
of business intelligence. The process requires an honest assessment
of a company’s strengths and weaknesses. Without metrics that are
strategically sound, companies run the risk of becoming distracted
and losing focus on what is most important.
Getting the most out of a business intelligence deployment means
following a rigorous set of guiding principles, assigning clear roles and
responsibilities, and managing change throughout an organization. It
means working closely with an ecosystem of partners that will establish
the foundation and guide the implementation. And it means staying
focused on getting the right metrics to the right people at the right time.
4 Strategy&
Intelligent business
True business intelligence is exactly what it sounds like. It is the ability
to make sense of markets; to measure the progress of a company against
its goals; and to employ the skills, processes, technologies, applications,
and practices used to support good decision making. It is not a software
solution. It is not a methodology. And it is not easy.
Very few companies in the world have the discipline to focus their
operations in every business unit and product line on the things they
do best. Those that do are the companies that identify their strongest
internal capabilities and set thoughtful, strategic goals. And they
constantly, almost obsessively, measure their performance against
those goals.
That’s where business intelligence comes in. When it’s used correctly,
business intelligence presents a way of identifying the strengths and
weaknesses of a company. It can inform strategy and drive pro?tability.
And it can transform the culture of a company, from top to bottom. In
fact, we have worked with companies that have realized more than
US$1 billion in savings, and set up systems that drive top-line growth
and ensure lasting pro?tability.
Many companies have stumbled in their early attempts to leverage
this performance-driven approach to running a business by going
down the path of measuring thousands of unnecessary performance
indicators, rather than those that really matter. Before a company
can begin measuring its progress against goals, it needs to identify
those goals. To do this requires a much more thoughtful approach
than most companies have taken to date. A business intelligence
deployment must follow a rigorous set of guiding principles. It
requires carefully considered metrics that align with strategy,
drive value, ensure accountability, can be easily executed,
maintain quality and consistency, and manage interdependency.
And it requires a deep understanding of what a company is, and
what it would like to be.
5 Strategy&
The “metrics” system
The problem with business intelligence (BI) has nothing to do with
the quality of the products. Most of-the-shelf BI software is easy to
implement; incredibly powerful; rich with features; and capable of
aggregating, integrating, and analyzing data from nearly any part of a
business. And it’s not that companies don’t need business intelligence:
Gartner Inc. predicts that through 2012, 35 percent of the top 5,000
global companies will regularly fail to make insightful decisions, owing
to a lack of information, processes, and tools.
The problem with business intelligence is how companies approach it (see
“Steps to Success,” page 10). Many companies believe that BI is a software
solution that simply needs to be bought and installed. They use it narrowly
and follow the wrong metrics. And despite the signi?cant procurement,
installation, and maintenance costs, business intelligence is often used to
serve up inaccurate data or distract employees by delving too deeply into
corporate minutiae. In fact, it is no exaggeration to say the true value of
business intelligence has been heretofore widely misunderstood.
Ultimately, business intelligence is the key to running a performance-
oriented company. This means that any BI deployment has strategic,
operational, and cultural implications. And perhaps no aspect of a BI
implementation is more important — or more difcult — than choosing
metrics that are strategically and mathematically sound.
Metrics that do not accurately measure a company’s progress against its
goals can have employees chasing their tails. Metrics must be crafted and
customized to ?t a company’s speci?c goals. For example, a series of
Strategy& studies conducted over the past seven years with consumer
products, healthcare, and chemical companies statistically correlates
return on innovation investment (ROI
2
) with organic growth and links
innovation spending with ?nancial performance in ways that can lead
decision makers to generate higher, more reliable returns on innovation
and research and development (see Exhibit 1, next page). A company
recently employed ROI
2
to better understand its innovation efciency from
research and development eforts. In particular, company leaders wanted
to know the bene?ts and associated costs of their innovation expenditures.
Metrics that do
not accurately
measure a
company’s
progress against
its goals can
have employees
chasing their
tails.
6 Strategy&
Exhibit 1
ROI
2
highly correlates with ?rms’ growth performance
1
Revenue growth = 2003–
2005 after adjustments
to minimize impact of an
acquisition and other one-
time events.
2
ROI
2
is taken as a percent-
age of revised 2005 reve-
nues to minimize size bias.
