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Data that survives the deal.

Most data programmes in industrial groups fail at the same two moments: Day 1 of a carve-out, and the day the TSA expires. This is a working notebook on what actually holds up — architecture, governance, and the AI use cases worth funding — written from inside a multinational manufacturer rather than from a consulting deck.


The problem, as you actually experience it

You’ve closed. The data separation plan looked fine in the SPA. Eleven months later the seller’s ERP still runs your month-end close, three countries reconcile master data in spreadsheets, and the AI pilot the board asked about has no foundation to sit on.

None of this is a technology problem. It becomes one about six months too late.


Where this comes from

Built three times

Enterprise data architectures designed and delivered from scratch, three times, in multi-hundred-million-euro organisations.

Through the deals

Distributed data teams led across onshore and offshore delivery, through carve-outs and integrations rather than around them.

Both sides of the table

Fifteen years split between consulting delivery and running data on the client side, where the outcome actually lands.

Mid-deal, pre-deal, or watching a TSA clock?