Guide To Employee Productivity And Process Optimization

How and to what extent does an ERP system support a company in increasing the productivity of its employees? What requirements are necessary for cross-departmental processes to run automatically and without interruptions? And what potential lies dormant in the integration of ERP software and third-party systems with a view to the innovation agenda of a manufacturing company?

The guide is aimed at medium-sized companies in the DACH region and is based on the results of the study »Creating added value for medium-sized companies through ERP software«, which the market analyst technology | PAC 2020 conducted. For this purpose, 100 companies from the region were asked about the central topics on their corporate agenda: increasing employee productivity, process optimization and promoting innovation activity. All of these aspects are closely linked to the use of ERP software:

  • ERP applications provide process control functions or were purchased to improve processes.
  • Whether this can generate added value for the company and how high it is depends to a large extent on the employees who use the ERP system.
  • If ERP applications are too rigid or not flexible enough, they can prove to be a stumbling block for the realization of innovations that depend on ERP functions.
  • Productive employees in view.

The study makes it clear that companies prioritize employee productivity above all. Due to the shortage of skilled workers and the significant economic changes of the past few months, medium-sized companies are faced with the need to deploy their existing workforce even more efficiently.

The study results also show that the optimization of existing processes only takes second place for most companies. This is particularly characteristic of a mature market like the one in the DACH region, where more emphasis is placed on continuous optimization than on disruptive change. It is also evident that the use of artificial intelligence (AI) is very important to companies – both in terms of process optimization and employee productivity.

Finally, the results make it clear that for most companies the focus is more on improving the working environment and processes than on driving innovations and the associated business models are questioned and reinterpreted.

Based on these results, the guide explains interesting ways of positively influencing these three central topics through technical and organizational measures as well as new processes and procedures. For example, the use of AI-based ERP tools and the benefits of ERP-based e-learning offers or process mining to identify optimization potential are highlighted. Readers will also find out what contribution machine learning is already making to manufacturing companies – for example, for demand forecasts in ERP-supported demand planning.

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