Source: Strategy& analysis
ROI
2
vs. revenue growth
– This is the best measure of a
company’s growth potential
– The measure is
forward-looking—it predicts
a ?rm’s growth based on its
current innovation portfolio
– It is a comprehensive
measure—it considers all
aspects (e.g., investment/ex-
pected revenue/operating
margins) of the portfolio
R
2
= 87.16%
0%
2%
4%
6%
8%
10%
12%
14%
0.00% 0.25% 0.50% 0.75% 1.00%
Revenue growth
1
(organic)
Return on innovation investment as percentage of revenue
2
Company A
Company C
Company E
Company D
Company B
Company F
Rationale
It’s not uncommon for product-oriented companies to throw money at
research and development in hopes of increasing pro?tability. But not all
R&D is created equal. By closely measuring ROI
2
, the company gained a
clearer sense of where its money was best spent.
The statistical validity of ROI
2
bolsters its value as a metric, but so does the
fact that it functions as a leading indicator, helping decision makers
anticipate what their product portfolio will look like in the future. Too
often, companies rely on lagging indicators that accurately report past
performance while giving no indication of what lies around the next bend.
Good metrics have other temporal considerations. Some — such as ROI
2
—
guide strategic decision making over the longer term, perhaps for the next
year. Others (e.g., sales win rate) can help monitor weekly or monthly
performance. A daily dashboard may report essential metrics (e.g., client
issue escalations) that are important to manage on a day-to-day basis. All
have a role to play as part of an efective BI strategy.
7 Strategy&
By the numbers
Best-in-class business intelligence — and the metrics selected to support
it — exhibits six characteristics. In successful companies, performance
criteria align with strategy, drive value, ensure accountability, can
be easily executed, maintain quality and consistency, and manage
interdependency (see Exhibit 2, next page).
Each company will weight these criteria diferently. For example,
one leading global logistics provider, which had grown to more
than 470,000 employees in 220 countries, placed an emphasis on
maintaining quality and consistency. Because of a series of acquisitions,
the company had established a strategic imperative to improve its
?nancial controls and reporting standards across divisions. It needed
to reduce complexity, improve transparency, and transition from
intuition to fact-based decision making.
The company designed, implemented, and deployed a uni?ed system
for management and shareholder reporting, ?nancial and country
consolidation, and forecasting and planning. The new common
reporting system consolidated four business units and more than
3,000 reporting entities worldwide. And the key performance indicators
that emerged as a result improved ?nancial reporting capabilities,
increased ?nancial control and transparency throughout the company,
and harmonized the ?nancial systems. The company saved more than
€1 billion (approximately US$1.4 billion) as a result.
Meanwhile, a global software company worked to align its strategy
by measuring the relative value of growth (RVG) — an assessment
of the strength the market places on revenue growth relative to
margin growth — across its entire product portfolio and balancing
that portfolio with company strategy. From the beginning, the
company built a clear message about its goal of improving top-line
growth and share price and built a strong case throughout the
company (and externally) for change. As a result, the company
drove top-line growth from 4 percent to 7 percent and nearly
doubled its stock price in two years.
8 Strategy&
Exhibit 2
Six characteristics of best-in-class business intelligence
Source: Expert interviews;
articles from specialized
journals (Journal of
Performance Management,
Business Performance
Magazine); James W.
Smither, Performance
Management: Putting
Research into Action;
Pfeiffer; Strategy& analysis
– In line with company’s strategy & culture
– Clearly articulated
– Strong leadership commitment
– Supporting governance structure
Metrics selection and performance measurement criteria
Align with
strategy
– Link ?nancial & operational targets
– Focused on value drivers
– Provide leading & lagging indicators
– Reinforced with consequences
Drive value
– Individual accountability & ownership for performance
– Ambitious commitments
– Strong message regarding performance
– Supporting incentive system
Ensure
accountability
– Provide management insight
– Simple-to-use systems & processes
– User-friendly systems interface & intuitive report design
– Provide “right time” information
Can be easily
executed
– Consistency & transparency
– Holistic (tools, processes, roles)
– Balance ?exibility & standardization
– Track progress over time, across products
– Provide a “single version of truth”
Maintain
quality &
consistency
– Allow use of feedback to change metrics
– Have adaptive capabilities & enable corrective action
– Enable use of external developments
Manage
interdependency
Other examples:
• A major European stock exchange implemented a BI solution to
create a unifying force within the organization as well as manage
costs. The implementation provided con?dence for executives and
drove a sense of urgency within the organization through a new
culture of goal setting and performance tracking. Also, reporting
was streamlined, helping to lower operating costs by 25 percent.
9 Strategy&
• A global energy company implemented a robust BI solution with
the goal of simplifying its reporting process. Over the course of
20 months, the company decreased the number of ?nancial systems
by 40 percent, accounting units by 46 percent, and reporting units
by 61 percent. The solution shortened the planning cycle by three
months and the standard reporting by 150 pages with each cycle,
leading not only to cost savings but, more important, to a new focus
on higher-value activities.
