In many companies, extremely valuable data is simply lying around unused: Transaction or event logs, for example, from ERP, CRM, production control or the ticket system. This data is usually available anyway, but is neglected and often basically only eats up system resources. They form the basis for generating a comprehensive digital view of business processes with comparatively little effort and immediately deriving measures for optimization.
Once a business process has been defined, it is tacitly assumed that it will later be lived in this way or at least in a very similar way. In fact, external influences, special cases, errors or even qualification deficits lead to an abundance of various deviations from the standard process. Without technical support it is practically impossible to recognise these deviations in detail, to state the consequences for quality, costs and throughput times and to derive suitable measures. Process mining technology offers all of this, making processes understandable, analyzable and assessable on the basis of their digital footprint.
In most companies, the core of BI landscapes is the analysis of rigid key figures. How the value of a key figure comes about, what it essentially means and how the process on which it is based is optimised is rarely questioned.
Process mining offers immense potential to improve the quality of key figures and thus to make the management of companies more successful.
Process mining can also address the cause and not just - as is so often the case - the symptom. We are now no longer just analyzing the result in the form of conventional KPIs, but rather the process that led to this result.
With the help of process visualizations and benchmarks, runtime analyzes and compliance checks, we can identify developments before they influence the result.
Getting started with process mining is basically no big deal. The data is usually available, the experts are in-house and the tools usually offer templates that allow initial evaluations. The tool providers have already prepared content and ready-made data models for many standard business processes, meaning that meaningful analyzes can be carried out in four simple steps:
Analysis of the actual process using a completely data-based approach based on the transaction log files from the underlying source systems.
The basis of all process mining applications is the event log. It is made up of all individual actions and can be enriched with any number of attributes (e.g. material, location, supplier, customer).
Management and controlling of the process in an adapted template app, definition and measurement of relevant KPIs, analysis of process disruptions and variants, implementation of benchmarks , deriving measures.
technology und possible uses
celver than yours Process Mining Sparring partner
Assistance with the tool selection
Proof of Concept (PoC)