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Monday, November 30, 2009

Real World Analogies in OBIEE

As OBIEE emerges as a cornerstone part of Oracle’s Web 2.0 Fusion offering, it is a good time to discuss a real world analogy that has been apparent to me for many years now and has generated excitement during planning sessions of the more innovative implementation teams I’ve been on. OBIEE is an excellent web tool, for its dashboards and navigations, and it is important to look at User Groups as a cohort of individuals with shared goals who need to use OBIEE as a communications tool and as an effective analytic tool. A tool that has been useful in the real world for doing this is the fantasy sports league application, and it gives us many valuable insights for achieving uptake in our OBIEE implementations.

Although it is ironic that an application with the word “fantasy” in its title would be a useful analogy to solve our business problems, it is still true. Fantasy sports leagues have been very successful in the real world as an analytic tool that has had mass uptake. The application needs to be effective in helping groups to complete their assigned work, and to make better decisions, which are both key goals of our OBIEE implementations. Fantasy leagues are used as a communication vehicle for real world business groups that are looking for ways to interact, such as a college cohort looking to stay in touch after graduation, or a company contest. The value of contests as a business tool for generating ideas is well documented. Google’s programming contest, which started in 2002 has generated tens of thousands of applications, is responsible for important real-world systems like Google Local and Professor-Verifier [The Google Way, Chapter 7: Look for Ideas Where They Are, Bernard Girard, No Starch Press 2009].

The history of the fantasy leagues, more than thirty million strong today, is curiously analogous to what we want to achieve with OBIEE. From 1960 to 1980 it was a tool used by the intellectual elite, like Harvard Sociology Professor William Gamson’s “Baseball Seminar”. Rotisserie leagues started getting media attention in 1980, and special notice was given to the fact that data was used in real time, statistics from the current season. The business of statistical analysis matured in the fantasy sports field after its popularity created a demand for optimized predictions of specified Key Performance Indicators that scored points in the leagues.

Fantasy sports as a web application online is currently used by over 30 million people, creating competition for the best analytic dashboards to attract the most users.

So what do analytic dashboards used by these fantasy leagues look like, and how can we do that in OBIEE dashboards? While graphs may be important, note that for the masses these graphs are not extremely useful. Tabular lists dominate fantasy sport websites. The lists must default to the most useful Top-N and be re-sort-able by column. This is a common feature of tabular reporting in OBIEE, but it is important to understand that in the real world, other more graphic features do not undermine the importance of putting our data in this fashion on dashboards. The ability to quickly navigate from one presentation of data to another presentation of data with the same visual representation, a tabular, re-sortable presentation, is the dominant feature. Visual keys, surprisingly, are most useful when they simply give us more information on that representation. For example, ESPN has a Top-N page of multiple major categories, and the graphic is simply a photograph of the face of the top person in that category. In OBIEE, it might be useful to expose more photos of our business individuals, such as the business owner responsible for the dashboard. If it were a KPI were measured by team performance, a team logo might be useful. More sophisticated analytic tools are for a different audience, and follow the needs of the statistical analysts who are part of smaller decision teams, so they do not get exposed on the dashboards used by most of the people who consume the application. This might be an equivalent of a text alert on the screen that aggregates the number of Monte-Carlo simulations that were done, but exposing details of the thousands of simulations would not be possible.

BI Applications in 7.9.6 already have done some good work in providing a user experience. We just have to pay careful attention about how to implement the system. For example, built into the out-of-the-box experience are two sets of dashboards. The set of dashboards that is used by most people has the common presentations similar to fantasy leagues, such as the Top-N type of presentation. When you see demos of the tool, they default to the graphics, but there is a view selector that allows tabular lists of the data, and I would suggest considering in most cases whether the default presentation when coming on-screen should be tabular to reduce clicks and increase usability. The other set of dashboards spans multiple subject areas. These are pre-built statistical analyses available for when decisions need to be made upon the data, and include scatter charts, regressions and tools common to a smaller audience, the more sophisticated decision analysts.

Another question I have been asked in OBIEE implementation discussions is whether a contest for who uses the dashboards the most is possible. This would be analogous to the fantasy sports league itself. The answer is that it is very possible, in fact we do monitor usage in the OBIEE implementations, and more sophisticated applications are already developed. BIConsultingGroup’s product IMPACT gets more sophisticated reporting out of the usage of the end users. A dashboard could be designed and written with the specific intent of making a usage contest out of the usage analysis information, with the key business interactions as the key performance indicators. For a more comprehensive analytic application, the design could integrate an application similar to a fantasy league draft, where draft results for units in the sales pipeline could provide interesting information about predictions about which sales in the pipeline have the best chance of success.

What are design teams responsible for? Blogger Jeff McQuigg writes, “A BI system is a well thought out, planned and coordinated collection of efforts designed to produce a system that is so well organized it allows your user community to ask sophisticated questions of it and get those answers quickly and with a high degree of accuracy.” Fantasy leagues provide us with a successful real world analogy that we can use for building great OBIEE dashboards.