But the work doesn’t end once companies have determined their criteria
weighting and acted accordingly. It is critical that performance metrics
and incentives be continually revisited to ensure they are aligned with
strategy. That’s why companies should employ a continuous metrics
improvement process, to manage and govern the use of metrics to drive
value (see Exhibit 3).
Exhibit 3
Continuous metrics improvement process
Source: Strategy&
– Transparent process
– Widely available
– Actionable (with “temporary”
metrics as possible alternative)
Understand
capabilities
& needs
End of life
Highly
reliable
Good
enough
to use
1. Create & develop 2. Manage & govern
Governance committee
3. Utilize & drive value 4. Retire & refresh
Ongoing metrics
recommendations
Manage
usage
Assess & drive quality
and ?nalize de?nitions,
thresholds & targets
Assign
owners &
viewing rights
Select ones
with highest
value
Validate
10 Strategy&
Steps to success
Successful BI implementations follow
a set of guiding principles that fall into
four categories.
Foundation
1. Drive the case for change from the
top down and the bottom up. A BI
implementation will be successful only
if people use it. And this kind of change
can be intimidating at any level of a
company. To ensure success, work to
foster demand for the tools from the
front line, while insisting the tools be
adopted in the executive ranks.
2. De?ne BI comprehensively. Business
intelligence is not just metrics. A BI
deployment changes the approach
to how business gets done, putting
a larger onus on performance
measurement and accountability. Be
certain your company’s approach is
equally comprehensive, including
metrics, processes, systems, and
change management.
3. Develop a modular approach.
BI projects can touch nearly every
data source in a company. Use agile
development practices to ensure a
?exible, faster, and more efective
deployment.
Design
4. Focus on the right metrics. This is
where the truly coherent, capabilities-
driven strategy gets implemented. The
metrics should be tightly aligned with
strategy and essential capabilities.
They should include both internal and
external inputs. And they should consist
of a balance of leading and lagging
indicators.
5. Keep it simple. BI software can drill
down to the most irrelevant minutiae
within a company. And it can slice
and dice information in hundreds of
diferent ways. Keep the distractions
to a minimum. Include only the most
important metrics from the top three
or four levels.
6. Build a uni?ed BI system. Companies
are complex systems with hundreds of
hidden interdependencies. BI systems
can uncover some of those complexities
and allow great visibility into the way
a company operates. To enable this,
however, you must integrate data
across the company, to allow root cause
analysis and custom analytics.
Pilot/rollout
7. Launch early. Getting an early return
for a project like this can go a long
way toward sustaining its success.
Start of with existing high-quality
metrics in high-priority product groups
and functions to add value and build
momentum.
8. Detail system requirements and select
partners. Working closely with IT will be
a critical factor during this stage. Be sure
to objectively assess options for project
management, systems integration, and
software tools.
9. Leverage existing infrastructure. A
business intelligence implementation
is going to run across the breadth of a
company’s IT infrastructure. Although
you don’t want to wait for new systems
before building out BI capabilities, you
must ensure that BI software works
alongside the future vision for IT and
the business. The good news is that BI
software is often a “front end,” which
Continued
11 Strategy&
allows for a high degree of ?exibility in
the back end.
Change management
10. Establish central governance
structure. Business intelligence is not
like any other enterprise application.
It requires collaborative ownership
and oversight. It requires business-led
governance with IT support. And it
requires new data management roles
and functions, robust metric life-cycle
management, and strong ongoing project
management.
11. Proactively manage change. This
is not a build-it-and-they-will-come
scenario. Adoption must be driven
throughout the enterprise. Dashboards
and metrics must have teeth, with
accountability and incentives. And
management must train, communicate,
and secure senior leadership in driving
behavioral change.
12 Strategy&
Roles and responsibilities
None of the value of business intelligence is gained without the support
and leadership of key stakeholders (see “Project Pitfalls,” page 14). The
roles that employees assume in rolling out a BI implementation can be
just as important as the metrics themselves. That’s why forward-
thinking organizations, including the United States government, the
NEC Corporation, and Yahoo, have assigned chief performance ofcers
(CPOs).
The rise of the CPO tells us something important about business
intelligence and the culture of performance a BI system cultivates.
Metrics, and the changes they enable, are of the utmost importance
to an enterprise. They must be managed from the highest executive
ranks, and by the executives most directly responsible for the
performance they re?ect. In the case of ?nance-oriented dashboards,
that is likely to be the chief ?nancial ofcer; operations-focused
dashboard initiatives may fall under the control of the chief operating
ofcer, or even business unit heads.
