a forrester consulting thought leadership paper commissioned by hewlett packard …h17007.€¦ ·...

A Forrester Consulting Thought Leadership Paper Commissioned By Hewlett Packard

Employ Next-Generation Business Intelligence For More Insightful And Rapid Decisions

October 2012

Forrester Consulting


Page 1

Table Of Contents

Executive Summary ................................................................................................................................................................................. 2

Why Is BI On Top Of Everyone’s Agendas?....................................................................................................................................... 3

Why Do Many BI Initiatives Pose Numerous Challenges? ............................................................................................................. 5

Move Forward With Successful BI Initiatives Using A Combination Of Best Practices And Next-Generation

Technologies ............................................................................................................................................................................................. 7

Key Recommendations ......................................................................................................................................................................... 11

Appendix A: Methodology................................................................................................................................................................... 12

Appendix B: Study Demographics ..................................................................................................................................................... 12

Appendix C: Endnotes .......................................................................................................................................................................... 13

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Executive Summary

To put it bluntly, there is no management without measurement. Unless you have been asleep at the wheel, you have

been using numerous variations of so-called business intelligence (BI) tools and solutions for the past 20 years. No

matter what the name — management information systems (MIS), reporting applications, executive information

systems (EIS) — or the tools — custom coded, embedded into ERP or based on desktop tools like spreadsheets — were,

we all have been and are using them to understand where our businesses were, where our operations are today, and

where our strategy and tactics will take us in the future.

Multiple conversations with Forrester clients show that most firms use only 1% to 5% of the data available to them.

What if that number doubled or tripled or quadrupled? The possibilities of the new insights would be virtually endless.

There’s a treasure chest of truly amazing examples out there, such as saving lives by real-time monitoring of millions of

hospital patients data points, saving natural resources by sophisticated analysis of smart grid data, or extending single

views of customers from 360 to 720 degrees by including customer interactions with their friends in social circles.

But these new insights and intelligence require new approaches. The time for using one-off “homegrown” BI

applications has passed. There’s just too much complexity, too much data, and too many regulations in the modern

word. In March 2012, HP commissioned Forrester Consulting to investigate and analyze the trends, patterns, and best

practices in the modern BI environments. To further explore this market, Forrester developed and tested a hypothesis

the combination of best practices and next-generation technologies can significantly contribute to successful BI

implementations. In-depth surveys with 291 senior business and IT professionals revealed that these companies

achieved only moderate success in their BI initiatives, with many reporting much-needed room for improvement. This

study also confirmed findings from other extensive Forrester research that a combination of best practices and next-

generation technologies can significantly boost the chances for delivering efficient and effective BI solutions.

Key Findings Forrester’s study yielded four key findings:

• BI is now a key corporate asset. Most enterprises have graduated from using BI as just another back-office

application and now are investing in and leveraging information as a key corporate asset for competitive

differentiation.

• The road to successful BI environments remains perilous. The majority of factors, including complexity and

poor applicability of earlier-generation approaches and technologies, lead to multiple BI challenges. In most

cases, companies have more chances of success when they work with an experienced, successful, trusted partner

with deep and broad BI specialization.

• BI success can be within your reach. Enterprises can increase their chances for successful BI implementations by

following best practices and leveraging next-generation technologies.

• Open standards are important. It’s important to work with vendors that embrace open standards, not just for

software, but for the entire BI infrastructure as well. For example, technologies that can improve the integration

of storage and network virtualization and increase integration of the systems-level virtualization capabilities with

higher level management software can provide clients with lower operating expenses, which contributes to more

successful and more agile BI initiatives.



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Why Is BI On Top Of Everyone’s Agendas?

Change is the only constant in the modern, fast-moving global economy. Within days — a few months at most —

incoming C-level and all other strategic, tactical, and operational decision-makers must identify ways to improve their

enterprise performance by boosting profitability, raising market share, leapfrogging competitors, and/or accomplishing

key objectives. But achieving these objectives is not as simple as just looking at the numbers. What about non-financial

measures (e.g., customer loyalty and employee satisfaction) that don’t show up in financial accounting? How do you

quickly and efficiently get the 360-degree view of your business?

The answer is seemingly simple: There’s no management without measurement. To execute on enterprise strategy,

business and IT executives need a business-focused, strategic, and pragmatic way to measure their finances and

operations. Without such measurements — most often achieved by enterprisewide BI deployments — businesses won’t

be able to link operational results to strategy (37% of survey respondents still do not use BI at an enterprise level).

