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3 Steps to Identify Your Happy Paths with Process Mining in '24

As business leaders and analysts are already aware, efficient and effective management of business processes can reduce costs, save time and improve customer experience to the extent that it can even prevent disastrous scenarios like Chernobyl. One way to manage your operations efficiently and effectively is to identify happy paths and standardize all business processes according to them. However, this strategy can be challenging and time-consuming without process intelligence software like process mining

In this article, we’ll go over 3 ways you can benefit from process mining to identify, model and test happy paths. 

What is a happy path & how to test them?

A happy path, also known as happy flow, is the most efficient and effective workflow from the first step until the final one. For example, in a loan approval process, a happy path refers to zero errors in tasks and activities and a smooth flow until the final response. 

Happy path testing verifies that the required validation is met, and there are no other scenarios that produce better results than the happy path. To do so, analysts map happy paths as an activity diagram where they can show the flow of actions with arrows and geometrical figures.  

Process mining can be a useful tool for determining process happy paths since it can automatically discover and model processes and compare these workflows against ideal models or performance KPIs.

The way process mining can streamline testing for happy paths include:

1. Automatically identify happy paths in your processes

Process discovery is a core process mining capability that helps users automatically collect, analyze and model process data to identify the happy path. 

With process discovery, users can map how processes are executed and compare them to process performance KPIs. Analysts mark the process flows with higher costs, delays or waiting time as unhappy paths and choose the process model which provides the desired outcome at the lowest expense and shortest time as the happy path.  

The figure below shows how a process mining tool can discover, map and compare operational workflow against performance KPIs. 

Source: IBM Cloud Pak for Business Automation

2. Seamlessly detect deviations with underlying reasons 

Processes can have various deviations from the happy path due to errors and inefficient practices. 

Users can analyze these process variants and pinpoint the root causes behind them. To do so, they can benefit from the automated root-cause analysis feature that many process mining vendors offer. Based on their insights, the users can recommend changes to enhance these disrupted processes. These improvements include actions such as:

  • Correcting errors
  • Eliminating unnecessary steps
  • Automating manual-tasks
  • Standardizing and orchestrating 

For example, Terberg, an industrial transportation company from the Netherlands leveraged process mining for their purchase-to-pay and accounts-payable processes. The company identified a high number of delayed deliveries and discovered that deviations were related to the warehouse management processes.  Once Terberg executives establish the happy path and ensure that employees internalize it, they could reduce costs and save time. 

3. Constantly monitor corrected processes 

Conformance analysis, another core process mining capability, can allow users to compare happy paths against corrected processes to assess the compliance levels. As a result, analysts can constantly monitor their processes to determine and correct errors and frictions. If the process requires regulation from a third party, constant monitoring can also ensure that processes following the happy path comply with rules and standards. 

For instance, South African construction and material company Afrisam deployed process mining to monitor their operations in real-time and identify and visualize their risks.  

Further reading

Discover more on process mining capabilities and how they can improve and manage business processes:

Review our data-driven and comprehensive vendor lists for process mining to choose the right tool.

If you have doubts and questions, let us know:

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Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Hazal Şimşek
Hazal is an industry analyst in AIMultiple. She is experienced in market research, quantitative research and data analytics. She received her master’s degree in Social Sciences from the University of Carlos III of Madrid and her bachelor’s degree in International Relations from Bilkent University.

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