This is not to say the chief information ofcer doesn’t play a critical role
in selecting, implementing, and managing business intelligence. In fact,
the CIO should lead the technology design and the selection of software
and systems integrator. The CIO should also manage the data quality
and the build-out of the system. Successful BI implementation depends
on broad, business-based support and cross-functional input. And it
depends on the multidisciplinary capabilities and ecosystem of your
partners (see Exhibit 4, next page).
13 Strategy&
Exhibit 4
BI implementation goes beyond metrics
Note: ETL = extract,
transform, and load.
Source: Strategy&
Wipro
Accenture
IBM
Cap Gemini
Infosys
SAS
Business Objects
Cognos
Hyperion
MicroStrategy
Tivio
Technical design for
ETL interfaces
ETL interfaces &
application modi?cations
System build, test & rollout
BI system setup & rollout
BI software specialists
ETL software specialists
Analytics tools
Program management
Change management
Business design (metrics, targets)
Technical design (metrics, dashboards)
Vendor selection & sourcing
Systems
integrator(s)
Business
consultants
BI vendors
& tools
Client
Partner ecosystem
14 Strategy&
Project pitfalls
Any major change to the way an
organization measures success is sure to
have a few pitfalls. Below are seven of the
most common issues that come up during a
business intelligence implementation, and
some suggestions on how to address them
before they arise.
Risk 1: Lack of sustained leadership
support
Preemption: Designate project
champions at multiple initiative levels;
incentivize leadership and management
to encourage a sustained level of efort;
continue to build organizational pull.
Risk 2: Partner failure (e.g., systems
integrator, BI tool vendor)
Preemption: Thoroughly evaluate
potential external contractors and
con?rm adequate track records;
negotiate efective ?nancial controls
contingent on project success into
external partner contracts.
Risk 3: Project delays or scope creep
resulting in loss of organizational
momentum
Preemption: Ensure strong project
management capabilities; set stretch
targets and manage through modular
releases; clearly de?ne project scope
and do not change scope without time/
resource changes.
Risk 4: Development halted to
accommodate systems changes
Preemption: Utilize a modular approach
to implementation to prevent collective
progress interruptions; efectively plan
future upgrades and schedule within the
context of other system changes.
Risk 5: Security breaches
Preemption: Leverage role-based security
tools; implement central governance and
improved data control.
Risk 6: Unintended consequences of
focusing on wrong metrics
Preemption: Outline and document
metric choices, including secondary
impacts; implement a ?exible
architecture and processes that can
accommodate routine upgrades,
including metric adjustment.
Risk 7: Organization resists tracking
and acting on metrics and targets
Preemption: Clearly show support
for project and broader goals at the
executive level; align incentives at
both the department and individual
levels to encourage adoption; reinforce
behavioral changes that create
transparency and information sharing.
15 Strategy&
Conclusion
A business intelligence implementation may seem like a daunting
undertaking, fraught with risks and bounded by rules. But it is not
an action intended to be undertaken alone. An ecosystem of vendors,
integrators, and business consultants work together to ensure the
success of a well-conceived BI project. Together with these providers,
a company can understand the current state of metrics, systems,
people, and management and de?ne a future vision.
But whatever team a company assembles, applying business intelligence
properly is the only way to make an impact on an organization. That
means ?rst understanding the potential for business intelligence to
de?ne and measure strategy, and then following the guiding principles
to make that happen. Anything else would be less than intelligent.
Resource
Alexander Kandybin and Martin Kihn, “The Innovator’s Prescription: Raising
Your Return on Innovation Investment,” strategy+business, Summer 2004.
www.strategy-business.com/media/?le/rr00007.pdf
www.strategyand.pwc.com
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details. Disclaimer: This content is for general information purposes only, and should not be used as a substitute for consultation with professional advisors.
This report was originally published by Booz & Company in 2010.
doc_248486865.pdf
Business intelligence is often seen as a software solution designed to serve up data on executive dashboards.
Unleashing
the true value
of business
intelligence
Beyond the
dashboard
2 Strategy&
Contacts
Amsterdam
Marco Kesteloo
Partner
+31-20-504-1942
marco.kesteloo
@strategyand.pwc.com
Chicago
Tom Casey
Parner
+1-312-578-4627
tom.casey
@strategyand.pwc.com
Düsseldorf
Dietmar Ahlemann
Partner
+49-211-3890-287
dietmar.ahlemann
@strategyand.pwc.com
Frankfurt
Andreas Späne
Partner
+49-69-97167-408
andreas.spaene
@strategyand.pwc.com
London
Alan Gemes
Senior Partner
+44-20-7393-3290
alan.gemes
@strategyand.pwc.com
Moscow
Dr. Stefen Leistner
Partner
+7-985-368-7888
stefen.leistner
@strategyand.pwc.com
San Francisco
Douglas Hardman
Partner
+1-415-653-3537
douglas.hardman
@strategyand.pwc.com
São Paulo
Ivan De Souza
Senior Partner
+55-11-5501-6368
ivan.desouza
@strategyand.pwc.com
Stockholm
Per-Ola Karlsson
Partner
+46-8-506-190-49
per-ola.karlsson
@strategyand.pwc.com
This report was originally published by Booz & Company in 2010.
