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Efficient team fallacy: why process and task mining shouldn't be used in isolation

Efficiency does not equal productivity. Process mining vendors have been trying to promote the idea that companies should first understand the processes within the core IT system and only then - tasks. However, that approach doesn’t work with task-intensive processes, and you’ll find out “why” in this article. 

A typical scenario in a global process

Let’s look at the next scenario of global operations with three teams involved in it. Imagine that all three teams are located in different regions. Each of the teams is responsible for a certain part of the process, and the next team continues the work based on what was produced by the preceding team. 

After a few months of running the same process, the Blue team seems to be more efficient than the other two teams based on process mining findings. Their throughput time is very short and the efficiency of work is high compared to the Yellow and Pink team. Based on these criteria, they get all the praise and get rewarded. The Pink team has the longest throughput time and thus gets recognized as the bottleneck of the process. 

The reality, however, was very different. The Pink team had a hard time dealing with the cases that came from the Blue team. They had to do double the work because of all the fixing, rework, and incomplete information. It turns out that the Blue team didn’t follow the instructions properly, creating more work for the Pink team and increasing their throughput time, while they completed their parts very quickly. 

Implementing task mining and process mining separately doesn’t make sense 

If we only look at a single IT system, we wouldn’t know the reality of things and would assume that the Blue team is doing a great job. Measuring compliance within one IT system doesn’t make sense. However, that’s exactly how companies have been doing process and task mining activities in recent years. 

First, they use process mining to analyze the process within a core IT system like SAP and identify a bottleneck (in our case, the Pink team). Then they implement task mining technology on the “broken part of the process” (the Pink team) and observe their efficiency, monitoring and micromanaging every task they are engaged in. Based on task mining findings, they’ll push the Pink team to perform faster and to be more efficient, while on a large scale, Pink wasn’t even an issue. Optimizing the work of the Pink team would be optimizing the wrong issue. 

Wrong problem – wrong solution

Analyzing a single siloed IT system doesn't work in real-life scenarios, as that is only a small fraction of an end-to-end process. It’s tempting to extract event logs from one system and make conclusions on how the process goes. However, the reality is very different and thus this approach will always lead to sub-optimized or wrong decisions.

After all, the Pink team felt demoralized because of unfair working conditions and eventually left the company. The new team that comes instead will likely have the same scenario; while the company still wouldn’t know the real reason for “inefficient” work from Pink. Blue team, on the other hand, would have their salary raise and a paid yearly company trip. On a larger scale, the company will still be experiencing the tangible loss of having inefficient processes in the form of highly costly processes and high employee turnover. 


Cases like this happen around the world on a regular basis. Executives end up bringing the wrong solutions to insignificant problems and miss out on the most critical issues. Process mining and task mining technologies should not be used in isolation one after the other. Both processes and tasks need to be analyzed simultaneously in order to bring full visibility over business processes. One such technology is Work API, a hybrid solution that inherently combines process and task mining in a single easy-to-use platform. Book a call with Workfellow experts to learn more about this innovative approach. 

Written by

Kazyna Turdibayeva

Marketing manager at Workfellow

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