Process Mining can detect and improve inefficient processes. Liongate has built up a high level of competence through numerous large-scale projects and can support companies in analyzing and optimizing processes in real time. Thus concrete recommendations for action can be derived.

 

Traditional process models à la event-driven process chains (eEPK) or business process models and notations (BPMN) are similar to flight plans and route networks. They are helpful if you want to know which options are available for a trip – but unfortunately they are useless if you have to find out where a specific aircraft or train is actually located. Fortunately, there is modern radar and GPS tracking for this. But what about your business processes?

 

In order to gain a real insight into your processes, Process Mining can help you in a direct and minimally invasive way. The basic idea is to unlock the treasures that already lie dormant in your company’s mountains of data and make them usable. Process Mining automatically discovers, monitors and improves existing business processes.

 

Digital Trace Search

 

In everyday IT life, many machine-readable traces inevitably emerge. These are, for example, identification numbers, activity steps or time stamps.

 

These tracks are recorded by a process mining tool. This makes every execution of your process – a so-called process instance – traceable: waiting times, processing times, process loops or even special cases are directly identifiable. This first stage of process mining is the “discovery phase”. Additional adjustments are not necessary in your IT systems, except for the setup of the extraction logic.

 

Process Mining ideally supports existing investments in process modeling. For example, existing BPMN models can be compared in the Process Mining tools during the conformity check in order to identify deviations from the standard. A search for error causes (Root Cause Analysis, RPA) can help to identify the causes of delays or additional effort. In addition, it is also possible to analyze the different ways in which they have been carried out in business reality – the so-called process variants.

 

These functions create transparency about the process reality. The process data obtained in this way form the basis for a better assessment and planning of further steps. The targeted use of Artificial Intelligence (AI) and Machine Learning (ML) or Robot Controlled Process Automation (RPA) leads to an effective improvement of process quality.

 

Targeted and agile procedures

 

A target-oriented and agile process model helps to establish Process Mining successfully and profitably. It is not a question of using a specific tool, but of establishing Process Mining as an accepted procedure among all stakeholders. An interdepartmental approach can sustainably improve end-to-end processes such as Purchase-to-Pay (P2P) or Order-to-Cash (O2C).

 

A systematic proof-of-concept (PoC) can considerably accelerate the necessary learning process. The technology is aligned to the specific company requirements and implemented step by step. The expansion stage can grow with the requirements without losing previous milestones. Further implementation leads to the integration or establishment of a continuous improvement process, support for process modelling or the establishment of a dashboard for process monitoring and the determination of KPIs.

 

We would be pleased to present our concept and approach for ProcessMining processes in detail and create an initial benefit in a proof-of-concept.

 

The airplane on our photo is by the way a converted airplane, which is used as a residential house. You see: It is worth taking a closer look. Contact us!