Industry 4.0, business intelligence, big data, data mining and now process mining – terms that affect our working world on a daily basis. But what’s behind that? What are the impacts of the new technologies? And the most important thing: what is their use for companies?
Digital data flood in industry 4.0
Digitalization in companies is increasingly starting to resemble an accelerating spiral, since nearly all processes in the business world are depicted electronically. The rapid progress in technological innovation results in numerous approaches to problem solving and in multifaceted perspectives. This change into a consistently digital world creates masses of data and digital footprints containing useful information that can be used for diverse analyses. But how to read suitable information out of the abundance of individual, apparently incoherent data? This topic is taken up by several disciplines with different objectives. Some of them are already established in practice, but are limited exclusively to the evaluation of data from specific questions.
Rethinking needed: holistic view of the data in the process context
For companies, it is no longer sufficient to simply examine data in relation to defined questions. Rather, they want to understand the interrelationships mapped in the business processes. This dynamic approach to the data landscape requires some rethinking, since here, the focus is rather on the relationships between all areas of the company. The process mining method adopts this claim by examining the digital traces within the IT systems and reconstructing a concrete picture of the business processes from real event data in all possible sources – so-called event logs.
Mining, i.e. “digging” for existing process information, is done with the aid of innovative software tools. The multidimensional interrelationships are connected by means of intelligent algorithms and presented in comprehensible evaluations. More precisely, the relevant data is extracted from the company’s entire information sources and visualized in a simplified form.
The solution: process mining as a basis for business process optimization
Process mining is a way of investigating processes that are steadily becoming faster and more complex. As a result of the analysis, the results obtained can be used to initiate optimization measures. But is creating a cost-reducing, efficient optimization concept based on a flowchart really that easy? The processes visualized through process mining are based on actual data, often in real time, and provide information about any weak points, problems or non-compliance with the defined business processes. Furthermore, an unbeatable point in terms of project time and costs is that the actual situation is recorded much more thoroughly than it would be in the classical way – in the form of interviews.
However, in order to derive highly meaningful suggestions for improvement, a deeper background knowledge is necessary. This task is performed by the data scientist, who not only has the ability to systematically use large amounts of data, but also has the according expertise regarding the methods of evaluation. In addition, process mining requires sound know-how and a broad understanding of the entire process landscape, including the internal and external processes affecting the company. The data and process specialist now has the task of transforming the knowledge gained from process mining into improved and cost-efficient processes.
In tools such as the Horus Business Modeler, target processes can be modeled and simulated based on the analysis results in order to derive suitable recommendations for process improvement.
With a subsequent project-accompanying comparison of the actual processes identified through process mining with the target processes, the effects of the developed improvement measures can be checked continuously. Possible weak points can already be detected and eliminated during the design phase. This process-oriented approach, the sensible use of the powerful tools and the targeted focus on the relevant issues is becoming an increasingly important part for an efficient optimization of the corporate landscape.
Author: Sabine Rudolf
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