Currently, we can find many articles in the media about artificial intelligence, industry 4.0 or 5G technology. Thus, it is difficult to overlook the importance of data for the modern economy. However, process mining still does not receive sufficient attention. It may seem surprising, but often even specialists working with data on a daily basis are not aware of the possibilities of these tools. For this reason, we present the most important arguments why you should use process mining and what outcomes you should expect. 

Efficient and automatic generation of process models

Tasks such as collecting information about the process, mapping activities and process analysis are not new. They were undertaken by companies for decades. But so far it has been a very tedious process and often based on arbitrary assumptions. It also did not always properly reflect the actual activities carried out by employees. Process mining addresses these challenges:

• Time economy: with process mining, you don’t have to build the process manually, because the algorithm does the work for us. This allows you to focus on what is really important, which is the process analysis.’
• Results basedd on objective data: the entire process mining analysis is carried out based on actual process logs. As such, relies to a far lesser extent on arbitrary assumptions, estimates or human intuition. The human factor is still important and has its place, but we are gaining a tool that allows us to look at the results objectively based on actual data

• Capturing all the complexity of the process: When performing manual process mapping we are not able to capture every single detail. It would be totally unrealistic. Process mining, on the other hand, contains (depending on the quality of our data) up to 100% information about the process. Therefore, if there is such a need, we can drill down to every single activity or variant of the process.

At the moment, process mining is one of the best tools that allow you to effectively and efficiently analyse process data.

What results can we achieve with process mining?

The use of process mining greatly facilitates the analysis of processes, and some cases, process mining may even be indispensable. Using process mining, we can easily perform, among others the following analyses:

• Fulfillment time and number of steps in the process: These are basic process performance statistics. However, with to process mining, we can easily verify the execution of the process depending on the time range, people involved or type of client.
• Identification of bottlenecks: Process visualization with filtering options allows you to easily see where delays occur in the process.
• Identification of unnecessary activities: Thanks to the transparent visualization of the process and the access to all activities for which there are logs, it is very easy to find those places where there is a loop in the process or some unnecessary activities are performed.
• Root cause analysis: When we find bottlenecks or loops in the process, we can very easily see how these implementations of the process differ from the desired version. For example, you can check what resources were involved, what cases are related to these cases, what events took place before the delay occurred.
• Process audit and compliance: Process mining allows you to compare a an ideal, reference model of the process with its actual execution. By doing so you can check what is actually going on in the company, conduct process audits or measure the process performance with KPIs.

The efficient use of process mining opens completely new opportunities for obtaining information about the activities actually carried out in the company, and thus for process optimisation and increasing profitability.

Perfect tool for sensible development of the company

Carrying out initiatives to improve internal processes is usually quite a challenge. It requires the involvement of the company’s employees or external consultants. It is necessary to have a lot of conversations and meetings with people working at different stages of the process. Inevitably, the results of this type of analysis are to some extent qualitative. Thus, they are subjective and can be challenged by people adopting a different set of assumptions. Process mining addresses this issue by offering the following benefits:

• Precise problem identification: Process mining analysis allows us to accurately identify places in the process that require improvement and provides information on the causes of the problem.
• Recommendations based on hard data: Process mining is based on actual activities and lead times. This provides you with actual numbers in the discussion on potential improvements in the process. It also allows you to get away from disputes arising from differences of opinion and assumptions. Rooting the discussion in numbers and facts diametrically facilitates the development of solutions accepted by all parties.
• Team involvement: The results of process mining are visual and intuitive, which makes it way easier to involve your team. You can show employees a process chart, point to potential issues and ask for feedback. In this way, you not only get more information, but also give voice to employees.
• Estimating the effect of potential iniatives: After developing a list of potential changes in the process, it is possible to reasonably estimate the effect that they will have. This way you will be able to make the right decisions about what initiatives to implement. Moreover, access to the right data gives managers much more confidence that the direction of changes is correct, and that the company’s team is more willing to accept them.

The above-mentioned features make process mining an ideal tool for managers and specialists responsible for process optimisation, lean six sigma or, in general, initiatives aimed at increasing the efficiency of the enterprise. With process mining, you can accurately define what improvements should be implemented, justify them with numbers and gain support within the organization for their implementation.

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