Moving BI to the Enterprise
Information Management Magazine, September 2005
The purpose of business intelligence (BI), as conceived in the early 1990s, was to give business users direct access to information instead of having to go through the IT department to obtain custom reports or views of information. The idea was to empower business users by allowing them to query a repository of integrated data (i.e., a data warehouse or data mart) and create their own reports. Giving business executives, managers and staff self-service access to information would enable them to avoid the backlog in the IT department and enhance their ability to make decisions, create effective plans, and optimize processes and performance.
In reality, however, self-service BI proved overwhelming for all but the most sophisticated power users. Most users found the original query, reporting and analysis tools too complex or time-consuming to use. Because they didn't use the tools extensively, they would forget how to log on or use various functions and features. They often spent too much time looking for the right report among hundreds or got lost in an endless series of drill-downs and dimension lists. As a result, BI tools replaced the IT department as the major barrier between users and the information they needed to make sound, timely decisions.
In the past five years, many BI tools vendors have responded to these complaints by making their product lines more friendly to the majority of users in the enterprise, not just power users. Consequently, they've rediscovered the value of standard and parameterized reports, and added dashboards and analytic applications that provide a more intuitive interface, dynamic customization, guided analysis and collaboration features.1 The result is that many organizations can now confidently extend the benefits of BI tools to a majority of their employees throughout the enterprise.
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Analytical Silos
Scattershot Deployments. However, despite the popularity of business intelligence, most organizations have not deployed BI tools and solutions in a systematic or consistent manner. They have allowed individual workgroups, departments and divisions to build their own data warehouses and data marts, purchase their own BI tools and define key metrics, data elements and business views in unique, non-standard ways. Thus, although BI usage has increased overall, BI deployments remain small and disconnected. Many organizations today are riddled with these "analytical silos."
Even when an organization has resisted delivering BI solutions in a scattershot manner, business events have intervened making it impossible to deliver consistent information using a standard set of BI technologies and processes for collecting and integrating data for analysis purposes. Mergers, acquisitions, reorganizations, executive turnover and other forces perpetually undermine organizations' attempts to deliver a universal BI solution and avoid analytical silos.
BI Vendors. In addition, BI tools vendors sometimes exert tremendous influence over organizations, especially the uninitiated, who believe that purchasing a BI tool is the only thing they need to do to implement a BI solution. Without strong central controls, many organizations now find themselves in possession of a half-dozen or more BI tools that are associated with different data marts and data warehouses, which contain overlapping information and redundant staff. This not only makes BI a target of cost-conscious CFOs, but it undermines an organization's ability to deliver a consistent view of information for reporting and analysis.
Data Redundancy. In short, the proliferation of analytical silos with their redundant BI tools and data structures threatens to undermine the promise of BI to deliver business insight and value to the enterprise. TDWI research shows that, on average, organizations have 2.1 data warehouses, six independent data marts, 4.5 operational data stores and 28.5 spreadmarts (i.e., spreadsheets that function as independent data marts).2 Many organizations report that they have many more analytical silos than this, especially spreadmarts, which in many cases are too numerous to count.
Tool Redundancy. Invariably, each analytical silo uses a different set of BI tools, leading many BI professionals to complain that their organizations "have one of every kind of BI tool imaginable." TDWI research shows that organizations have an average of 3.2 BI tools from different vendors. Not surprisingly, the average number of BI tools increases with company size, from 2.3 BI tools for organizations with less than $500 million in revenues to 3.7 BI tools for organizations with $5 billion or more in revenues. Obviously, bigger companies have more departments and business units that purchase BI tools separately (see Figure 1).
Effect of Industry Consolidation. At first blush, 3.2 BI tools from different vendors doesn't seem like an unmanageable number, but this doesn't necessarily reflect the total number of BI tools a company has. Due to the consolidation in the BI industry, many best of breed BI tools that organizations purchased several years ago have been acquired by leading BI vendors and wrapped into a comprehensive BI suite. Thus, organizations often have two or three times as many BI tools as they have BI vendors.
The Excel Effect. These numbers also don't necessarily count Excel as a BI tool, even though it is the query, reporting, analysis and planning tool of choice for most power users and managers. The numbers would be higher if Excel was counted. Unlike Excel-based spreadmarts, Excel can be a legitimate BI tool when used as a front end to an analytical server.3 After a long period of resistance, many BI vendors are now embracing Excel, as well as other Microsoft Office tools, making them full-fledged BI clients in packaged suites. This greatly aids BI standardization efforts.
Figure 1: Average Number of BI Tools by Size of Company. (Based on 594 qualified respondents.)
BI Tools By Category. The proliferation of BI tools is more obvious if we count BI tools by category instead of by vendor (see sidebar: Standardizing on Categories of BI Tools). The TDWI survey* shows that organizations average almost three production reporting tools, three OLAP tools, two dashboard applications, two end-user query and reporting tools, 1.5 data mining tools and 1.5 planning/modeling tools. Combining these figures with the previous chart, organizations have an average of 13 BI tools (see Figure 2).
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