3 Strategy&
Executive summary
Business intelligence is often seen as a software solution designed to
serve up data on executive dashboards. But this is a wasteful and costly
misunderstanding of the value of true business intelligence. When
deployed properly, business intelligence should help de?ne strategy,
drive pro?tability, and develop a performance-oriented culture
throughout an organization. It is much more than a reporting tool.
Using business intelligence is a way of doing business.
To work in this way, the approach to business intelligence implementation
must be comprehensive and must focus on thoughtful, custom-crafted
metrics that will measure progress toward speci?c goals. Conceiving
these metrics is among the most important, and most difcult, aspects
of business intelligence. The process requires an honest assessment
of a company’s strengths and weaknesses. Without metrics that are
strategically sound, companies run the risk of becoming distracted
and losing focus on what is most important.
Getting the most out of a business intelligence deployment means
following a rigorous set of guiding principles, assigning clear roles and
responsibilities, and managing change throughout an organization. It
means working closely with an ecosystem of partners that will establish
the foundation and guide the implementation. And it means staying
focused on getting the right metrics to the right people at the right time.
4 Strategy&
Intelligent business
True business intelligence is exactly what it sounds like. It is the ability
to make sense of markets; to measure the progress of a company against
its goals; and to employ the skills, processes, technologies, applications,
and practices used to support good decision making. It is not a software
solution. It is not a methodology. And it is not easy.
Very few companies in the world have the discipline to focus their
operations in every business unit and product line on the things they
do best. Those that do are the companies that identify their strongest
internal capabilities and set thoughtful, strategic goals. And they
constantly, almost obsessively, measure their performance against
those goals.
That’s where business intelligence comes in. When it’s used correctly,
business intelligence presents a way of identifying the strengths and
weaknesses of a company. It can inform strategy and drive pro?tability.
And it can transform the culture of a company, from top to bottom. In
fact, we have worked with companies that have realized more than
US$1 billion in savings, and set up systems that drive top-line growth
and ensure lasting pro?tability.
Many companies have stumbled in their early attempts to leverage
this performance-driven approach to running a business by going
down the path of measuring thousands of unnecessary performance
indicators, rather than those that really matter. Before a company
can begin measuring its progress against goals, it needs to identify
those goals. To do this requires a much more thoughtful approach
than most companies have taken to date. A business intelligence
deployment must follow a rigorous set of guiding principles. It
requires carefully considered metrics that align with strategy,
drive value, ensure accountability, can be easily executed,
maintain quality and consistency, and manage interdependency.
And it requires a deep understanding of what a company is, and
what it would like to be.
5 Strategy&
The “metrics” system
The problem with business intelligence (BI) has nothing to do with
the quality of the products. Most of-the-shelf BI software is easy to
implement; incredibly powerful; rich with features; and capable of
aggregating, integrating, and analyzing data from nearly any part of a
business. And it’s not that companies don’t need business intelligence:
Gartner Inc. predicts that through 2012, 35 percent of the top 5,000
global companies will regularly fail to make insightful decisions, owing
to a lack of information, processes, and tools.
The problem with business intelligence is how companies approach it (see
“Steps to Success,” page 10). Many companies believe that BI is a software
solution that simply needs to be bought and installed. They use it narrowly
and follow the wrong metrics. And despite the signi?cant procurement,
installation, and maintenance costs, business intelligence is often used to
serve up inaccurate data or distract employees by delving too deeply into
corporate minutiae. In fact, it is no exaggeration to say the true value of
business intelligence has been heretofore widely misunderstood.
Ultimately, business intelligence is the key to running a performance-
oriented company. This means that any BI deployment has strategic,
operational, and cultural implications. And perhaps no aspect of a BI
implementation is more important — or more difcult — than choosing
metrics that are strategically and mathematically sound.
Metrics that do not accurately measure a company’s progress against its
goals can have employees chasing their tails. Metrics must be crafted and
customized to ?t a company’s speci?c goals. For example, a series of
Strategy& studies conducted over the past seven years with consumer
products, healthcare, and chemical companies statistically correlates
return on innovation investment (ROI
2
) with organic growth and links
innovation spending with ?nancial performance in ways that can lead
decision makers to generate higher, more reliable returns on innovation
and research and development (see Exhibit 1, next page). A company
recently employed ROI
2
to better understand its innovation efciency from
research and development eforts. In particular, company leaders wanted
to know the bene?ts and associated costs of their innovation expenditures.
