The folks over at ZS Associates sponsored a study by the Economist Information Unit on analytics titled “Broken Links: Why analytics investments have yet to pay off”. This report showed the classic challenge of analytics – 70% think analytics is very or extremely important but only 2% say their analytics efforts have a broad, positive impact. In response I recently wrote a series of blog posts – How To Fix The Broken Links In The Analytics Value Chain – over on our company blog. You can find the posts here:
- How To Fix The Broken Links In The Analytics Value Chain
The first step is to understand what is broken. The study showed two areas where analytic adoption fails – in problem framing/solution approach and in taking action/managing change. Analytic technology works but the analytic value chain is broken at the start and at the finish. - Framing Analytics with Decision Modeling
Fixing the first broken link means accurately framing your analytic problem. What CRISP-DM calls Business Understanding is critical for analytic success yet most analytic teams jump straight from identifying a metric to building analytic models. Framing the problem in terms of the decision-making that must be improved is critical and decision modeling is the right way to do this. - Operationalizing Analytics with Decision Modeling
Fixing the first link and applying analytics to the right problem is necessary but not sufficient – you still need to actually change organizational behavior and take action. Operationalizing your analytics so that the decision-making you identified is actually changed, doing this fast enough and tracking the effectiveness of this change are all critical. Decision modeling is key here too.
Decision modeling, specifically decision modeling using the Decision Model and Notation (DMN) standard, can fix the broken links in your analytic value chain. To learn more, check out these briefs:
- 6 Questions To Ask Your Business Partner Before You Model
- 5 Things You Need to Know Before You Deploy Your Model
