The Five Dimensions of Business Intelligence
It’s interesting how BI tools have evolved. We keep moving upward and outward, defining new dimensions of BI tools that provide either deeper insights or broader penetration within organizations. We are now in the throes of adding several new dimensions to BI, namely monitoring and advanced analytic dimensions, which will further fuel BI’s growth. (See Figure 1.)
Reporting Dimension
In the beginning, organizations simply delivered reports to users. The reports were predefined, static, and paper-based, and they shed light on past activity. Over the years, reporting moved online and became more interactive. Some parameterized reporting screens with drop-down pick lists make users think they are performing ad hoc queries. Nevertheless, reporting was the first significant dimension of BI.
Analysis Dimension
But in the 1990s, reporting became passé. Many users clamored for personal analysis tools that would allow them to explore and analyze data in a relatively unfettered fashion. Consequently, vendors delivered ad hoc query tools and OLAP tools that let users “slice and dice” data to their hearts’ content. Analysis of dimensional data became the second significant dimension added to BI.
However, two things happened at this point that caused a major crisis of faith among BI tools vendors. First, it turned out that only a small minority of users really had much interest in using ad hoc query and sophisticated OLAP tools. Most users found these tools much too difficult to use or navigate without getting lost. “Slice and dice” turned into “lost and frustrated,” and created a host of BI shelfware.
Second, most BI vendors abandoned reporting, but—almost too late—rediscovered that most users prefer viewing reports to exploring data in an unfettered manner. In the past several years, leading BI vendors have scrambled to cover their reporting flanks by developing or acquiring reporting tools. With both reporting and analysis tools in hand, users would have a complete set of BI tools—or so vendors thought.
Figure 1: The five dimensions of BI. BI tools evolved from reporting to analysis tools, which many users simply used to dump large data sets into Excel to do planning. Today, companies are adding a monitoring layer as well as new, advanced analytics and visualization to the stack.
Planning Dimension
Unfortunately, BI vendors gradually discovered that most users were using analysis and reporting tools as glorified extract programs to dump data warehouse or source system data into Excel. Although they were glad for the sales, users often complained of poor query performance. It turned out that business analysts and managers who needed to create business plans and budgets, model scenarios, or recalculate forecasts would use the BI tools to grab large data sets and move them into Excel, Access, or a statistical modeling program. These runaway queries would bog down query performance for everyone else.
Today, many BI vendors sell business performance management software. What they’re really doing is acknowledging the third dimension of BI tool evolution: the planning layer. Today, most BI vendors offer much tighter integration with Excel, because it is by far and away the best all-purpose business planning and modeling tool available, and probably always will be. But some BI vendors now offer budget and planning tools that are fairly well integrated with reporting and analysis tools, creating a business performance management (BPM) suite.
Monitoring Layer
But a combination of reporting, analysis, and planning still doesn’t do the trick for most users. The tools make it too hard to find the right data and too easy to get lost in it. And the planning tools are not well integrated with the analysis tools. What most users really want is a monitoring layer on top of analysis, reporting, and planning tools that pulls them all together and provides a highly simplified and intuitive interface—namely, a dashboard or scorecard. These visual interfaces enable business users to track or monitor the metrics they care about most, compare actual performance to predefined targets, and set alerts to notify them when performance falls below goals.
This monitoring layer delivered in the form of dashboards and scorecards represents the fourth dimension of BI. Today, most organizations use different BI tools to deliver reporting, analysis, planning, and monitoring capabilities, and most are not tightly integrated. Ideally, all these tools work harmoniously on a common BI and data infrastructure.
For example, the monitoring layer notifies a user via an alert that performance in a key area has dropped below target. In response, the user can click on the alert or chart and drill into the analysis layer to explore the root cause of the issue or access detail reports on products or customers that are part of the problem or issue. This “exploration” is done in a structured way, providing only the drill paths relevant to the issue, so users don’t get lost in the data. The users can then turn to the planning layer to update targets or forecasts that immediately show up in their dashboard, or write an analysis of the problem and its impact on strategic goals for publication in the corporate scorecard.
Most leading BI vendors are now working feverishly to deliver such integrated BPM solutions. Many now offer BI platforms that provide a common BI and data infrastructure to support a variety of BI activities. (See Figure 2.)
Figure 2. BI platforms provide integrated BI tools or modules that are aligned with business strategy and run on a common BI and data infrastructure.
New Dimensions—Advanced Analytics
But while BI vendors rush to offer an integrated BI or BPM platform that supports reporting, analysis, planning, and monitoring, user requirements keep moving ahead. Many companies are now asking, “How can we deliver further value from our DW/BI investments?” Not surprisingly, there is a groundswell of interest in exploiting new dimensions of BI, namely data mining, text mining, and advanced visualization.
Some companies have already created custom solutions or used early adopter technologies to create sophisticated statistical models to detect fraud, automate cross-sell recommendations, define loan prices and terms, and predict customer behavior and machinery breakdowns, among other things. Similarly, some companies are analyzing call center interactions, e-mail responses, Web pages, and video and image files to understand key trends and patterns in text and other unstructured data. Because there is so much data involved in this type of deep analysis, many are leveraging advanced visualization techniques to quickly detect key patterns and rules or display data in usable forms such as maps.
Conclusion
While I have defined five dimensions of BI, there are probably many more. BI is a rich field, one built on the continuous exploration of knowledge and pursuit of truth in our businesses. Since knowledge and truth are fleeting and evanescent, we will always need new tools to help us capture the insights required to run our businesses. And this is a good thing, since it means there’s a rich and lively future for those of us who have made our living in the BI field.