Though businesses plan simple, easy-to-follow and easy-to-understand processes, actual processes hardly conform to these plans. This is because companies usually encounter deviations in process conditions and inputs. As these deviations are not easy to identify, conformance analysis (or conformance checking) is a useful process mining feature to handle this task.

By leveraging event logs, conformance checking help companies discover nonconformant cases and identify their root-causes to improve process efficiency. Considering that around half of the operations don’t follow planned processes, the importance of conformance checking is increasing for businesses.

What is conformance analysis?

Conformance analysis, also known as conformance checking, is one of the critical features of process mining to analyze process steps if they conform to the actual process, as desired. This feature is vital to highlight process variations and identify root-causes of the deviations. By eliminating nonconformant cases, businesses can create more standardized and simplified processes. The main goal is to reduce process complexity and achieve standardized processes that work together in harmony.

Wikipedia defines conformance analysis as the following:

Business process conformance checking is a family of process mining techniques to compare a process model with an event log of the same process.

What are the different types of nonconformant cases?

We can separate nonconformant cases into two main categories:

Events that don’t follow the reference process steps

Although these events are specified in the reference process, they cause process variations because they occur in the wrong order. Here are some examples of unfitting events:

  • Repeated events: Some events might not work as expected and need to be repeated to complete the task. There might be a problem in this event that cause repetitions in those events.
  • Skipped events: Processes can skip specific operations and continue without executing them. Skipping events might cause errors in the next steps and create additional costs and time to rework.
  • Reworking: Some processes require reworking and go back to the previous steps to complete the task. This situation prolongs the process cycle time and creates additional costs.

Additional events that don’t exist in reference processes

These are the unexpected events that occurred in the event logs. As they are unexpected, they are not specified in the reference model. Unless they exist the majority of actual processes or contribute to the process efficiency, the reasons for those events should be identified. They should be eliminated as they cause process variations.

How does it work?

Conformance analysis is used for identifying process deviations by comparing ideal and actual processes based on event logs. Below you can find a conformance analysis interface example from a process mining tool.

Source: Wikipedia

Here is how process mining solutions execute conformance analysis:

Choose a reference process

Businesses need to choose a reference process that can be thought of as the ideal process. The reference process is how companies should maintain their operations and only consists of conformant events that companies want to achieve.

Use event logs to see actual processes

Process mining tools leverage event logs to generate a visualization of as-is processes. This includes all occurred events while businesses handle their operations. In the end, they have a clear understanding of how their processes actually work and are ready to conduct conformance analysis.

Identify events that don’t conform to the reference process

After choosing reference processes and having a full picture of as-is processes, conformance analysis compares them to identify nonconformant cases and how close their actual processes are to the ideal. For this analysis to make sense, the majority of actual processes should conform with the reference processes. However, in real-life, this might not be the case because actual processes can occur in a completely different way than expected.

What should businesses do after conformance analysis?

After conducting conformance analysis, businesses should first understand the context of nonconformant cases. Unfitting or additional events mostly occur because of the problematic issues in the processes. For example, the employees aren’t trained enough, and they are completing their tasks in an undesired way. Businesses should identify root-causes like that and find solutions to eliminate them. As we indicated in our ultimate process mining guide, process mining tools can provide recommendations to reduce process variations in the future.

However, all deviations don’t need to be eliminated; they might have occurred due to different reasons:

  • The company may have the wrong idea about their reference process. The additional steps that are not specified in the reference process might be necessary to complete the task. In this case, companies should review their reference processes.
  • Some deviations might be on purpose. For example, when a loyal customer arrives, the company can skip some of the required process steps to provide faster service.

Why do companies need conformance analysis today?

Businesses mostly want to reduce these deviations because nonconformant cases can:

  • generate additional costs
  • cause higher use of resources
  • decrease product/service quality
  • lead to auditing problems and violate specific regulations

Conformance analysis is a process mining feature to help companies handle these variations. By identifying the unfitting and additional events in processes, businesses can avoid those issues beforehand. As the average conformance level is around 40 – 65% according to QPR, conformance analysis becomes critical since many tasks don’t follow the ideal procedures of businesses.

As companies understand the importance of identifying process variations, conformance analysis becomes a more popular process mining feature every year. In a 2018 Gartner survey, while 23% of respondents were using process mining for conformance analysis in 2017, this share is estimated to increase to 30% in 2020.

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