The document discusses the evolution of business intelligence from silos to centralization to agility. It notes that agility is key for efficient BI processes to keep pace with fast business changes. Traditional approaches like waterfall development don't work well for automating "untamed" business processes that require new agility. The document recommends treating front and back office BI differently and using a combination of top-down and bottom-up approaches. It advocates establishing self-service BI and agile development methodologies to support unpredictable BI needs.

2. …“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”. Forrester on Business Intelligence, 2011

3. • More than 49% of surveyed companies have concrete plans to expand
their BI solutions by 2014
• Enterprise BI maturity levels are still below average (2.75 on a scale
of 5, a modest 6% increase over 2009)
• Lack of agility and flexibility leads to unsuccessful BI initiatives
• Implementing BI requires using best practices and building upon
lessons learned
• BI technologies and processes have not kept pace with business
realities
• Centralization has not led to agile, streamlined BI implementations

4. • Agility is the key to efficient business intelligence processes
• Untamed business processes create challenges for standard BI
approaches:
• Untamed processes are often invisible
• Traditional SDLC doesn’t work well for automating untamed
processes
• Untamed processes often require new approaches and
technologies

5. Business Intelligence Is Moving
From Silos - To Centralization - To Agility
1990s 2000s 2010s
Silos Centralization Agility
Forrester, 2011

6. Business Process Example Why Agile process is needed
Risk management Looking for trends of • Process involves complex transactions and exceptions
salespeople violating discount • Correlation between discounts and individual contract exceptions
policies may be unpredictable and on many different levels of a contract
Sales Managing major accounts • Salespeople must compete against other companies for retailer
shelf space and define the space their company has already secured
• Salespeople may not know until they are in the client’s office what
competing products the client is considering
Sales and marketing Analysis of competitive new • Sales and marketing staff often needs to react to unexpected
products, pricing, and competitive threats
promotions • It’s difficult to predict all possible future competitive threats
Paralegal Case support • Case workers often need to analyze multiple cases with disparate
attributes for similarities and patterns
• It’s difficult to predict all possible questions a lawyer might ask
when analyzing a case
Drug research Patient trials • Researching, investigating, and correlating drug treatment with
patient outcomes requires a complex, multidimensional analysis with
hundreds of potential cause/effect variables
• It’s difficult to predict unexpected patient outcomes
that will require a cause/effect analysis
Forrester, 2011

7. Best practice Why it is important Recommendations
Requirements for Some Business Processes Can Change Daily
BI Business ownership and BI project ownership translates into • Demonstrate BI ROI to business leaders
governance more successful BI environments • Run a BI maturity self-assessment and benchmark against
peers and competitors
Emphasize organizational Forcing decision-makers and • Foster a culture that makes change easier: set
and cultural change knowledge workers to step outside of expectations up front, communicate often, collect
management their comfort zones is a big change feedback, etc.
• Build and use BI on BI
• Make BI usage part of individual performance metrics, and
even link it to compensation incentives
Decouple data Data preparation requires more • Create separate, loosely integrated organizational
preparation from data planning and control than data usage structures: put one in charge of data preparation, another
usage processes in end- in charge of data usage
to-end BI cycles • Emphasize IT ownership of data preparation processes
Approach and treat front Front- and back-office BI applications • Create different sets of policies and guidelines for
and back-office BI have different tolerance levels for approaching BI projects in the front and back offices
Forrester, 2011
requirements and users risk, latency, planning, and data • Create special policies and guidelines for approaching BI
differently accuracy projects that span untamed front- and back-office processes
Establish hub-and-spoke Both extremes — organizational/data • Create a set of policies and guidelines that dictates which
organizational models silos or a totally centralized BI data entities belong in the centralized (hub) area and which
environment — have multiple negative belong in satellite organizations (spokes)
implications • 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

8. Best practice Why it is important Recommendations
Use a combination of Neither approach is perfect: • Use a bottom-up approach for all data
top-down and bottom-up • A bottom-up or horizontal approach preparation processes: sourcing, extraction,
approaches to BI design requires building an enterprise data integration, cleansing, reconciliation, and modeling
and applications warehouse and then applying it to • Use a top-down approach for all data usage
reporting and analytical applications. processes: building reports and dashboards that link
• A top-down or vertical approach clearly strategy to goals, goals to metrics, and metrics to
links strategy, goals, and metrics to data data
but often creates redundant efforts
Use Agile development Traditional waterfall design and • Leverage Agile development best practices
methodologies development methodologies are too slow • Support the Agile development methodology with an
and too inflexible for BI Agile architecture and technologies
Enable BI self-service for Even the best planning efforts can’t predict • Implement self-service BI tools and technologies
business users future BI usage patterns • Ensure that at least 80% of all BI requirements can
Forrester, 2011 be implemented by business users themselves

9. Automated Unified
Automated information discovery Logically unified data sources
Making BI contextual Data and content
Full BI life-cycle automation Disk and streaming
BI on BI Historical, current, and predictive
Suggestive BI Complex data structures
Automated decision management Metadata
Agile BI
Pervasive Limitless
BI within processes
BI within an information workplace (IW)
Adaptive data models
Self-service
Unlimited dimensionality
Mobile
Exploration and analysis
Offline/disconnected
On-demand/SaaS

10. 1. Place BI agility and flexibility on an equal
footing with risk management
2. Don’t fight people from the business who want
to wrest control of BI away from you: rather,
support them
3. Look for experience with next-gen and agile BI
when selecting a systems integrator