Organizations will also find it difficult to get a coherent view of their internal and external processes, customers,

logistics, operations, and finances.

Multiple conversations with Forrester clients show that most firms use only 1% to 5% of the data available to them.

What if that number doubled or tripled or quadrupled? The possibilities of the new insights would be virtually endless.

There’s a treasure chest of truly amazing examples out there, such as saving lives; preserving natural resources; fighting

crime; and improving profitability, customer satisfaction, and employee productivity — all based on better and faster

insights.

• Saving lives. A provider of healthcare BI and data solutions runs customized predictive modeling algorithms to

identify those patients that could benefit most from a targeted management program. By utilizing agile DBMS

technology tuned for analytics, the solution queries that used to take a day now return results within

milliseconds. This significantly shortens the cycle of adjusting patient management programs, which can

sometimes mean a difference between life and death.

• Understanding and improving customer profitability. A telephony vendor was able to improve customer

service via transparent call detail record visibility into the more than 2 million connections they manage every

day. Faced with customer demands that were outpacing the application, the vendor needed a database that would

let customers directly query the raw CDRs (Call Data Records) for any period of time. The database had to let the

data warehouse store at least two years’ worth of CDRs — or about 1.2 billion records, each containing about 200

pieces of information — and deliver responses in 10 seconds or less for 90% of queries. By implementing state-of-

the-art analytics, the vendor was able to run queries up to an order of magnitude faster and perform near real-

time analysis. The new system eliminates the need for aggregate data and enables faster, more granular analysis

and to cost-effectively store and query two years’ worth of CDRs (versus 90 days). For example, it has cut the time

to perform a critical monthly cost analysis of toll-free call traffic from hours to seconds.

• Improving employee productivity. A pharmaceutical company uses BI for stretching its IT resources and

increasing employee productivity sometimes even by an order of magnitude. This company realizes these gains

because its BI platform automates the capture of critical research information and processes high volumes of data

accurately — with minimal ongoing maintenance required. The ability to design questionnaires quickly and

easily has helped this business roll out new research projects even faster — with some studies taking only a few

weeks to launch. The value of accelerating the launch of a major, multiyear medical research project is significant,

particularly for study sponsors in the pharmaceutical industry — where blockbuster drugs can generate millions

of dollars a day.



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• Expanding a 360-degree single view of a customer into 720 degrees. Studies have found that if one person

defects from a product or service, other customers with social connections to that person may also. To capitalize

on this study, a financial services firm is mining point-of-sale transactions at a massive scale to identify these

social relationships based on card usage patterns to conduct targeted retention campaigns. As a result, it is

increasing revenue and profit.

But these new insights and intelligence require new approaches. The days of one-off, so-called “homegrown” BI

applications are gone. Modern large, complex, heterogeneous, global enterprises need “industrial strength” BI platforms

and applications to help them handle:

• Increasing data and content volumes. It’s not just that we generate large volumes of data in our transactional

applications like enterprise resource planning (ERP) as well as from smart devices like utility meters and cell

phones, social media outlets like blogs and wikis, but we also replicate this data many times over. We replicate

data for backup and disaster recovery, analytical applications (so that they do not interfere with the operational

apps), and regulatory purposes such as the 30-year record retention requirement for US-based financial

institutions. As a result, analysis that could be performed in spreadsheets or homegrown desktop-based BI

applications a few years ago now requires petabyte-size data warehouses and industrial-strength BI applications.

• Complex regulatory reporting requirements. The number of regulations required to keep the increasingly

complex global economy transparent to ensure legal compliance will continue to skyrocket. BI applications,

reporting, and analytics are the key enablers to support regulatory requirements like the Sarbanes-Oxley Act

(SOX), Basel III, and International Financial Reporting Standard (IFRS) in the financial services sector; the

Health Insurance Portability and Accountability Act (HIPAA) and pay-for-performance in healthcare; and

hydrocarbon accounting in oil and gas, transportation, and manufacturing industries. Like it or not, most

enterprises have no choice but to comply and implement these tools.

• Increasing complexity of global operations. The days of operating in a niche market have come and gone for

enterprises. Most are expanding into global markets, diversifying their products and service lines to spread the

risk and increase the number of lucrative business opportunities. As these businesses grow, both organically and

via M&A, it gets increasingly more challenging — without enterprise-grade BI platforms — for management to

keep a bird’s eye view on diversified, global, heterogeneous, multifaceted operations.

