In this post, you will read about what process analytics is, its potential benefits and example use cases.
What is process analytics?
Process analytics, also called process mining, is a set of computational techniques that provides a clear understanding of the processes under investigation. These techniques help us uncover useful information from the bulk raw data records and gain insights on different perspectives (such as efficiency, structuredness or resource). And eventually, by using these insights, we may have the opportunity to improve the overall efficiency of the processes, cut costs, save time & energy, improve customer satisfaction, etc., depending on the subject.
Whether it is the activities we perform when using an application or the processes being carried out within an organisation, everything that touches a digital system is recorded.
Most of the time, a single activity record usually doesn’t mean much; however, when multiple related records are analysed together, they can help answer a lot of questions and provide insights.
Suppose we are analysing a specific process by referring to the perspectives mentioned above. Some of the questions we can answer by using process analytics techniques are the following:
- Performance perspective
- What is the average completion time of this process?
- Is there a specific group with longer completion times?
- Which activities take most of the time?
- Are there any bottlenecks that slow down the process?
- Are there any repetitive activities?
- Resource perspective
- Is it the case that some resources complete certain activities much above the average time?
- Are there activities only performed by one resource that could be considered as knowledge retention risk?
- Structuredness perspective
- Is the flow aligned with the way the process was originally designed?
These are just a few high-level and initial questions one can ask. Of course, different questions can be raised in the subsequent steps depending on the answers. Even deeper analyses could be performed when the above-listed perspectives are combined as needed.
Example use cases
As for the different use areas, process analytics can be applied in many domains. Some examples are as follows:
- Customer Support / Operations Processes: Companies can analyse customer support processes to improve response times, enhance issue resolution, and optimize the overall support experience.
- Analysis of learning patterns in online learning platforms: Process analysis can be applied to identify the patterns followed by the students and gives insight to curriculum designers for further optimization opportunities. In this context, it can also help follow up and improve students’ performance.
- Patient Flow Analysis in Hospitals: Hospitals can use process analysis to optimize patient movement from admission to discharge, reducing waiting times and improving patient experience.
The mutual benefit
Usually, it is not only the benefit of one party but two parties. As can be seen from the abovementioned use cases, the improvement of processes by process owners often results in the benefit and satisfaction of the counterparty (customer/user/patient) as well. While this situation is quite important in itself, ultimately, it also means a potential positive return for the process owner in the long term.
The next post will be about the process of a process analytics project.