Sramana Mitra: Now, let’s take some use cases and work through three or four customers whose cases you have permission to discuss. You may choose which best project your capabilities. The objective is to give our readers a feel of what is happening in your world of big data.
Dale Skeen: I’d be happy to do this. The first example comes from a customer named TXU, which is Texas Electrical Utility, the largest retail provider of electricity in Texas. They had a problem where they could not see their business processes in [real time] because these processes were automated in a number of systems (not in a BPM), including ERP or CRM systems. They were blind to their customer-facing processes and customer service processes in particular. This meant that if something happened between these systems and a process got stuck, they found out about it [only] because customers called and complained.
It was at that point they realized there was a problem, and then they went into a reactive mode to try to resolve it, after the fact and after the customer was unhappy. What we provided with our operational intelligence solution was the ability to monitor each of these systems that were a component in their business processes – they actually had two instances of SAP running. We were looking at log files, database changes, or API skin information to piece together what was going on with these business processes. Examples were enrollment processes for subscribers to the electrical service and to be able to change the provider – in Texas you can do that – or to reconnect a customer after they paid a delinquent bill.
Those were things the company had absolutely no visibility into. With our operational intelligence solution, we were able to detect these business events, piece them together, correlate them, and show them in the context of a business process. We were able to quickly identify an exception that took place or a process that was stalled, and we were able to do so in real time. We could then notify the personnel who was responsible for it. In other cases we could trigger an automated process that would correct the problem. The goal was to correct it before the customer even found out they had a problem and was negatively impacted.
So, our system provided the visibility – what was happening with these business processes – and the analysis of what was going on and the ability to either take guided or automated resolutions against what occurred when business processes failed. For TXU, this had a dramatic impact. They were able to reduce the amount of time it took them to discover they had problems from hours to minutes, or even less than a minute. They were able to mitigate most customer problems before the customers were negatively impacted. They thus had an increase in customer satisfaction and a decrease in customer turnover. They were able to optimize their back-office handling of business process exceptions because they were notified in advance and they could manage them more effectively.
In short, they were no longer in firefighter mode. Over time, they managed to benefit from their newly acquired ability to see these business processes in action.