But even more importantly, for many large enterprises, BI remains and will continue to be the “last frontier” of

competitive differentiation. No one said it better than Walter Wriston, chairman of Citigroup in the 1980s, that:

“information created from a financial transaction will be more valuable than the execution of the actual transaction

itself.” Indeed, while a transaction occurs only once, the information about that transaction can be leveraged and reused

numerous times for better insights into customer-facing processes such as sales and marketing activities and in internal

processes such as capacity, product, and resource planning (see Figure 1).



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Figure 1

The Majority Of BI Users Are Using BI For Better Insights And More Effective Decisions

Base: 291 IT decision-makers

Source: A commissioned study conducted by Forrester Consulting on behalf of HP, March 2012

Why Do Many BI Initiatives Pose Numerous Challenges?

However, a perfectly successful BI environment with only few glitches often remains an elusive goal (see Figure 2). One

of the main causes: Earlier-generation BI approaches and technologies seem to have a serious side effect — a constant

backlog of BI requests (30% of survey respondents reported that their BI requirements are not addressed on time). It’s a

classical FIFO (first in, first out) queue problem, where new BI requests come in at a higher rate than they can be

addressed and fulfilled. Here are some of the reasons why:

• Implementing BI requires using best practices and building upon lessons learned. Using best practices and

learning from past mistakes make a significantly greater contribution to successful BI implementations than

technology and architecture alone, for several reasons. First, end-to-end BI architecture and implementations

require closely coordinated integration efforts to put together multiple components like data sourcing,

integration, modeling, metrics, queries, reports, dashboards, portals, and alerts. Second, it’s tricky for anyone to

define future BI requirements, as the business and regulatory climate may change significantly. Last, but not least,

if you get three people in a room, you’ll typically get five opinions on how best to derive, calculate, and use

metrics like customer profitability. As a result, creating successful BI strategies, processes, and applications takes

years of experience — and, alas, learning from failed implementations.

• Business and IT BI stakeholders are not always perfectly aligned. “Just get it done” is the new mantra in the

21st century, when delaying or hesitating even for a few minutes can mean a lost deal or an unhappy client.

Therefore, business users of BI applications mostly care about their clients; they need to react to the clients’

needs, even when and if it means getting the answers or getting the job done with whatever means they have at

their disposal. And whether these means are bypassing enterprise standards — well, that often takes secondary

priority — remember, customers first! While IT workers obviously understand and fully support the priorities of

their business partners, they often have conflicting priorities, goals, and objectives, such as requirements to

standardize and rationalize tools and platforms, minimize operational risk, and plan for the future.

• All enterprises are different. If one believes in the point made earlier that information provides a key

competitive differentiating edge, then using an off-the-shelf canned BI solution would not provide that

advantage. Hence, very few enterprises use packaged BI applications without at least some kind of customization



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and modification, and many still build their BI applications from scratch — custom coding (89% of survey

respondents moderately or heavily customize their BI applications).

• BI technologies and processes have not kept pace with business realities. In the past 10 years, enterprises pretty

much solved the problems that plagued typical BI implementations in the 1990s: data and information silos and

unstable, poorly scalable BI technologies. But while earlier generation BI technologies have matured into

industrial-strength solutions — function-rich, scalable, and robust — they have largely failed to address one

simple, pragmatic business reality: the need for flexibility and agility. In the past few years, businesses have begun

to realize that their enterprise-standard BI approaches, while suited to addressing most current business

requirements, are neither flexible nor agile enough to react and adapt to information requirements that seem to

change with ever-increasing speed. Additionally, on the infrastructure side, it is only in the past two years

Forrester has seen a considerable churn in converged infrastructure (CI) technology. Forrester expects this pace

to continue in 2012. Vendors will focus on improving the integration of storage and network virtualization and

increasing integration of the systems-level virtualization capabilities with higher level management software. This

combination of improved integration and lower operating expenses will benefit future analytics and BI initiatives.

