Where the investment happens in pockets.
Three years running data, analytics and AI for the commercial and operations business of a global industrial technology manufacturer.
What is different here
Manufacturing rarely has a data problem in the way the phrase is usually meant. There is volume, there is history, and there are people who understand the process better than any model will. What there usually is not is a single owner, so investment happens in pockets, each one defensible on its own and none of them adding to a number anybody in finance recognises.
What usually needs fixing
Demand governance is the highest return work available and the least popular, because it means saying no in public. It removed thirty per cent of low value initiatives from a $17M portfolio.
Access databases and desktop workflows running commercial decisions, invisible to the platform strategy until the person who wrote them leaves.
Pricing, demand, inventory and service each answer to a different leader, and the questions worth asking sit exactly across those boundaries.
Where I have done it
3 of the seven case studies are in this sector.
The work this usually involves
Six services, and most engagements touch three of them. Which three depends on where the chain is breaking rather than on what you came in asking for.
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