Business Intelligence for IT
“The ability to learn faster than your
competitors may be the only sustainable
competitive advantage.”
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Arie de Geus
“The Living Company,” 1997
The renowned Dutch business strategist got it right. In today’s world, tangible business advantages are fleeting at best. Repeatable success depends largely on the ability to adjust your course quicker than your competition can adjust theirs. A prerequisite to that course correction is, of course, an understanding of exactly which adjustments need to be made. In the business world, the means to that end is “Business Intelligence” or “BI” for short. Quite simply, BI is the creation of “intelligence” about how well the “business” is working.</p><p>It is important to note that BI is not itself a “Killer Application.” Rather, a BI platform provides a foundation for collecting and managing vast amounts of information within a comprehensive infrastructure to enable multiple “Killer Applications,” each targeted at answering a specific business question
“Guessing what the pitcher is going to throw is
80% of being a successful hitter.
The other 20% is just execution.”
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Hank Aaron
Baseball Hall of Famer
Hammerin’ Hank was obviously a pretty good guesser. Imagine, however, if Aaron not only had ready access to the pitcher’s history–with corresponding data about the pitcher’s wind-up, glove angle, etc.–but also had a means to analyze that data to correctly predict the next pitch. How many more home runs he could have hit if he’d known what pitch was coming?
Likewise, a BI platform not only provides a company with access to pertinent data; it also provides actionable information by performing “analytics” on the available data.
“How to pull ahead of the pack? Become an
analytics competitor: Use sophisticated
data-collection technology and analysis to
wring every last drop of value from all your
business processes.”
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Thomas Davenport
“Competing on Analytics,” Harvard Business Review, 2006
In his “Competing on Analytics” article, Thomas Davenport makes a solid case for centering a business around data analytics and cites multiple examples of companies that have had demonstrable success with that strategy. For example, Capital One’s information-based strategy is responsible for at least a 20 percent growth in earnings per share every year since the company went public. Marriott’s revenue opportunity management efforts increased actual revenue as a percentage of optimal rates from 83 percent to 91 percent. Properly executed analytics efforts can directly improve a company’s bottom line.
Such analytics applications are built upon BI platforms and represent an increasingly significant percentage of the corporate IT budget. Indeed, the Gartner EXP 2006 CIO Survey identified BI applications as the CIO’s single highest priority.
Unfortunately, the CIO’s organization is itself seldom considered an equal as a “real” business unit. While IT groups are generally responsible for bringing BI to the rest of the corporation, they are often the last in line to reap any of the benefits themselves.
“A key component of the enterprise
architecture value proposition is the alignment
of implementation (largely IT, but increasingly
business process) with the enterprise’s
business strategy.”
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Gartner
“Enterprise Architecture Research Agenda,” 2006
BI, however, is not just for everyone else. “BI for IT,” often using Enterprise Architecture (EA) efforts as a foundation, can internally optimize IT’s business processes and initiatives and can help align IT with corporate business objectives. The potential usages of BI technology within the CIO’s organization are numerous: cost optimization, asset maximization, lifecycle management, service delivery, impact analysis, gap analysis, as-is/to-be transformations, etc. Such BI analytics should be an integral part of the CIO’s EA dashboard, like the one in figure 1.
In fact, not only should IT’s BI requirements be considered on par with the needs of other business units, a good argument can easily be made that IT should actually be a first among equals. An Enterprise Architecture represents the business as a whole. Properly constructed, EA should include all of the important data, applications, infrastructure components, processes, and strategies that define the business. By definition, then, EA is cross-functional. Since IT is responsible for managing many of the assets used by other business units, the EA platform provides an excellent starting point for corporate BI efforts as well as enabling IT’s own internal BI initiatives.
Thus, both EA & “BI for IT” are foundational to corporate BI requirements. By first enabling BI within the CIO’s office, IT can more easily offer BI services to other business units and can even package some of those services for easier consumption by others.
“Competing on analytics means
competing on technology.”
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Thomas Davenport
“Competing on Analytics,” Harvard Business Review, 2006
Davenport defines three primary technology requirements to compete on analytics. These include sufficient computing hardware, good BI software and a solid data strategy.
The hardware requirement is the easiest to address. While cost is definitely a factor, sufficient hardware to perform complex BI analytics is generally available. As for the software requirement, excellent EA/BI solutions are also available.
The data strategy, however, is more problematic.
“In God we trust; all others bring data.”
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W. Edwards Deming
American Statistician
All analytics are data-limited. They are only as good as the scope, quality and timeliness of accessible data.
The EA domain can require massive amounts of data in order to perform sufficiently interesting analytics. These include both tangible assets (people, locations, computers, etc.) and intangible elements (goals, processes, strategies, etc.). This data often exists in numerous independent silos, scattered across multiple systems and applications in multiple locations, stored in widely variant formats, and managed by multiple people.
While the efforts to define, collect and manage this data are significant, the benefits can far outweigh the costs. Importantly, however, caution must be exercised to guarantee that the data collection process is easily repeatable. A single snapshot of corporate data is of limited use to perform serious analytics.
Obviously, some software assistance from the EA platform is necessary. Optimally, such software will provide a non-intrusive, repeatable data collection and maintenance capability. Since some connective data may not even exist elsewhere in the organization, the EA platform must also be capable of being the source-of-record for selected data elements in addition to being an aggregator of externally maintained data.
The good news, again, is that much of the data maintained by a good EA platform will be quite usable–and absolutely necessary–throughout the organization to support corporate BI efforts.
“The lines between corporate
performance management (CPM) and
business intelligence (BI)
are blurring.”
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Gartner
“Hype Cycle for BI and CPM,” 2006
Many organizations are embracing Corporate Performance Management (CPM) at the senior executive level. CPM enables organizations to track operational business activities against financial performance and supports the creation of appropriate improvement strategies. Gartner has recently started using “BI-CPM” and “process-centric BI” to imply the usage of BI’s analytical tools to provide forward-looking insights into the daily management of business objectives. Thus, corporate BI efforts are themselves foundational to CPM.
BI is not only an important service provided by IT; it is also intrinsically essential to the IT organization itself. Built on top of a solid Enterprise Architecture platform, “Business Intelligence for IT” also provides an excellent foundation for corporate BI and CPM efforts.
Bill Cason is the CTO of Troux Technologies, an EA solution provider.
