Today’s new and powerful information platforms collect, distill, analyze and present massive amounts of operational data in formats that are easy for the most junior customer service person to understand. In a typical scenario, these platforms apply rules to incoming machine data and enable proactive actions, such as opening up a customer case, dispatching a part and/or alerting a field service team to take preventive action. The customer gets his problem solved and the customer service team is satisfied they have successfully dealt with a problem. Everyone is happy.
But as the late night TV ads scream, “But wait, there’s more!” Today’s platforms provide so much more capability than the basic proactive scenario above. They offer two higher levels of analysis, predictive and prescriptive.
In the scenario above, what if the customer service team reviewed predictive data and addressed a potential problem before it became a problem. The customer would never have had to make the call he made above. If he’s happy after the customer service team efficiently addresses his query, think about how happy he is that he didn’t need to make the query at all.
In the prescriptive analytics scenario, the information platform takes predictiveness one step further and recommends to the engineering or customer service team specific actions that will enable them to address a potential problem. This saves additional time and allows more junior engineers and customer service staff to address potential problems and not just identify or predict them.
These predictive and prescriptive scenarios allow customer service teams to dramatically reduce the mean time to resolution (MTTR), enhancing customer satisfaction, elevating product reputation and increasing customer service efficiencies.
The concept of predictive and prescriptive analysis touches another issue: MTTR requires a redefinition. If teams are able to address issues before them become problem, then “resolution” now has a whole new meaning. Tune in to my next blog as we delve deeper into this discussion