• The BI architectural stack remains quite complex. In an average large enterprise operating several business

lines in multiple regions, the number of components that need to be cobbled together to build complete end-to-

end BI solutions sometimes reaches a few dozen. All of these components rarely come from the same vendor, and

even when they do, chance are, some of the components were recently acquired and are not seamlessly

integrated. Integration challenges first start with having to extract, integrate, reconcile, and aggregate data from

dozens, sometimes hundreds — literally — data sources (85% of survey respondents use more than 10 data

sources, 48% more than 50, and 24% more than 100). Next, even if a centralized enterprise data warehouse

(EDW) is part of your current and future strategy, it’s always a light at the end of the tunnel, never completely

finished (39% of survey respondents have four or more data warehouses/data marts using four or more different

platforms). And last, but not least, using the best BI tool for each specific use case is still a prevalent strategy in

many enterprises, and therefore IT has to deal with supporting and integrating multiple BI platforms (see Figure

3).

All of the above contribute to one undisputable fact: BI requirements change faster than IT can keep up. Even if you

create and deploy BI applications by the book, following all known best practices, it still can be an unattainable goal to

enable your BI application to react on a dime to frequently changing business requirements. Whereas one can expect at

least several years’ life span out of ERP, CRM, HR, and financial applications, with some major and minor

enhancements along the way, a BI application can become outdated the day it is rolled out. Even when it takes mere

weeks to design, build, and implement a BI app, that might still be too long. Just within that short period of time, the

world may have changed completely. A sudden M&A event, a new competitive threat, new management structure, and

new regulatory reporting requirements are but just a shortlist of the reasons why the traditional BI application’s life

span can be days and weeks, as opposed to months or years.



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Figure 2

The Majority Of BI Key Stakeholders Feel That Their BI Maturity And Success Leave Room For Improvement

Base: 291 Business intelligence decision-makers


Figure 3

Adopting The Best Tool For The Job Can Trump Enterprise Standards; Most Enterprises Use Multiple BI Platforms



Move Forward With Successful BI Initiatives Using A Combination Of Best Practices And Next-Generation Technologies

Forrester recommends a radical shift in BI strategies to make BI implementations more successful so that they can

effectively support all business decisions — strategic, tactical, and operational. While Forrester will never state that

agility will cure all of BI’s current ills, it certainly provides the most important best practices and leverages a key

capability of the underlying BI technology to help close the gap that earlier-generation BI processes and technologies

create. Don’t misconstrue, however, Forrester’s recommendation for just Agile software development methodology,

which is nothing new. But Agile development by itself is not enough for BI, so Forrester also recommends adopting

multiple best practices and next-generation technologies to make BI more flexible. Forrester defines Agile business

intelligence as:



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“An approach that combines processes, methodologies, organizational structure, tools, and technologies that

enable strategic, tactical, and operational decision-makers to be more flexible and more responsive to the fast

pace of changes to business and regulatory requirements.”1

While creating a successful earlier-generation BI environment is challenging, ensuring that your Agile BI has all of the

right key success factors requires significant expertise. Before charging full speed ahead into the Agile BI journey,

Forrester recommends engaging a partner that has a proven track record of successful Agile BI implementations.

Start By Adopting Agile BI Best Practices Start by adapting your organizational structures and enterprise culture for agility. No technology or processes can

address BI challenges if a company’s organizational structure and enterprise culture are not already on firm, agile

ground (see Table 1). Once the organization is aligned for agility, the next step is to consider and implement Agile BI

processes (see Table 2).

Table 1

Agile BI Organization Best Practices

Best practice Why it is important Recommendations

Insist on business

ownership and

governance of BI.

Business ownership of BI initiatives often

translates into more successful BI

environments.

Demonstrate BI ROI to business leaders.2

Take Forrester’s BI maturity self-assessment and

benchmark against peers and competitors.3

Emphasize

organization and

cultural change

management.

Humans innately resist change. Forcing

decision-makers and knowledge workers

to step outside of their comfort zones —

e.g., using familiar BI applications like

spreadsheets — is a big change.

Foster a culture that makes change easier: set expectations

upfront, communicate often, collect feedback, etc.

Make BI usage part of individual performance metrics,

and even link it to compensation incentives.

Decouple data

preparation from data

usage processes in end-

to-end BI cycles.

Data preparation requires more planning

and control than data usage; the two do

not necessarily have to be tightly coupled.

Create separate, loosely integrated organizational

structures: put one in charge of data preparation, another

in charge of data usage.4

Emphasize IT ownership of data preparation processes

rather than business ownership of data usage processes.

Approach and treat

front- and back-office

BI requirements and

users differently.

Front- and back-office BI applications

have different tolerance levels for risk,

latency, planning, and data accuracy.

Create different sets of policies and guidelines for

approaching BI projects in the front and back offices.

Create special policies and guidelines for approaching BI

projects that span front- and back-office processes,

especially untamed processes.



