Process mining is the use of analytics to examine and improve processes. Effectively, businesses mine the event data logs from their standard company systems. This provides them with insights into what is really happening across both internal and customer-facing processes throughout the organisation.
Business can then identify – and address – bottlenecks, delays and other problems that may affect the customer experience. Even better, managing processes tends to improve efficiency, and therefore reduce costs. It’s a real win-win.
Many industries are using process mining, including manufacturing, banking and insurance. In telecommunications, a number of companies are reaping benefits from this new technique. In particular, it is helping them avoid being part of a race to the bottom on price that damages quality and reputation.
Using what you already have to hand
The joy of process mining is that it uses what companies already have to hand, and often do not use at all: data about their processes. There is no need to spend time and money gathering new data, which means that results are often available extremely rapidly. This, in turn, allows organizations to quickly make improvements.
In telecoms, where customer churn is a big issue, speed matters. And because telecoms routinely gather a huge amount of internal and external data about customers and processes, they are ideal candidates for process mining.
There are several telcos that are taking advantage of the potential of process mining. One company collects a significant amount of data about its customers’ activity, including call details, network data and customer data. It has been able to use analytics to mine this data very effectively and develop a much better understanding of its processes.
With this knowledge in hand, the company removed repeated steps and eliminated wasted time and effort. This has made processes more efficient, which is better for customers. It has also, however, meant that employees have more time to solve real customer problems because they are not spending so much time on unnecessary activity.
Do you need to gain stakeholder buy-in, raise investment, and prove AI´s value to your organization? Download our comprehensive step-by-step guide and strengthen your efforts.
A customer experience problem
One specific example shows the potential. A telecoms player tracks and stores a lot of information about the way its customers use its app and services. It found that there was an odd pattern related to a particular promotion. Customers were asked to "Shake the app to activate GBs." The company could see that customers were downloading the company’s app, seeing a pop-up, activating the promotion, getting another pop-up, and then calling the call centre. However, it was not at all clear why this was happening.
This was a problem for several reasons. First, it clearly meant that the customer experience wasn’t quite right. Second, however, the call centre is external to the telecoms company and makes a profit with every call. This issue, therefore, had direct financial implications for them.
Using process mining to find the solution
The company used process mining to examine what was happening in more detail. As a result, it discovered that customers were shaking the app to activate the promotion and getting a message that said, "You activated 2GB." However, the data was not actually credited to their phones until about two hours later. Customers were, therefore, phoning the call centre after a few minutes to say that their data had not arrived yet and to ask if there was a problem. Staff were tied up on calls explaining that the promotion would activate within a few hours, potentially causing delays in responses to customers with more serious problems.
The solution was simple and obvious. The telecoms company modified the second pop-up message to read, "You selected the shaking promo. It will be activated within two hours." Almost immediately, the calls to the call centre stopped, reducing costs. And staff could deal with real problems again.
Wide-ranging effects on customers and companies
This simple example shows how process mining can solve the immediate problem, increase efficiency and, at the same time, improve the customer experience. The potential financial implications can be huge. One analysis suggests that in the first year of using process mining, the telecoms company had decreased its cost per order processing by almost 40% while also improving productivity.
This meant a big improvement in the quality of business processes. And it helped the company position itself effectively in a very competitive market at a difficult time. If you want to learn more about it, please go here to our customer stories.