A big trend I’ve seen this year with several of the new customers we’ve brought on board here at Decisions is how BPM is being used to improve the experience of their customers at different points in their lifecycle. In this article I’m going to outline two categorical use cases that I’ve seen and the potential impact on the customer journey.
Automating Analysis Yields More Valuable Customer Interactions
It is all too common for me to hear about situations in the workplace where a full time job is dedicated to plugging data into a spreadsheet to make some sort of decision. It tends to happen most often in the financial services world, and in many cases it is happening because a decision needs to be made about a client. Is this client eligible for a certain product? What options can I present to a certain client for this particular product?
In highly regulated environments such a financial services, it is becoming more and more important to have a clear understanding about how these types of decisions are made today, and how they were made in the past. This need becomes increasingly difficult to satisfy when the logic for these decisions are dispersed throughout versions of spreadsheets and other systems.
In one particular case, a client had application data coming in from their website and they had a team of people dedicated to plugging that data into a spreadsheet to make an eligibility decision. Their daily throughput was severely limited. Turnaround times suffered for applicants. Business opportunities may have been lost as applicants turned to other faster solutions for these specialty financial products.
Another case included the need to schedule multiple face to face meetings so that a financial advisor had time to “crunch the numbers”. I do understand the need for time to prepare meaningful proposals, but where possible I’m seeing more customers delighted from rapid feedback, and more valuable proposals coming from those who are able to gather more information from a client because the feedback on the initial eligibility check was instantaneous. In other words, automating the analysis of repetitive decisions can lead to more constructive interactions with customers. These interactions can be focused more on the relationship and opportunities together, than the homework behind seeing what is possible.
Transitioning from Manual “Number Crunching” to Self Service Interactions
Executives and other leadership roles are being asked to make a big cognitive leap when you begin to introduce the idea of self service solutions for your customers. In many cases, these leaders have put their trust in face to face interactions with customers and manual, but tightly controlled business processes, because that is what they did when they were in the trenches. “It worked then, it is working now, and we should improve the existing process.” For many, the logical next step is to look for a tool that can help the employee increase their productivity. However logical, it may not be optimal.
Instead of viewing customer interactions as a result of employee productivity, you may find more room for growth with the idea of defining a process well enough for the customer to be productive on their own!
Back to our previous examples where data is being manually entered into spreadsheets, we can begin to empower the customer by letting a machine do the number crunching, and designing a user experience that keeps customers on the right path.
Both of these ideas – giving the decision making to a machine, and guiding a user experience down a correct path – are critically dependent upon continuously optimized business rules.
Making the jump from manual data entry to customer self service can remove employee related bottlenecks in your customer journey and yield more interesting questions from customers as they become more informed throughout the process on their own accord.