Workshop: Predictive Maintenance Data Assessment

Avoid downtimes, become more efficient or increase customer satisfaction: Is predictive maintenance a relevant topic for you?

The initial situation:

You have already collected data and wonder to what extent it is usable? Or you are planning to start collecting data and want to make sure that you do so in a target-oriented way?

Then you should take our Predictive Maintenance Data Assessment Workshop!

The process:

In the first step, our experts look at your data stocks or your data strategy from a predictive maintenance perspective and quickly give you feedback on whether you can build on it.

Scenario A) Your data can be used for a predictive maintenance scenario:

  • Then, in the second step, we start working on your predictive maintenance scenario, jointly define a PoC (Proof of Concept) and drive the scenario forward to the roadmap for an MVP (Minimum Valuable Product).

Result: You have a roadmap for one or more PoCs in your hand, which you can use to get started right away - with us or on your own.

Scenario B) Your data is not (yet) usable for a predictive maintenance scenario:

  • If your data is not usable on a 1:1 basis or you have not even started collecting it, we will work out a targeted data strategy together with you in the second step - against the background of your business and your (planned) predictive maintenance scenario.

Result: You have a roadmap to a data strategy suitable for predictive maintenance in your hand, which you can use to get started straight away - with us or on your own.


Inventory analysis

Identification of deficits / Identification of data sources / Data quality analysis


Planning of data provision & preparation / Identification of use cases and their prioritisation / Identification of added values & monetary potentials / Agreement on project success factors

Your results

Agreed action plan / Prioritised use case catalogue / Monetary effects of the use cases / Scope & Objectives of the PoC

The aim of our analytics strategy for predictive maintenance is to identify optimisation potential:

What goals does your company pursue and which predictive maintenance measures support a sustainable success strategy?

What measures need to be taken to ensure that predictive maintenance is supported and exemplified by all the people involved?

Which processes are relevant for optimisation and contribute significantly to influencing quality in production?

What is the technological status of your company with regard to predictive maintenance and which tools are already being used?


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