What is The Core Industrial Data Management Challenge for Global Manufacturers?

Manufacturers have always prided themselves on the strength of a decentralized model. Each production site makes independent decisions, optimizing locally and driving innovation on the factory floor.

That autonomy has been one of their greatest assets and a key reason behind their long-term success.

But as companies embrace data-driven practices at scale, it has also revealed one of their greatest challenges.

Their data landscape is fragmented.

They’ve got silos. They’ve got technical debt. They’ve different architectural setups across their various factories.

Each site evolved independently over the years, and now they’re trying to make all these puzzle pieces fit together into a coherent, scalable data strategy.

So, where do you start?

You begin by acknowledging the tension: You don’t want to control the production units, but you do need shared standards and a unified approach to how we manage and connect our data.

Here are some steps to tackle this:
⇨ Define a strategic target architecture.
⇨ Roll out data management tools.
⇨ Create baselines and frameworks that support, not stifle, local innovation.

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