Process Mining: Added value in process analysis – security for the digitization strategy in manufacturing
For a very long time, process managers were dependent on cost-intensive and time-consuming methods such as interviews or workshops to identify improvement potential in their processes. Due to the digitization of business processes, however, companies also have access to process data from IT systems.
As a key technology for digitization, Process Mining enables automated process analyses based on this data stored in IT systems. For the first time, companies have the opportunity to efficiently uncover improvement potentials in their processes that previously went unrecognized. With the use of Process Mining, ongoing operations can be monitored and optimized, productivity increased and business risks avoided.
In principle, Process Mining can be performed with data from any IT system. Particularly well suited here are applications with a high volume of process flows, high complexity, high competitive and cost pressure and processes in which savings potentials can easily be realized. Besides the administrative and cross-industry standard processes such as purchase-to-pay and order-to-cash, manufacturing processes are another ideal use case, since there is particular potential in the areas of OEE, machine utilization, quality and bottlenecks.
How does Process Mining work?
With Process Mining, users visualize and analyze digital process traces with the aim of continuously improving processes and assessing the success of optimization measures.
IT systems store data for each individual process step. Process Mining tools can therefore display the actual process flow on the basis of time stamps and activities – with all its variants and in full complexity. This allows improvement potentials to be directly uncovered and fact-based decisions on optimization measures to be made.
Data basis & implementation
Before any analysis can be carried out, relevant IT system data must be extracted and logically linked. The logic for the required data model is encapsulated in so-called standard connectors. These contain the required extraction information of the database tables and their transformation into a coherent event log. Thus, standard processes in the ERP environment such as P2P or O2C can be connected relatively easily, provided that the implementation is close to the standard.
However, IT system landscapes are complex, often individually adapted and do not always store data in a way that allows for “out of the box” approaches. Therefore, the initial data extraction and transformation still requires the biggest effort in implementing a Process Mining solution – as in so many projects in the business intelligence environment. For many companies, this often poses a challenge for the implementation of Process Mining in manufacturing. In reality, however, the costs are low in relation to the benefit (experience shows that the return on investment is less than 10 months), and can be significantly reduced with solutions for data preparation, such as the ETL tool LANA Connect developed by Lana Labs.
Practical experience also shows that the introduction of Process Mining is not only worthwhile from the point of view of process optimization, but can also provide important insights into your own system landscape. After the initial connection of the process, an evaluation of the data quality is carried out, which already shows the first potential for improvement. Thus, in many cases Process Mining leads to improvement measures already during implementation that can be extremely valuable for companies’ digitization strategy.
Book your individual demo appointment now and discuss your specific Process Mining use case!