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The Myth of Self-Service Business Intelligence

Liberating IT?

Remember D-Day? That was the day in June 1944 when Allied troops stormed the beaches of Normandy to liberate Europe from the Nazi occupation. But there is another D-Day, one that is less well known but yet significant in its own right. That was the day in 1990 that data warehousing came to life. This is the day that information technology (IT) managers celebrate with gratitude and fondness. (Or at least they should!)

At the time, data warehouses promised to liberate IT from the drudgery of creating custom reports. Previously, the IT department was swamped. It couldn’t keep pace with the demand for custom development and was slowly drowning in a backlog of requests, a good portion of which were for custom versions of corporate reports. (Alas, things haven’t changed much for some organizations where IT groups are still bogged down with requests for custom reports.)

Admittedly, IT was cautious at first about creating redundant data stores—a data warehousing prerequisite and a long-time IT taboo emanating from the days of expensive disk storage. Once IT realized it could offload a huge portion of its work to end users, however, it began to evangelize the benefits of data warehousing to the business. Soon enough, data warehousing and its successor, business intelligence, became a clarion call for IT and a booming career opportunity as well.

The heart and soul of data warehousing, at least to an IT professional, is the notion of self-service reporting or self-service BI. Here, business users create their own custom reports using end user–oriented query and reporting tools running against a data warehouse. IT steps aside as an intermediary between users and the data and gives users what they’ve demanded for years: complete and unfettered access to data without IT interference. All that IT needs to do is set up the data warehouse and provide query and reporting tools. It can then focus on more value-added activities, such as developing new applications.

Data warehousing created a win-win situation in which business users gained direct access to data and IT managers eliminated the need to create custom reports—or at least that was how it was supposed to work.

Downsides of Self-Service BI

Unfortunately, as many organizations have discovered the hard way, self-service BI is a myth and doesn’t translate well to reality. Although the concept is valid, implementation is misguided. The result is reporting chaos.

One cause of the chaos is that organizations, keen to empower users with data warehouses and BI tools, go overboard. They give users too much responsibility for generating the information and reports they need to do their jobs. In reality, most users don’t want this responsibility, and it’s not part of their job descriptions. It takes too much time, and users often make mistakes and get frustrated. If they do get training, users usually forget how to use the tool by the time they need to create a report. Consequently, they either stop using the tool or call IT to create the report for them. The organization then finds itself exactly where it was before it spent hundreds of thousands, if not millions, of dollars on its DW/BI program.

For example, the human resources department in one large organization I worked with discovered that it had 26,000 different reports serving 450 active users out of a potential of 3,500. Most of the reports were variations on a couple of themes, and most hadn’t been used in months or years, but they were still sucking up disk space and cluttering report folders. The majority of the 3,500 employees who could benefit from the BI infrastructure found the tools difficult to use or couldn’t find the right report in the directory.

There is another, more deleterious, downside to reporting chaos than lack of usage and BI tool shelfware. It occurs when the small percentage of users who do employ the new tools don’t define key metrics, accounts, and terms in a consistent fashion. This makes it impossible for executives to get a harmonious view of business activity, and they may unwittingly make critical decisions based on inaccurate information.

Another problem is that overambitious business users may submit costly, long-running queries, which bog down query performance for all other users. When result sets take a painfully long time to return, business users accustomed to split-second response times for Google queries stop using the BI tools altogether. What’s ironic is that most of these network-clogging, runaway queries are usually unnecessary; users typically need only a fraction of the data that they include in their queries.

The Pendulum Swings

When organizations first deploy data warehouses and BI tools, they embrace BI self-service with an exuberance bordering on delirium. Once afflicted with report chaos, however, they recognize the limitations of self-service BI. Rather than ricochet back to the days of canned reporting, most organizations seek to balance self-service BI with tailored delivery of information to casual users.

Mapping Users to Tools. In order to achieve this balance, organizations realize they need to better understand the information requirements of their users and provide them with tools and reports that are optimally suited to their needs. In essence, they need to investigate what users want to achieve from a business perspective before they ask what kind of information or tool they need. Are they trying to reduce supply chain costs while increasing quality by implementing a supplier rating program? Are they trying to maximize call center productivity by tracking call times and sales volumes? Knowing their ultimate business goals focuses the discussion of BI tools on the right level.

After such investigation, most organizations discover that 80 percent of their users consume reports or information views created by the remaining 20 percent. The 80 percent of “information consumers”—or casual users, as I call them—consist of executives, managers, front-line workers, customers, and suppliers. The remaining 20 percent are “information producers,” comprising business analysts, power users, and IT developers. (See Figure 1.)

