The Top 10 Reasons Business Analysts Should Leverage Process Mining

Aug 20, 2023

Process Mining is a subject that has garnered a lot of attention over the past two to three years. Much of the noise has centred around the mergers and acquisitions in the vendor space, and contrary to what some write, it is still in its infancy when it comes to end user adoption.

Some academics and industry analysts suggest that Process Mining is a technique that replaces the need for traditional business and process analysis, but this is never likely to be the case. Instead Process Mining and its closely related cousin Task Mining, are complementary to traditional approaches, and should be thought of in the context of “and” rather than “or”.

For the past 30 or more years we have increasingly applied automation to processes, both with and without proper documentation. The result is that many of the processes we use, business decisions taken, rules applied, and customer journeys are now embedded or hidden within systems. This cloak of “invisibility” makes it practically impossible for us to apply traditional analysis techniques to discover and analyse these rules, processes decisions and journeys.

Conversely, Process Mining only discovers processes, decisions and journeys that go on inside systems, while Task Mining discovers how users interact with (some) systems. Therefore, no amount of Process or Task Mining will help when dealing with human-to-human interaction. For that we still need traditional business and process analysis techniques like workshops, interviews surveys etc.

Without diving (in this article) into “how” to do Process Mining, let’s look at why Process Mining is an important tool for business analysts and the benefits it brings to business analysis teams.

  • Know what’s really going on in your company. A key risk in traditional business analysis is that often the information we collect and the models we create and based on people’s perceptions, rather than the reality. The fact that Process mining can automatically discover the actual processes as they are executed in your organization, means we can start to deal more with reality. Whether we take that reality and start to analyse and address issues directly, whether we use reality to shape discussions with people to reshape perceptions will be situationally specific. But, for sure anything that helps us ensure we are fixing the right problems or uncovering the right issues, must be a good thing.
  • Act on facts, not opinions. Building on the previous point, it is not simply a case of using Process Mining to discover the process model or process paths. Process mining provides objective and reliable data on how your processes perform, such as cycle times, bottlenecks, deviations, and costs. Just as with traditional approaches, the risk Process Mining helps to isolate the true reasons for process failure, and if you are using the right tool can also help understand how many problems occur through the interactions between and across different processes.
  • Make the most of available data. Any type of business or process analysis is only as good as the data used to inform potential decisions. All too often the volume of data can overwhelm human analysis, leading us to need to take decisions based on small samples. With Process mining we can leverage huge datasets, and it is not uncommon for Process Mining to be performed on hundreds of thousands of cases, containing hundreds of events. This information is already stored in your information systems, in event logs, audit trails, or databases. Process Mining simply makes that data both more accessible and consumable, so that we can increase confidence in what we are doing) or not doing!).
  • Unravel complexity. Sometimes trying to undertake business or process analysis is like searching for a needle in a haystack. Process mining can help you to visualize and understand complex processes and the events contained within them, across multiple actors, systems, and interactions. The ease with which modern process mining tools can, with a no-code approach, filter sort and present data makes it easy to identify root causes, outliers, and other issues.
  • Harmonize process variations. Process mining can help you to analyse and align the different ways of executing the same process across different units, teams, or regions. Creating harmony is important, as it is quite possible that multiple variations are a good thing not a bad thing. Often people considering process mining are led to believe that there is a single “Happy Path”, most often this is not the case and we either confuse the idea of a Happy path, with the fact that that it is just the most common path. Harmonizing process variations across common cases is a way to ensure consistent outcomes and outputs.
  • Increase efficiency and reduce risk. Eliminating waste, reducing rework, ensure compliance and error reduction are all worthy goals of business and process analysis. They are also areas where the application of process mining will likely cause any number of aha! moments. By looking at the total end to end process, it often becomes apparent that the obvious fix may not be the smartest. By visualising all impacts and using simulation to test any hypothesis will ensure that you are fixing the right issues and gaining true efficiency. Thus, process mining is a great vehicle for higher productivity, quality, and customer satisfaction.
  • Support process automation efforts. There is no getting away from the fact that much analysis and design today is centred around automation. Whether you are considering low-code/no-code solutions, RPA or simply planning an ERP or system migration, process mining delivers significant value. As mentioned in the previous point, using simulation as a part of process mining enables insights into the impact of automation. Often automation is applied to the wrong part of a process, or the wrong type of technology is applied. By testing the impact of automation, running multiple scenarios and analysing costs and resources enables smarter decisions. Identifying and validating automation options before implementation saves significant time and reduces wasted effort on misguided automation, it also helps in analysing costs and benefits that can be used in business case creation.
  • Validate process conformance. For most people trying process mining for the first time, it often surprises them just how different the As-Executed process model they discover is from the As-Intended/As-Designed model they thought they had. Process mining helps you to compare the intended and real process models and detect any deviations or non-compliance issues. Those conformance/compliance issues maybe down to poor design, lack of training or any other number of issues. In some cases, team members have simply figured out a better way of serving customers, which can be a good thing, however, in highly regulated industries this lack of proven conformance carries significant business risks.
  • Monitor and improve processes continuously. The use of process mining for process monitoring and continuous improvement is not often discussed. A lack of discussion on this topic serves to undermine the long-term value of having a good process mining solution available to you. Aside from the fact that in those compliance situations or customer experience-oriented environments constant monitoring is key, monitoring saves you time and effort. Think about how much money organisations spend on customer satisfaction surveys and NPS data collection, with outcome-based process monitoring there is no need for it. You can easily see whether you are delivering on-time every time, predict when you might not deliver and issue alerts to fix issues before they become issues. Although in its infancy real time process monitoring with predictive alerts will become standard within a few years. As more and more processes become automated, it will become less and less possible to undertake monitoring and improvement through anything other than data monitoring.
  • Create a single point of truth. The concept of a single point of truth is perhaps overused and potentially abused. In this case the fact base we are referring to is the facts about what is actually happening or going to happen with a process. By reducing the need for opinion only based decisions we can make it easier to get understanding of issues and buy-in for change. Some vendors, such as Apromore, can hold not just single process views, but to hold your entire process architecture and thus can execute analysis where process interactions may cause problems and help business managers understand that that the problem does not lie within the process being analysed but instead in a related process.

In conclusion when it comes to Process Mining for Business Analysts, it should not be a question of whether to use but instead a question of when and how best to use. It is a technology, just like Generative AI that will transform the art and science of business analysis. The key is to find and apply tooling that is created and priced to enable it to be a tool in every analyst’s toolbox, something more akin to an “ultrasound” scanner in hospitals, and less seen like an MRI scanner that is used occasionally and only for serious situations and by highly trained staff. To date many Process Mining solutions have been priced and pitched as an MRI for business, which has hampered rather than helped get broad adoption.

Author: Mark McGregor

A former Research Director at leading IT industry analysis firm Gartner, Mark has an extensive background in enterprise architecture, business process management, process modelling, process mining, and change management. He has held executive positions with several technology companies. Since retiring from Gartner, he has worked with clients such as Changepoint, Erwin, Mega, Planview, LeanIX, Signavio, ABBYY, Workpath, Axellience and iGrafx. Currently he serves as a Product Marketing & Strategy Advisor with Apromore, while also providing advice to investors and management consultancies on these specialist markets.

Mark has authored or co-authored four books on business and process management, including “Thrive! How to Succeed in the Age of the Customer” and “In Search of BPM Excellence” and “People-Centric Process Management”. Widely respected for his knowledge and views on business change, he is the creator of "Next Practice" and has been described as a “BPM Guru," a "Thought Leader" and a "Master of Mindset”.




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