Those who want to evaluate their data today are confronted with a multitude of possibilities and a flood of terminology that does not make selection easy. Around the term big data, solution clusters have formed whose meaning is difficult to understand, especially for beginners. Every technology has its own purpose and its own way of dealing with data. Where the new Process Mining analysis tool can be placed between other methods and terms such as Business Intelligence, how it works, and how companies ultimately benefit from it – this is what the following article should shed light on.
The actual value of the data lies in their evaluation. The entire process of preprocessing, searching and evaluating, ie the systematic use of statistical mathematical methods with the aim of pattern recognition, is summarized under the term Data Mining. Technically, data mining uses algorithms that help establish relationships between the data. Of course, priority is given to finding correlations that contribute to decisions. Data mining is thus used in every intelligent evaluation – the only question is under what aspects.
Business Intelligence (BI) platforms include processes and processes for collecting, evaluating, and presenting data. The aim or goal is reducing costs, minimizing risk, and adding value. All possible KPIs can be evaluated – information about your own company, competitors, customers or the market development. Prerequisite: users must specify exactly what they want to investigate – and what the goal of their analysis is. BI uses multi-dimensional analysis to correlate data, identify patterns and discontinuities, and answer previously defined questions.
The approach of defining evaluation criteria in a BI dashboard prior to analysis is inherently limiting because it only highlights portions of a process or specific data and correlations. Do you always know in advance what is relevant? Classic BI vendors, who initially focused on connecting more and more data sources and unstructured data (such as social media ), put a new focus on freer analysis capabilities.
Unlike BI, which focuses primarily on individual metrics and provides many insights, the innovative big-data technology Process Mining is based on a more comprehensive approach. Here, not individual KPIs, but processes end-to-end and on their Analyzing efficiency – and presenting it exactly as it happens in reality.
Process Mining collects the digital process traces in the company and puts them together. By this way process sequences can be visualized from beginning to end and in all their possible variations. Thanks to the new level of transparency, companies can identify weaknesses and inefficiencies as well as deviations from the target in real time – regardless of which IT system uses process mining.
This approach in one’s own sovereign space enables a purposeful optimization of internal processes and thus promises a very fast ROI. Users do not have to commit themselves to predefined questions. They can take an unbiased look at their processes, identify previously unknown problems.This will derive the right action in the event of bottlenecks and optimization potential. In contrast to BI, Process Mining can be used to find answers to when, where and why problems have occurred in the supply chain, for example.
With these data analysis solutions, the end of developments is far from over. Big data technologies are increasingly turning to automation and machine learning. The first steps in this direction are made. In the field of process mining, machine learning functions already enable the automatic root cause analysis. Machine learning functions also enable the derivation of concrete recommendations for action from the results of the process analysis.
The development is still at the beginning of its possibilities and can still expect a lot. Artificial intelligence will be a decisive competitive advantage for companies in the future. With little effort, as much data as possible can be used in the company and made available for targeted optimization. That’s why it will go more than ever in the future. And that’s exactly what Process Mining supports.