Figure 1. This diagram is one way to map user segments to BI tools.

There are numerous subcategories within each of these groups, varying from one organization to the next depending on the makeup of their user populations. Once organizations segment their user base, they can map each segment to one or more BI tools that meet their information requirements. This type of evaluation helps maximize BI usage and minimize BI shelfware.

Be aware, however, that individuals often play multiple roles. A power user who creates custom views for colleagues in the marketing department may be a casual user when viewing human resources information or corporate financial data. Typically, you need to arm users with a variety of tools or logins to access different reports and sets of BI functionality.

Tools Selection Process. As simple as it sounds, many organizations skip the step of mapping users to tools. What usually happens is that information producers hijack the tool selection process and pick BI products that are suited to them but not to the majority of users. To avoid this problem, populate the BI tools selection team with a cross-section of users from multiple areas and listen carefully to their feedback. Remember, there is no tool that meets the needs of all users, so you’ll need to invest in a suite of tools. Fortunately, the BI market has matured to the point where leading BI vendors now offer a comprehensive suite of integrated BI tools built largely on a single, integrated architecture (or so they claim).

IT -Driven Standard Reports

Once you catalog users and assign tools, you need to create a limited set of standard, interactive reports. These reports are geared to information consumers, the 80 percent of your employees who require periodic access to information. The remaining 20 percent of business analysts, power users, and developers can continue to use their ad hoc tools to perform deep analysis and exploration of data.

A well-designed interactive report can replace dozens, if not hundreds, of existing reports. Each report typically focuses on a specific domain and contains about 20 dimensions and 12 metrics. These standard reports are broad without being overwhelming because they present a simple, intuitive interface that makes it easy for users to apply filters to navigate and analyze the predefined data set. Once users navigate to a particularly useful view of information, they can subscribe to that view so it’s available with fresh data the next time they open their reporting tool.

These standard interactive reports usually take the form of a dashboard, scorecard, or parameterized report that enables users to change a predefined view by selecting filters from a pick list or other graphical mechanism. As a result, these reports often give users the impression that they performing ad hoc queries against all the data when, in reality, their access is circumscribed by a predefined set of metrics, attributes, and filters. The BI team needs to monitor usage and examine which elements are being used and which aren’t and perform periodic selective pruning to keep the reports relevant and fresh.

Report Governance. Guess who needs to create these standard interactive reports? Yes, it’s the IT department or its successor in this space, the BI team. But unlike in the days of old, the BI team does not serve as a custom report development shop. Its role is to examine global requirements, create a library of standard interactive reports, and establish a governance process for adding, deleting, and modifying the reports. A governance committee, comprising a representative group of business users and IT professionals from a single domain or multiple domains (depending on the organizational structure and DW architecture), reviews requests for new reports or modifications. The committee determines whether any of the existing reports can meet the need or if an extension or new report is required.

Effecting Change. Of course, you don’t want to kill requests by committee, so before you implement the governance process, you need to work hard and fast to develop the standard interactive reports so that 80 percent of the users can get 80 percent of the information they need from them. Then, you need to shut down the older, ad hoc reporting systems. This can be politically sensitive, so you must be cautious.

Some organizations are fortunate enough to have a CEO or CFO issue a mandate that the new standard reports will be the basis for all future decisions. If you’re really lucky, they’ll enforce this mandate by using the reports themselves and scolding subordinates who present information created in ad hoc, nonstandard ways. Less fortunate organizations need to tread carefully, persuading groups and managers that the new reports contain more accurate and comprehensive data than their existing reporting solutions. While many groups will convert, others will hold out for a long time, even if the BI team refuses to support the system with upgrades, platform support, or help desk services.

Power Users. Remember, exceptions are the rule. Give information producers unfettered access to data and allow them to acquire the BI tools they want—because they’ll acquire what they want whether you allow them to or not. In other words, self-service BI makes sense for power users, but not for everyone else. Make sure the power users create reports only for themselves, not the general audience. If they come up with a view of data that can help executives and managers make better decisions, then that view—along with data set and information tools required to produce it—needs to be adopted by the report governance committee and moved into a global report library for all to access.


In adolescence, we swing wildly from one passion to another, carried away by the newness and potential of our object of interest. In adulthood, we learn that there is a price to pay for our excesses, and we seek to find balance amidst the extremes. In the world of BI, organizations often are carried away with the notion of self-service empowerment and fall prey to reporting chaos. To remedy this situation, organizations need to achieve balance between self-service BI for a select few and tailored delivery of information for the majority. This will give organizations a stronger foundation upon which to leverage information for insights and business gain.

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