Process Mining Use Cases: Who Uses Process Mining?
One of the questions when starting out with process mining is “What is the added value for me and my organization?”. To answer this question, you first have to understand your use case. One ingredient of understanding your use case is to understand who will be using process mining and why.
In the above picture you see some of the most typical places in an organization, where process mining is used. Depending on the role the concrete value will be different. Given your role, you have to think about “How is my job getting easier or better with process mining – compared to not using process mining?”.
Let’s take a quick look at the six use cases above1.
1. Process Improvement Teams
There are many different terms used for process improvement teams in organizations: Process Excellence, Operational Excellence, Process Performance Management, etc. These teams often use Lean Six Sigma methods in their improvement initiatives and, as a central team, help different business units in the organization. Process mining fits very well into their toolbox and allows them to analyze the true processes based on data, rather than through manual inspections and interviews.
Process mining itself is agnostic to the improvement method that you use. This means that it does not matter whether your organization uses BPM, Theory of Constraints, Lean, Six Sigma, or Lean Six Sigma. Process mining does not replace these methods. Instead, the business analysts will use their improvement framework to interpret the process mining results, drive the change, and verify whether the outcome was effective.
The benefit of using process mining in process improvement projects is that the actual processes can be analyzed much faster, and much deeper, than they could be in any manual way. This does not mean that the workshops with process managers and other stakeholders in the business unit go away: Instead, you will start the conversation with them on another level. You can show them the process and say “This is what we are seeing. Do you know why this is happening?” (instead of wasting hours of their time by letting them explain to you how the process works).
Frank Geffen & Rudi Niks, Accelerate DMAIC using process mining
Anne Rozinat, How to reduce waste with process mining
2. Data Science Teams
Many organizations have started to build data science teams, because they have recognized the value of increasing amounts of data and they want to be able to make use of it. Data scientists are typically well-versed in all kinds of technologies. They know how to work with SQL, NoSQL, ETL tools, statistics, scripting languages such as Python, data mining tools, and R. And they know that 80% of the work consists of the processing and cleaning of data.
Data scientists are starting to adopt process mining, because it fills a gap that is not covered by existing data-mining, statistics and visualization tools: It can discover the actual end-to-end processes. Process mining also allows data scientists to work much faster. Even if you could write an SQL query that answers your particular process question, the process mining tool shows you the full process right after importing and allows you to directly filter the data without any programming.
Furthermore, data science teams do not analyze data for themselves, but to solve problems and issues for the business. Process mining helps them to communicate their analysis results back to the business in a meaningful way. Charts and statistics are often too abstract when summarizing a process. So, being able to provide a visual representation of the process to the process manager makes your explanation much more accessible to them.
Anne Rozinat & Christian W. Gnther, Why process mining is ideal for data scientists
Anne Rozinat, Change in perspective with process mining
3. Process Managers
Process managers are responsible for one particular process in the organization. The methods they use are often similar to the central process improvement teams (see above), but instead of working with different departments at different times they focus on their own processes and repeatedly analyze them for continuous improvement.
When a process manager adopts process mining, they have the advantage that they have all the domain knowledge available to interpret the data and the process correctly. This is a great advantage, because process mining does not only require expertise in how to do the actual process mining analysis, but the domain knowledge to interpret what you are seeing is absolutely crucial. At the same time, they typically need some training in a process improvement method (like Lean).
Process managers focus on operational questions and process mining brings them an eye-opening transparency about what is actually going on in their process. Once they have completed a process mining analysis, they can easily repeat it to see whether the improvements were as effective as they have hoped.
Joris Keizers, Leveraging human process knowledge via process mining (the lead time of their core production process was cut in half)
Donna Stewart talks about process mining with Marcello La Rosa (the throughput time of handling simple claims was brought from several weeks to hours)
The role of internal audit departments is to help organizations ensure effectiveness and efficiency of operations, reliability of financial reporting, and compliance with laws and regulations in an independent and objective manner. External auditors provide assurance from outside the organization.
Both groups can benefit from process mining in many ways. Clearly, processes are not all an auditor looks at. For example, an IT auditor also looks at which system controls are in place to prevent fraud. However, when they do look at processes they typically do it in a very manual way (by looking at the process documentation, interviewing people, and inspecting samples). This is time-consuming and does not guarantee that the actual process problems will be detected.
When auditors use process mining they focus on compliance questions (like segregation of duties and process deviations). The advantage of using process mining is that they can be much faster. Furthermore, they can analyze the full process (not just samples) and, therefore, achieve a higher assurance. They can focus on the deviations (by quickly seeing what goes right) and better identify the true risks for the organization. Finally, the visual representation helps them as well, because in the end they will need to communicate their findings in an audit report.
Youri Soons, Experiences of CAS with process mining
5. IT Departments
If you look at process mining from the perspective of an IT department, you are mostly concerned about how well the IT systems (or apps, or websites) are working.2 There can be many different reasons to try to understand how IT systems are actually used. For example, you might want to replace a legacy system. Or you might want to scale back unnecessary customizing to make upgrades easier and save maintenance costs.
More recently, organizations have started to analyze the so-called customer journeys by combining click-stream data from their apps and websites with data from other customer interaction channels. The goal to improve the customer experience is typically at the center of these customer journey process mining analyses.
Customer journey processes are often more complex than, for example, administrative processes. Therefore, it is really important to formulate concrete questions and filter down the data to the subset that relates to your question (see this article for 9 simplification strategies). However, if done right, customer journey analyses can contribute greatly to not just improving the usability of websites and apps, but also to shift the perspective from ‘How are we doing things’ to ‘How does the customer experience our service’ in any process improvement project.
John Mller, Interview before Process Mining Camp 2014
Process mining fits into many types of consultancy projects. Whether you are helping your client to introduce a new IT system (transformation projects), build an operational dashboard, or help them to work more efficiency, in all of these projects you need to understand what the ‘As is’ process looks like.
The most common use case of process mining for consultants is in process improvement projects. As such, the use case is very similar to the one of Process Improvement Teams (see above). But instead of an internal team working with a business unit in the organization, you are coming in as an expert from the outside, bringing with you a fresh perspective and your experience of working with different clients.
Consultants can specialize in many different areas by, for example, focusing on particular industries or IT systems. Furthermore, if you build up your process mining skills, you can help clients to try out or adopt process mining, when they do not have these skills themselves yet.
Anne Rozinat, 7 Reasons for consultants to do process mining
Anne Rozinat, Process mining does not remove jobs it creates new ones
So, which benefits can process mining bring to you?
To find out, first start learning more about process mining to fully understand how it works and what it can do. Download the process mining software Disco and contact us for an extended evaluation license to explore some of your own data sets.
Consider joining one of our process mining trainings. Perform a small pilot project and learn about the success criteria for process mining. To create your business case, keep thinking about how process mining fits into your daily work and how exactly it will help your organization.
This is not a complete list. There are many more use cases, for example, for Quality Improvement, Software Development, Platform Vendors, Monitoring Outsourcing Providers, Risk Management, etc. We have just listed the areas, where we see process mining being used most frequently right now. ↩︎
Note that we are not talking about IT processes like IT Service Management, which in this list would fall under the Process Manager category (see above). ↩︎