Just read an excellent article on the subject by Tom Davenport. We at Forrester Research indeed see the same trend, where more advanced enterprises are starting to venture into combining reporting and analytics with decision management. In my point of view, this breaks down into at least two categories:
- Automated (machine) vs. non automated (human) decisions, and
- Decisions that involve structured (rules and workflows) and unstructured (collaboration) processes
Unfortunately, current best practices and technologies to address these four distinct but closely related requirements come from different vendors, technologies and experts. Tom is also correct in pointing out that a full loopback mechanism that measures decision outcomes is critical. Watch for upcoming Forrester research on this very important, but largely unaddressed (by analytics software and services vendors), topic.
I am also glad Tom pointed out a huge (often key) challenge that I know my clients face every day, which is how does one convince a non-analytically oriented CEO that analytics and decision management are vital to enterprise success. And I quote from the article:
"There’s a big, big gap between the most analytical and the least analytical. American business has a fair number of CEOs with engineering backgrounds, and they tend to be relatively analytical. At the same time, an awful lot have sales backgrounds, and they’re not analytical at all. Clearly, you could do a lot of analytics with sales, but people don’t generally go into sales because they like numbers. Executives with legal backgrounds also don’t tend to be very quantitative in their decision approaches."
One reason for such challenge is that unlike any other enterprise application or a process, analytics and decision management are very hard (but possible) to build a business case around, with a concrete, tangible ROI. One way that we suggest our clients break through this executive logjam is with education on the benefits of analytics and decision management, often using competitive BI benchmarks. And guess what, analytics on analytics — or understanding when, who, and how analytics are used in an enterprise, and potentially correlating usage of analytics to decisions, good or bad — is also one of the emerging best practices.