Herschel outlined a number of ways to apply BI in process planning and execution:
Add steps to a process to open up new opportunities. For example, use historical or predictive data to enhance a customer-related processes with cross-sell, up-sell or retention actions. Improve process efficiency/effectiveness by giving process managers more complete knowledge of, say, compliance or supplier reliability. Enhance process insight by introducing new data visualizations or better aggregate views of data. Interpret decision impacts - not just the immediate, obvious impacts, but also downstream ripple effects on, say, the supply chain or customer retention. Eliminate steps in a process, using analysis to spot low-value or high-cost steps.
Herschel shared the example of ING Insurance, which increased claim process efficiency by as much as 40 percent by using historical and predictive insight to screen claims, fast-tracking the many claims falling within expected parameters while giving the few exception items greater scrutiny. In the bargain, customer service and satisfaction improved.
Herschel summed up encouraging process teams to carefully consider how they might apply ten common BI and analytic techniques: simulation, optimization, events alerts, reporting, dashboards, visualization, ad-hoc query, statistics, descriptive data mining and predictive data mining. "There's no way you'll apply all ten, but you'll quickly realize how two, three or four could really improve a process," he said."Process-driven BI" has been a big theme at this week's Gartner BI Summit, so I sat in on a presentation by Gartner analyst Gareth Herschel on "Integrating Business Insight With Business Processes." Good presentation, but I wanted to hear more about the direct connections with modeling and management technologies. The performance management and process management camps share the whole idea of a "continuous circle of improvement."