Metrics that do
not accurately
measure a
company’s
progress against
its goals can
have employees
chasing their
tails.
6 Strategy&
Exhibit 1
ROI
2
highly correlates with ?rms’ growth performance
1
Revenue growth = 2003–
2005 after adjustments
to minimize impact of an
acquisition and other one-
time events.
2
ROI
2
is taken as a percent-
age of revised 2005 reve-
nues to minimize size bias.
Source: Strategy& analysis
ROI
2
vs. revenue growth
– This is the best measure of a
company’s growth potential
– The measure is
forward-looking—it predicts
a ?rm’s growth based on its
current innovation portfolio
– It is a comprehensive
measure—it considers all
aspects (e.g., investment/ex-
pected revenue/operating
margins) of the portfolio
R
2
= 87.16%
0%
2%
4%
6%
8%
10%
12%
14%
0.00% 0.25% 0.50% 0.75% 1.00%
Revenue growth
1
(organic)
Return on innovation investment as percentage of revenue
2
Company A
Company C
Company E
Company D
Company B
Company F
Rationale
It’s not uncommon for product-oriented companies to throw money at
research and development in hopes of increasing pro?tability. But not all
R&D is created equal. By closely measuring ROI
2
, the company gained a
clearer sense of where its money was best spent.
The statistical validity of ROI
2
bolsters its value as a metric, but so does the
fact that it functions as a leading indicator, helping decision makers
anticipate what their product portfolio will look like in the future. Too
often, companies rely on lagging indicators that accurately report past
performance while giving no indication of what lies around the next bend.
Good metrics have other temporal considerations. Some — such as ROI
2
—
guide strategic decision making over the longer term, perhaps for the next
year. Others (e.g., sales win rate) can help monitor weekly or monthly
performance. A daily dashboard may report essential metrics (e.g., client
issue escalations) that are important to manage on a day-to-day basis. All
have a role to play as part of an efective BI strategy.
7 Strategy&
By the numbers
Best-in-class business intelligence — and the metrics selected to support
it — exhibits six characteristics. In successful companies, performance
criteria align with strategy, drive value, ensure accountability, can
be easily executed, maintain quality and consistency, and manage
interdependency (see Exhibit 2, next page).
Each company will weight these criteria diferently. For example,
one leading global logistics provider, which had grown to more
than 470,000 employees in 220 countries, placed an emphasis on
maintaining quality and consistency. Because of a series of acquisitions,
the company had established a strategic imperative to improve its
?nancial controls and reporting standards across divisions. It needed
to reduce complexity, improve transparency, and transition from
intuition to fact-based decision making.
The company designed, implemented, and deployed a uni?ed system
for management and shareholder reporting, ?nancial and country
consolidation, and forecasting and planning. The new common
reporting system consolidated four business units and more than
3,000 reporting entities worldwide. And the key performance indicators
that emerged as a result improved ?nancial reporting capabilities,
increased ?nancial control and transparency throughout the company,
and harmonized the ?nancial systems. The company saved more than
€1 billion (approximately US$1.4 billion) as a result.
Meanwhile, a global software company worked to align its strategy
by measuring the relative value of growth (RVG) — an assessment
of the strength the market places on revenue growth relative to
margin growth — across its entire product portfolio and balancing
that portfolio with company strategy. From the beginning, the
company built a clear message about its goal of improving top-line
growth and share price and built a strong case throughout the
company (and externally) for change. As a result, the company
drove top-line growth from 4 percent to 7 percent and nearly
doubled its stock price in two years.
8 Strategy&
Exhibit 2
Six characteristics of best-in-class business intelligence
Source: Expert interviews;
articles from specialized
journals (Journal of
Performance Management,
Business Performance
Magazine); James W.
Smither, Performance
Management: Putting
Research into Action;
Pfeiffer; Strategy& analysis
– In line with company’s strategy & culture
– Clearly articulated
– Strong leadership commitment
– Supporting governance structure
Metrics selection and performance measurement criteria
Align with
strategy
– Link ?nancial & operational targets
– Focused on value drivers
– Provide leading & lagging indicators
– Reinforced with consequences
Drive value
– Individual accountability & ownership for performance
– Ambitious commitments
– Strong message regarding performance
– Supporting incentive system
Ensure
accountability
– Provide management insight
– Simple-to-use systems & processes
– User-friendly systems interface & intuitive report design
– Provide “right time” information
Can be easily
executed
– Consistency & transparency
– Holistic (tools, processes, roles)
– Balance ?exibility & standardization
– Track progress over time, across products
– Provide a “single version of truth”
Maintain
quality &
consistency
– Allow use of feedback to change metrics
– Have adaptive capabilities & enable corrective action
– Enable use of external developments
Manage
interdependency
Other examples:
• A major European stock exchange implemented a BI solution to
create a unifying force within the organization as well as manage
costs. The implementation provided con?dence for executives and
drove a sense of urgency within the organization through a new
culture of goal setting and performance tracking. Also, reporting
was streamlined, helping to lower operating costs by 25 percent.
