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Keeping Everything Clean with an MES Audit

Reading Time: 3 Minutes 01.09.2023 Currents & Trends

How to optimally implement the smart factory process

Companies must attach the greatest importance to clean data when transitioning to a smart factory. But how can you verify and ensure that your company only produces high-quality data that can be accessed transparently? More clarity can be brought to this by running a maturity level analysis with the deployed manufacturing execution system (MES). 

MES maturity level analysis  

As the central element of a self-organizing production environment, the corporate MES requires high-quality data if it is to work efficiently and yield meaningful results. The question is whether your own MES in combination with an Enterprise Resource Planning (ERP) software actually has the maturity level that is required to digitalize your company.

As the link between top floor and shop floor – enriched with logistics data from the ERP system –, the MES generally allows for optimizing production processes, proactively identifying problems and creating meaningful analyses and KPIs relevant to production. Bidirectional interfaces are used to exchange data between the ERP system and the MES. The scope of the communication and the exchange is best determined by analyzing the actual situation.

Identify potentials and develop solution scenarios

Based on comprehensive KPIs from the MES and ERP system, you can conduct a maturity level analysis to identify and exploit potentials and develop suitable solution scenarios. This allows you to create a first roadmap to increase the efficiency and profitability within your production. It should be clearly structured and comprise the following important steps to achieve perfectly organized qualitative data management and processing:

  • Specify clear goals

There must be a constant, transparent and constructive exchange between management, employees and IT department. Only then can you develop a mutual understanding and define and implement realistic goals. 

  • First assess the current situation

The current MES maturity level is analyzed using lean manufacturing methods to reduce unnecessary consumption in the manufacturing process. In particular, you have to analyze the material, process and information flow on the shop floor as well as the IT infrastructure and data management. The goal is to identify unnecessary transports and movements of staff, devices or machines, excess stock, waiting and inactive employees, idle plants and equipment or an overproduction of goods. This concerns a waste of resources as well as other sources of error. 

  • Prioritize use cases

In the next step, you describe and finalize the top three to five MES use cases of your company. This subprocess ranges from the description of the problem and MES functions through to the definition of the users' goals and finally the rollout.

  • Analyze potentials and set priorities

Specify, analyze and prioritize all potentials unlocked by the use of an MES in production. The results are subsumed under a decision matrix that includes the return on investment (ROI), the balanced scorecard and the portfolio, among other things.

  • Create a roadmap

Based on the results from the actual state and potential analysis, you can derive a roadmap that defines the specific phases with MES functions and maturity level implementation.

  • Initialize the project

By using project management methods and the previous audit results, you can prepare the project initialization for a rollout. At the same time, you define the further strategy.


An MES audit is an important step toward the optimum implementation of a smart factory. A maturity level analysis is essential to ensure high-quality data and enhance efficiency. In doing so, potentials and synergies from the interaction between the MES and an ERP solution are used to develop suitable solution scenarios. The roadmap for data management and processing comprises several steps that your company should follow. This structured approach helps you to optimize your manufacturing processes, proactively identify problems and generate valuable analyses and KPIs. 

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