"Process Mining is an analytical approach that uses data from IT systems to obtain objective insights and uncover hidden problems.”
For years, monitoring, analysing and optimising processes has helped companies and organisations to eliminate internal inefficiencies. Due to digitalization and automation, more, and more important parts of these processes are taking place in and between IT systems.
Process Mining - a more automated way of monitoring, analysing and optimising processes - makes process optimization easier in these digitalised processes. It is therefore an upcoming topic and typically supports the business with:
- Identifying bottlenecks
- Recording of human error or breaches of procedures
- Streamlining processes
- Anticipating problems and recommending measures
Converting the massive amount of available process data into meaningful insights, is the biggest advantage. After all, IT systems - which are used today to support business processes - keep track of countless data in all kinds of log files. Such log files, which are often very detailed, contain an enormous amount of information that unfortunately often remains unused. All too often, processes are still approached from a theoretical standpoint rather than analysing real-time data. By doing so, a huge amount of data remains untapped while the possibilities are endless.
The model example of a purchase process can be regarded as a straightforward process. In reality however, many differences and variants can arise. Even between business units within the same company. Mapping out a process can be performed in various ways but is usually done based on interviews. The findings of these interviews are compared to the process model, whereafter internal controls are tested, altered and/or implemented. This is typically a manual, labour-intensive exercise, with no certainty as to whether all events and variants have been documented. So usually the starting point is a theoretical process model which is tested against reality to make adjustments.
Process Mining takes the opposite approach and uses the underlying process data (often referred to as 'event logs') as the starting point of the analysis. This process data is used to visualise the way processes run which can afterwards be used for analysis purposes. Not only the time of an activity can be recorded, also additional relevant information as the source (e.g. person or machine) that performs or initiates the activity (e.g. order size in number or amount of money) can be taken into account. In this way, Process Mining makes it possible to make in-depth analyses and investigate why a process does or does not run efficiently.
Drawing up the process sequence for each transaction is impossible without extensive automation. Process Mining solutions have been developed specifically for this purpose and can map out processes intelligently using the event logs. All processes and variants within a process are recognised and visualised in an intuitive way. Special and suspicious routes can thus be identified immediately. The possibilities with Process Mining tools are endless, yet 4 major focus points can be distinguished:
- Visualise current processes using event logs, without any prior information
- Identify (immediately) all possible variants within a process
- Get a clear picture of the different ways of working between departments, companies, ... and determine the normal process flow that can be used as a gold standard.
- Use case: Load process data into a Process Mining solution and find out how many variants exist within that process and where any bottlenecks and/or loops are located.
- Compare the actual process sequence with process models to reveal deviations and errors in the process. e.g. inefficiencies, weaknesses, striking patterns, or potential fraud cases.
- Identify the problems with the highest priority with regards to the related costs involved and the time invested in them. Make an in-depth analysis of the root causes.
- Use case: For organisations with multiple ERP systems, standardising processes is not an obvious task. Process Mining helps to compare and benchmark the different systems. After the standardization, Process Mining can support continuous monitoring of processes and make adjustments possible.
- Turn potential areas for improvement into added value: expand existing process models or improve them.
- Learn which changes within the process are most appropriate, thanks to insight into the impact of possible changes.
- Automated process model detection is possible and indicates bottlenecks, inefficiencies and compliance issues and their impact. This new knowledge can be used to improve the process:
• standardize (fewer variants within a process)
• shorten (shortening lead times)
• run in a more efficient and reliable way (automating and eliminating unnecessary steps)
- Examine whether decisions taken achieve their objective
- Use case: Set up an alert mechanism each time a purchase order has been approved twice (i.e. a loop is identified)
The traditional way of optimising business processes requires a lot of time and resources to gather all necessary information. The result often remains a theoretical process model that reflects reality to a limited extent and does not include all deviations.
Process Mining formulates an answer by using an innovative, analytical approach in which (log) data generated by IT systems are used to gather objective insights and to uncover hidden problems that occur during the execution of business processes.
Are you curious what Process Mining can do for your organisation?
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