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19/01/2010
BI Opportunities Outpace Organizatio…
BI Opportunities Outpace Organizations’
Ability to Use It
Information Management Special Reports, November 27, 2007
Boris Evelson
Business intelligence (BI) sits at the top of the IT priority list for many enterprises. Enterprises
that haven’t paid enough attention now see a need to act, and those that have kept up with
BI want to consolidate their siloed implementations. The promises of BI attract any
organization, but how do you get started? Enterprises face multidimensional choices, and they
cannot start with vendor selection. Tasks such as data governance, matching requirements
with logical architectures and picking an experienced architect and implementer should be at
the top of the list.
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Business processes have become automated enough for business users to start thinking
ambitiously. The opportunity for BI innovation and differentiation appears at every turn constantly proven by many emerging companies popping up left and right. To protect your BI
investment, we believe you should watch and consider the following major market trends:
Convergence of structured and unstructured content analyses. Modern analytics
blends unstructured data with traditional structured data to give users the ability to detect
patterns and run what-if scenarios. Consider retail customer segmentation: The old way
meant combining customer sales with customer and store demographics. Today retailers on
the cutting edge realize that adding comments and complaints from email and call centers will
significantly enhance their segmentation analysis. You could always pore through text
manually and code it along criteria you developed, though few ever do because of the time
and effort it requires. BI calls for these connections to be automated, so analysts can focus
on turning insight into action, instead of hunting through multiple mail systems, phone
systems and enterprise applications.1
Combining data with process awareness. BI and business process management (BPM)
have always addressed a common need separately, bringing people and information into
alignment. The operational improvement cycle - learn, design, inform, act and repeat focuses on increasing efficiency. But organizations with ambitious strategic goals need to be
more than efficient - they need to be effective. BPM might make processing a customer
credit application less expensive, but analytics can use sophisticated customer segmentation
to increase cross-sell and up-sell ratios in real time during a customer interaction - when it
counts. Expect solutions to combine data and process dashboards, event-based actions
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triggered by data conditions that initiate a business process, and traditional BI layers
(reports, dashboards and analytics) responding seamlessly to business processes across
multiple systems.2
Entry of relational database alternatives. The relational database management system
(RDBMS) was originally designed to execute small transactions, not to examine large volumes
of data with BI queries. Over the years the technology has caught up, but RDBMSes still
have to shoehorn two personalities into one body. Alternate DBMS models will increasingly
enable BI for two big reasons: 1) removing the bias between structured and unstructured
data, and 2) OLAP query processing.
Explosion of dimensions to support future BI analysis. Traditional cross-tabular
reporting quickly becomes useless after more than a few dozen dimensions, no matter how
sophisticated the “slicing and dicing” interfaces are. One possible approach is so-called
“guided analytics,” where users can rapidly mix and match dimensions interactively. Another
is visualizing patterns graphically, giving users a big-picture view of extremely large data
matrices for identifying trends.
Figure 1: How to Choose a Vendor Category
Define the Architecture for All of the Layers of the BI Stack
Do not overlook the rest of the necessary BI components, which may or may not necessarily
be considered part of a BI strategy. This includes metadata, data integration, data quality,
data modeling, analytics, centralized metrics management, presentation (reports and
dashboards), portals, collaboration, knowledge management and master data management.3
Many of these components, while not necessarily BI driven, or even BI related, help determine
the success of BI implementations.
References:
1. IW strategy and architecture plan must break down the wall between structured data and
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unstructured content to ensure delivery of all relevant information. See the June 20, 2007,
“Information Should Be Front And Center In Information Workplace Strategies” report.
Confirming the trend, Business Objects announced its intent to acquire Inxight Software in
May. See the May 31, 2007, “Business Objects Buys Into Unstructured Information With
Inxight Software” report.
2. Most visionary business process management (BPM) vendors now find that they’ve been
defining their own market too narrowly. Not only do enterprises need to optimize their
business processes, they also want to optimize their business results. As TIBCO recently
demonstrated by buying Spotfire, the next strategic move for organizations seeking business
optimization will be to combine BI and BPM for visualizing process metrics and business
results together, and even more importantly, to turn transactions into decisions. See the
September 19, 2007, “From BPM To Business Optimization” report.
3. The “layers” of the BI stack include many other technologies such as metadata; extract,
transform, and load (ETL); data quality and master data management. See the July 11, 2006,
“Getting Your Arms Around Metadata” report; see the May 2, 2007, “The Forrester Wave:
Enterprise ETL, Q2 2007” report; see the January 17, 2006, “The Forrester Wave:
Information Quality Software, Q1 2006” report; and see the November 10, 2006, “Introducing
Master Data Management” report.
Boris Evelson is a princiapl analytst with Forrester Research specializing in business
intelligence. Evelson is one of the driving forces behind Forrester's offerings for
information and knowledge management professionals. His current research focuses on
some of the latest trends in BI, such as convergence of multiple, formerly separate
disciplines of structured and unstructured data, process and data intelligence, real-time BI
and many others into overall enterprise effectiveness and optimization. û
For more information on related topics, visit the following channels:
Business Intelligence (BI)
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