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Establish hub-and-

spoke organizational

models.

Both extremes — organizational/data silos

or a totally centralized BI environment —

have multiple negative implications.

Create a set of policies and guidelines that dictate which

data entities (and their ownership and governance) belong

in the centralized (hub) area and which belong in satellite

organizations (spokes).

Base these policies on multiple parameters, such as how

mission critical a data entity is or whether multiple units

across the enterprise share its use.

Source: Forrester Research, Inc.

Table 2

Agile BI Processes Best Practices

Best practice Why it is important Recommendations

Use a combination of

top-down and bottom-

up approaches to BI

design and

applications.

Neither approach is perfect:

A bottom-up or horizontal approach requires

building an enterprise data warehouse and

then applying it to reporting and analytical

applications. This is a monster effort that often

takes years and has questionable ROI.

A top-down or vertical approach clearly links

strategy, goals, and metrics to data but often

creates redundant efforts — many of the same

data entities need to support various metrics.

Use a bottom-up approach for all data preparation

processes: sourcing, extracting, integrating, cleansing,

reconciling, and modeling.

Use a top-down approach for all data usage processes:

building reports and dashboards that link strategy to

goals, goals to metrics, and metrics to data.

Use Agile development

methodologies.

Traditional waterfall design and development

methodologies are too slow and too inflexible

for BI.

Leverage Forrester’s Agile development best

practices.5

Support the Agile development methodology with an

Agile architecture and technologies.

Enable BI self-service

for business users.

Even the best planning efforts can’t predict

future BI usage patterns.

Implement self-service BI tools and technologies.6

Ensure that at least 80% of all BI requirements can be

implemented by business users themselves.

Source: Forrester Research, Inc.

Sound challenging? It is. That’s why Forrester seldom recommends implementing these state-of-the-art, agile, next-

generation BI environments on your own. As covered in the earlier section of the study, the BI journey is often

daunting, with multiple perils. Unless you have accumulated dozens — and even better, hundreds — of best practices,

lessons learned, pitfalls to avoid, we can guarantee that you will learn from your own mistakes. Having even a few BI

initiatives under your belt is never enough. These hundreds of best practices are the realm of professional consultants

and professional systems integrators who individually have accumulated dozens, and their firms — cumulatively —

hundreds and thousands of these lessons (47% of survey respondents use systems integrators and 41% outsource all or

parts of their BI initiatives).



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Base Agile BI On Next-Generation BI Technologies While some of these best practices can stand on their own, others require the application of next-generation BI

technologies. In the past, BI vendors and BI application developers focused on business and operational functionality

and architectural robustness. In most cases, these features have become commoditized. BI practitioners now need to

concentrate on next-generation technologies. Forrester categorizes these technologies as “agile” and defines four major

subcategories of agility: automation, pervasiveness, unification, and BI without limitations. Each of these new

technologies can stand on its own and is independent of the others, although some organizations have tackled them in

the following order:

• Automated BI. First and foremost, firms need to automate BI processes and steps as fully as possible to eliminate

manual work and free up valuable human resources for analysis and other value-added tasks.

• Unified BI. It’s quite a paradox that, as BI initiatives attempt to bridge data and information silos, BI technology

itself is not unified. Today, different BI tools address various BI use cases. Next-generation BI brings all of them

together in a unified platform.

• Pervasive BI. After automation and unification, companies should address pervasiveness. How? Make enterprise

BI applications available wherever and whenever strategic, tactical, and operational decision-makers need to

analyze information, make decisions, and act.

• BI without limitations. Last, but not least, earlier-generation BI applications have too many limitations. For

next-generation BI to be able to face the challenges of the modern business world — a world that does not fit into

nice, neat models — it must operate on information without any borders or restrictions.7

While it is beyond the scope of this study to cover all next-generation, Agile BI technologies, one deserves special

attention. BI appliances — preconfigured hardware/software combinations — optimized and tuned for DW and BI

address many of the Agile BI requirements (see Figure 4). Since procurement and deployment cycles are shortened, and

long-term total cost of ownership can be reduced, BI appliances have a role in increasing BI pervasiveness.