9 Strategy&
• A global energy company implemented a robust BI solution with
the goal of simplifying its reporting process. Over the course of
20 months, the company decreased the number of ?nancial systems
by 40 percent, accounting units by 46 percent, and reporting units
by 61 percent. The solution shortened the planning cycle by three
months and the standard reporting by 150 pages with each cycle,
leading not only to cost savings but, more important, to a new focus
on higher-value activities.
But the work doesn’t end once companies have determined their criteria
weighting and acted accordingly. It is critical that performance metrics
and incentives be continually revisited to ensure they are aligned with
strategy. That’s why companies should employ a continuous metrics
improvement process, to manage and govern the use of metrics to drive
value (see Exhibit 3).
Exhibit 3
Continuous metrics improvement process
Source: Strategy&
– Transparent process
– Widely available
– Actionable (with “temporary”
metrics as possible alternative)
Understand
capabilities
& needs
End of life
Highly
reliable
Good
enough
to use
1. Create & develop 2. Manage & govern
Governance committee
3. Utilize & drive value 4. Retire & refresh
Ongoing metrics
recommendations
Manage
usage
Assess & drive quality
and ?nalize de?nitions,
thresholds & targets
Assign
owners &
viewing rights
Select ones
with highest
value
Validate
10 Strategy&
Steps to success
Successful BI implementations follow
a set of guiding principles that fall into
four categories.
Foundation
1. Drive the case for change from the
top down and the bottom up. A BI
implementation will be successful only
if people use it. And this kind of change
can be intimidating at any level of a
company. To ensure success, work to
foster demand for the tools from the
front line, while insisting the tools be
adopted in the executive ranks.
2. De?ne BI comprehensively. Business
intelligence is not just metrics. A BI
deployment changes the approach
to how business gets done, putting
a larger onus on performance
measurement and accountability. Be
certain your company’s approach is
equally comprehensive, including
metrics, processes, systems, and
change management.
3. Develop a modular approach.
BI projects can touch nearly every
data source in a company. Use agile
development practices to ensure a
?exible, faster, and more efective
deployment.
Design
4. Focus on the right metrics. This is
where the truly coherent, capabilities-
driven strategy gets implemented. The
metrics should be tightly aligned with
strategy and essential capabilities.
They should include both internal and
external inputs. And they should consist
of a balance of leading and lagging
indicators.
5. Keep it simple. BI software can drill
down to the most irrelevant minutiae
within a company. And it can slice
and dice information in hundreds of
diferent ways. Keep the distractions
to a minimum. Include only the most
important metrics from the top three
or four levels.
6. Build a uni?ed BI system. Companies
are complex systems with hundreds of
hidden interdependencies. BI systems
can uncover some of those complexities
and allow great visibility into the way
a company operates. To enable this,
however, you must integrate data
across the company, to allow root cause
analysis and custom analytics.
Pilot/rollout
7. Launch early. Getting an early return
for a project like this can go a long
way toward sustaining its success.
Start of with existing high-quality
metrics in high-priority product groups
and functions to add value and build
momentum.
8. Detail system requirements and select
partners. Working closely with IT will be
a critical factor during this stage. Be sure
to objectively assess options for project
management, systems integration, and
software tools.
9. Leverage existing infrastructure. A
business intelligence implementation
is going to run across the breadth of a
company’s IT infrastructure. Although
you don’t want to wait for new systems
before building out BI capabilities, you
must ensure that BI software works
alongside the future vision for IT and
the business. The good news is that BI
software is often a “front end,” which
Continued
11 Strategy&
allows for a high degree of ?exibility in
the back end.
Change management
10. Establish central governance
structure. Business intelligence is not
like any other enterprise application.
It requires collaborative ownership
and oversight. It requires business-led
governance with IT support. And it
requires new data management roles
and functions, robust metric life-cycle
management, and strong ongoing project
management.
11. Proactively manage change. This
is not a build-it-and-they-will-come
scenario. Adoption must be driven
throughout the enterprise. Dashboards
and metrics must have teeth, with
accountability and incentives. And
management must train, communicate,
and secure senior leadership in driving
behavioral change.
