Industry data driven operational teams
What you should be looking for?
With the development of Industry 4.0, data is becoming a key driver to tackle current industry challenges: competitiveness and profitability, environment footprint reduction, greenhouse gas emission reduction, increased quality and regulatory requirements.
But Industry 4.0 goes far beyond that. It is a real journey for plant’s operational teams. Data and Digitization are transforming deeply how these operational teams are working, and we must say, it is a great opportunity for them as well as for their organisation.
How activities around data are handled until now? Let’s be honest, it is not the most efficient. Usually operational teams define their needs (dashboards, analytics, control cards, OEE…), then IT/OT teams prepares the proper tools to answer their needs built on generic technologies (Data Base, BI, Analytics…). Then follows long and exhausting back and forth exchanges to reach the targeted needs. That’s why today there is still a lot of usages around data that are not fulfilled due to this lack of agility.
One of the root causes of this inefficiency is the fact that the user of data is not the one that has the hands on the tools to build the proper answer to his usages.
In parallel, we can see that operational excellence activities could benefit vastly from the generalised use of industrial data both for real-time activities (detection of abnormal behaviour, process follow-up…) and more analytical activities (troubleshooting, understanding process behaviour…).
In the meantime, new IT approach have emerged, including self-service analytics, no-code application editors, user-friendly BI tools. They are a first step to improve agility around data. But they still lack on key characteristics to really accelerate the process in an industrial environment: embedding the context relative to industrial operations specificities (data model, data transformation model, usages…).
What you should be looking for are solutions offering both: self-service approach designed for the specificity of industrial usages. This combination gives operational teams the capability to build by themselves as they go the tools they need for their day-to-day activities, but also to be agile to make them evolve in time.
Mathieu CURA, February 2022