Preconfigured and integrated components help with BI automation and unification. And last, but not least, when BI

appliances include next-generation BI technologies, like BI specific DBMS, they also address many of the limitations of

earlier generation BI tools.8

Figure 4

BI And DW Appliances Can Address All Four Requirements For Agile BI





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KEY RECOMMENDATIONS

Based on findings in this study and other extensive Forrester client interactions (including thousands of client inquiries and

numerous surveys) Forrester finds that enterprises are faced with four options when seeking to raise their BI and DW

environments and initiatives to the next level. These four options include:

• #1 — Custom coding BI applications. Unless you are indeed in the business of analytics, custom coding BI

applications is best left for the professionals. There are plenty of robust and mature off-the-shelf BI and DW

tools out there. You do not need to reinvent the wheel unless your BI requirements are indeed extremely

unique.

• #2 — Leveraging BI tools embedded in your ERP applications. For smaller businesses, especially those that

run their entire operations on a single integrated ERP package (including financials, HR, supply chain, sales,

marketing, etc.), there’s probably little reason to look beyond BI tools that come embedded with these

packages. But once such businesses grow, expand, and diversify, they inevitably start using multiple, often

heavily customized ERP applications, frequently supplemented by multiple custom build operational apps. At

some point in that growth, the attractiveness of embedded BI tools is severely undercut.

• #3 — Integrating best-of-breed BI components. This is an option that all large and growing enterprises

eventually face. Once senior management is bought into the notion of BI as a key competitive differentiator,

nothing but best-of-breed will do. And if you have recruited, trained, and retained top BI talent with many

successful BI initiatives under their belt — it’s a great place to be. However, as described in the earlier sections,

integrating all of the BI components from scratch is not a quick and easy, inexpensive proposition. Forrester

recommends working with a vendor that has proven success in recommending what are the right “best-of-

breed components” for a particular scenario/workload, since one size fits all is never an optimal path in BI.

• #4 — Packaged BI solutions based on solution “accelerators” and best-of-breed BI components. Leading

consultants and systems integrators with the advantage of having built multiple BI solutions across industries,

business domains and regions, often package or “productize” collateral accumulated in such engagements

into so-called solution accelerators. These often include logical and physical data models, standard source

systems connectors, typical metrics, and pre-built reports and dashboards. Other characteristic accelerators

may include conversion utilities (from an older BI platform to a new one) and pre-built standard test scripts.

Anecdotal evidence suggests that solution accelerators can cut 20% to 50% of initial design, architect, build,

and implement efforts. Forrester recommends working with a trusted service, software, and infrastructure

provider with broad and deep expertise and consistent success record in BI and strong relationships with other

vendors in the data center.

The following table illustrates under what circumstances Forrester Research recommends these four options:

Enterprise size

Business complexity

Effort Time to deploy

Option 1 — Custom coding BI applications Any Unique High Longer

Option 2 — Leveraging BI tools embedded in your ERP

applications

Small Low Low Shorter

Option 3 — Integrating best-of-breed BI components Medium,

large

High High Longer

Option 4 — Packaged BI solutions based on solution

“accelerators” and best-of-breed BI components.

Medium,

large

High Medium Shorter



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Appendix A: Methodology

In this study, Forrester conducted an online survey of 291 respondents in the United States, United Kingdom, France,

China, and India to evaluate technology and best practices surrounding business intelligence (BI). Survey participants

included decision-makers in information technology and business roles. Questions provided to the participants asked

respondents to discuss organizational uses of BI, tools/platforms/applications related to BI, initiatives, requirements,

and future plans. The study began in February 2012 and was completed in March 2012.

Appendix B: Study Demographics

Figure 1

Respondent Regions And Enterprise Side



Figure 2

Respondent Revenues And BI Roles





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Figure 3

Respondent Roles



Appendix C: Endnotes

1 Source: March 31, 2011, “Trends 2011 And Beyond: Business Intelligence” Forrester report.

2 Source: August 25, 2009, “The Business Case For BI: Now More Critical Than Ever” Forrester report.

3 Source: December 21, 2011, “Update 2011: Forrester's BI Maturity Assessment Tool” Forrester report.

4 Source: July 22, 2011, “Agile Business Intelligence Solution Centers Are More Than Just Competency Centers”

Forrester report.

5 Source: February 8, 2012, “Justify Agile With Shorter, Faster Development” Forrester report.

6 Source: October 26, 2010, “Empower BI Heroes With Self-Service Tools” Forrester report.

7 Source: May 27, 2011, “It's The Dawning Of The Age Of BI DBMS” Forrester report.

8 Source: May 27, 2011, “Forrester's Business Intelligence DBMS Effort Estimation Model” Forrester report.

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