12 Strategy&
Roles and responsibilities
None of the value of business intelligence is gained without the support
and leadership of key stakeholders (see “Project Pitfalls,” page 14). The
roles that employees assume in rolling out a BI implementation can be
just as important as the metrics themselves. That’s why forward-
thinking organizations, including the United States government, the
NEC Corporation, and Yahoo, have assigned chief performance ofcers
(CPOs).
The rise of the CPO tells us something important about business
intelligence and the culture of performance a BI system cultivates.
Metrics, and the changes they enable, are of the utmost importance
to an enterprise. They must be managed from the highest executive
ranks, and by the executives most directly responsible for the
performance they re?ect. In the case of ?nance-oriented dashboards,
that is likely to be the chief ?nancial ofcer; operations-focused
dashboard initiatives may fall under the control of the chief operating
ofcer, or even business unit heads.
This is not to say the chief information ofcer doesn’t play a critical role
in selecting, implementing, and managing business intelligence. In fact,
the CIO should lead the technology design and the selection of software
and systems integrator. The CIO should also manage the data quality
and the build-out of the system. Successful BI implementation depends
on broad, business-based support and cross-functional input. And it
depends on the multidisciplinary capabilities and ecosystem of your
partners (see Exhibit 4, next page).
13 Strategy&
Exhibit 4
BI implementation goes beyond metrics
Note: ETL = extract,
transform, and load.
Source: Strategy&
Wipro
Accenture
IBM
Cap Gemini
Infosys
SAS
Business Objects
Cognos
Hyperion
MicroStrategy
Tivio
Technical design for
ETL interfaces
ETL interfaces &
application modi?cations
System build, test & rollout
BI system setup & rollout
BI software specialists
ETL software specialists
Analytics tools
Program management
Change management
Business design (metrics, targets)
Technical design (metrics, dashboards)
Vendor selection & sourcing
Systems
integrator(s)
Business
consultants
BI vendors
& tools
Client
Partner ecosystem
14 Strategy&
Project pitfalls
Any major change to the way an
organization measures success is sure to
have a few pitfalls. Below are seven of the
most common issues that come up during a
business intelligence implementation, and
some suggestions on how to address them
before they arise.
Risk 1: Lack of sustained leadership
support
Preemption: Designate project
champions at multiple initiative levels;
incentivize leadership and management
to encourage a sustained level of efort;
continue to build organizational pull.
Risk 2: Partner failure (e.g., systems
integrator, BI tool vendor)
Preemption: Thoroughly evaluate
potential external contractors and
con?rm adequate track records;
negotiate efective ?nancial controls
contingent on project success into
external partner contracts.
Risk 3: Project delays or scope creep
resulting in loss of organizational
momentum
Preemption: Ensure strong project
management capabilities; set stretch
targets and manage through modular
releases; clearly de?ne project scope
and do not change scope without time/
resource changes.
Risk 4: Development halted to
accommodate systems changes
Preemption: Utilize a modular approach
to implementation to prevent collective
progress interruptions; efectively plan
future upgrades and schedule within the
context of other system changes.
Risk 5: Security breaches
Preemption: Leverage role-based security
tools; implement central governance and
improved data control.
Risk 6: Unintended consequences of
focusing on wrong metrics
Preemption: Outline and document
metric choices, including secondary
impacts; implement a ?exible
architecture and processes that can
accommodate routine upgrades,
including metric adjustment.
Risk 7: Organization resists tracking
and acting on metrics and targets
Preemption: Clearly show support
for project and broader goals at the
executive level; align incentives at
both the department and individual
levels to encourage adoption; reinforce
behavioral changes that create
transparency and information sharing.
15 Strategy&
Conclusion
A business intelligence implementation may seem like a daunting
undertaking, fraught with risks and bounded by rules. But it is not
an action intended to be undertaken alone. An ecosystem of vendors,
integrators, and business consultants work together to ensure the
success of a well-conceived BI project. Together with these providers,
a company can understand the current state of metrics, systems,
people, and management and de?ne a future vision.
But whatever team a company assembles, applying business intelligence
properly is the only way to make an impact on an organization. That
means ?rst understanding the potential for business intelligence to
de?ne and measure strategy, and then following the guiding principles
to make that happen. Anything else would be less than intelligent.
Resource
Alexander Kandybin and Martin Kihn, “The Innovator’s Prescription: Raising
Your Return on Innovation Investment,” strategy+business, Summer 2004.
www.strategy-business.com/media/?le/rr00007.pdf
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This report was originally published by Booz & Company in 2010.
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