Part 3 of 4 – Learn how Impact and Root Cause Analysis is faster, takes less resource and yields a better result with Arkturus Process Mining.
Process Mining is a new technology that transforms how business process improvement is done from initial discovery, through to measurement, root cause analysis, and ongoing monitoring and management.
This blog focuses on the ‘Analysis’ stage and discusses how a data driven analysis approach using Process Mining enables you to identify the root cause of problems much faster than traditional methods.
Traditional Method of Process Analysis
Root cause analysis does not always get the attention it should. There are several reasons for this including a natural tendency for us to jump to conclusions on the root cause of a problem or to jump straight to a solution. In addition, when there’s pressure to fix a problem quickly, root cause analysis is often rushed because traditionally it can require a reasonable amount of effort and time.
Root cause analysis usually starts with theories on the cause of a process issue, and you then use process analysis and data analysis techniques to further develop and confirm the theories. You may use tools such as ‘Fishbone diagrams’ and ‘5 Whys’, and finally you verify the root cause of the issue.
To analyse a process for potential root causes of an issue, you generally need a more detailed understanding of the process than you collected during the Discovery stage. There may be existing detailed process maps and documented procedures that you can use, but more often than not you’ll need to collect this information through discussions with subject matter experts and/or walking the process. All this adds further time to the project.
Then you need to source data to verify the root cause of the problem. Although you may be able to use some of the data previously collected during the Measurement stage, for root cause analysis you usually also need more detailed data, including information on representative sample cases. The delay that you experienced in sourcing data during the Measurement stage, is now repeated in the Analysis stage, adding further delay to the project.
Process Analysis with Process Mining
With Arkturus Process Mining, you still follow a traditional approach of hypothesising potential root causes and still use standard tools such as ‘Fishbone diagrams’ and ‘5 Whys’, but your process and data analysis is much easier because you have comprehensive process information at your fingertips.
Using process visualisations and interactive charts you can very quickly identify key attributes associated with an issue to provide insights into the potential root cause. Key attributes can include a team or location, or a particular process path that ‘problem’ cases followed.
Above is the ProViz Interactive Charts view. Once you have identified key attributes of an issue, you can drill down to sample cases containing these attributes to analyse and help further verify the root cause of the issue.
Sometimes the root cause can be identified by looking at how the issue varies over time. This can indicate a capacity constraint, or alternatively it is not uncommon for a past system change to cause a problem that has not been noticed until now.
Note: if you are using process mining un-intended issues like this would generally be picked up shortly after that system change
Benefits
With Arkturus process mining, root cause analysis is much deeper and faster. Above displayed is our ProViz time lapse view. You have detailed process information at your fingertips, so you can avoid delays sourcing additional data. To minimise the risk of falling back on assumptions and intuition, you can instead follow a data driven analytical approach to identify the root cause of a process issue.
Our next blog will explore how Process Mining transforms the Monitoring activity.
