How Best-in-Class Companies Leverage Operational BI


In a recent blog on cloud computing, I wrote that asking folks to define an emerging technology is one way of gauging its popularity. In general, the squishier the definition, the hotter it is.


Another popularity gauge is how many (roughly equivalent) terms are used to describe it. A good example is operational business intelligence, aka pervasive BI, transactional BI, real-time BI and near real-time BI.


A thorough Intelligent Enterprise article discussing Aberdeen Research findings on the BI practices of best-in-class companies deals with the multiple term issue early on. The article notes:

No matter what flavor or definition is used, at the heart of the matter, organizations are beginning to focus their attention on leveraging existing data to enable and optimize daily, hourly, minute-to-minute, or even up-to-the-second actions.

Best-in-class companies are streamlining their decision-making processes, which is the overriding goal of operational BI. Indeed, Aberdeen says such companies experience decreases in both the time that elapses between business activity and the delivery of information to decision-makers, and the time between business activity and actual decisions or other resulting actions.


According to Aberdeen, other key characteristics of these best-in-class companies include improvements in customer satisfaction and customer retention and improvements in data access and availability for end users.


Best-in-class companies differentiate themselves from more "ordinary" peers with their ability to master five practices: process, organization, knowledge managment, performance management and technology. As I read through the in-depth explanations of these areas, it occurred to me that a number of them had been featured in my blogs, in my interviews with experts, and elsewhere on IT Business Edge.


For example, in the process category, Aberdeen notes that best-in-class companies are more inclined to automate their data processing and analysis activities. Charles Nicholls, the CEO of SeeWhy Software, in October made a similar point during my interview with him. Drawing a parallel between BI and aviation, he said:

When I get onto the plane, I feel very good that there are two pilots who know what they are doing. However, they are not actually flying the plane. They do the takeoff and they do the landing, but everything else in between is done by the autopilot. The autopilot is making very gentle corrections in course and speed, and it flies the airplane much more accurately than the pilot can. It's completely objective, and doesn't get confused, and that kind of thing.

Nicholls told me that companies are increasingly choosing to separate their data from data logic. He said:

So analytics can trigger business process management systems and trigger the process for retaining customers, or retaining stock, or those kinds of things. Therefore the nature of what we call BI -- for the sake of a label -- is changing. It's not just about producing reports, but about creating these kinds of autopilot systems.

Automation can affect decision-making in a dramatic way by eliminating the reporting process entirely, said Nicholls. In his example, a service representative might be immediately notified via e-mail or other means if a customer halted an online application for a mortgage, triggering an outbound call to that customer. Nicholls said:

This particular case doesn't involve a report or a dashboard. ... This is an example of how you can build BI into your daily processes. If you think about displaying information daily, a dashboard is just an electronic version of a report. If you think about an operational process, it may not be that relevant to have that dashboard, because then you are relying on a person to look at it. It doesn't give you the big performance lift.

In the knowledge management area, Aberdeen points out that best-in-class companies are ahead of their peers in providing training and other resources to BI end users. Often, this includes the establishment of a BI center of excellence or competency center.


I blogged about the importance of user involvement in BI initiatives in June and asked BI expert Lyndsay Wise, principal of WiseAnalytics, about it in an interview earlier this month. She told me that a lack of user training can derail a BI initiative because users won't adopt BI if they don't feel comfortable with it.

For super users and IT, I think they may think (BI is) more intuitive than it actually is. With BI search and different areas in which BI is starting to become more intuitive, by developing interfaces that look and feel the same way a person might surf on the Internet, hopefully in the future it won't be as much of an issue.

Since usability is still an issue for many -- if not most -- companies, Wise recommends getting business users more directly involved in BI initiatives. She said:

More super users within the business so that not only are end users not always going back to IT, but also those issues of whether something will work or how well it will work are determined by the business. Once the business adopts BI and likes it, they'll see other uses for it and want to use it more.

The Intelligent Enterprise article contains a number of other interesting insights about operational BI from Aberdeen Research. Among them: Best-in-class companies are showing more interest than their more average peers in operational forecasting.