Over the years, various performance improvement techniques and methods have been introduced, like Lean and Six Sigma. A disadvantage within these traditional optimisation methods is that performing the corresponding analyses often lays a heavy burden on the organization, and often – unintentionally – is delivered as a one-off. The data is collected in samples and results are often poorly reproducible and are difficult to structurally embed when returning to the order of the day. The rise of a field like Data Science is a driver to increase the quality and lead time of these kind of insights.

Farewell to Brownpaper sessions

With the TU Eindhoven as a driving force, a field has developed in recent years that allows processes to be analysed very accurately, completely and repeatable. This field is called process mining. Based on the notion that more and more systems register each transaction in transaction logs, with metadata like user and time, processes can be analysed in much more detail. Not only the ‘common’ process is analysed, but this provides insights into all variations that have ever occurred, how long certain actions within the process take and what the impact of the quality of execution is on the lead time, action time, and outcome of the process. As a result, the process generated is identical to the process performed. This is a big advantage over Brownpaper workshops or sampling where it is not possible to get this overall image.

Application of Process Mining in the Finance & Control domain

Activity based costing issues

Traditionally, distribution keys would be based on the basis of time-consuming and burdensome organization stopwatch measurements. Process mining allows an estimate of the duration of a particular activity to be accurately and can be realised continuously and at a lower cost than the traditional low-frequency stop-watch measurements.

Audit and compliance controls

To what extent is the execution of the processes (be it manufacturing or service processes) compliant to legislation? This can be identified instantly, frequently and with a complete scope of all occurrences, making it possible to take action to make the processes compliant. Think about specific procedures in the banking sector or in the government. Where, for example, four-eye control principles are of importance and errors have major financial and image risks.


Existing benchmarks often focus on output and give only a limited insight into the “why”. In addition, process mining makes it possible to determine the cause of variation and what the impact of an adjustment in the process will amount to.


Benefit tracking

After approval of the business case, there are generally few incentives to also set up monitoring. It takes a lot of effort to set up and implement the measurements. Process mining makes performing tracking on process indicators less burdensome and easier to perform repetitive assessments at a higher frequency.

In summary, it can be said that in the Finance & Control function, process mining can add value by realizing analyses in a fraction of the time relative to labour-intensive sampling techniques. In addition, it provides effective and detailed fact-based analysis capabilities that give the CFO more actionable insights at a faster pace to operate as a business partner and effectively enable the organization to realize day-to-day continuous learning.