Private equity deal teams follow a precise, unspoken scorecard when evaluating manufacturing acquisitions — and most owner-operators never see it coming. This episode breaks down exactly what investors are scoring, from strategic positioning to cash conversion ratios.
When private equity comes knocking on a manufacturing company's door, the evaluation has often already begun long before the site visit. This episode of Development pulls back the curtain on the criteria deal teams actually use — the strategic filters, financial thresholds, and operational tells that separate a compelling acquisition target from a pass. Drawing on this in-depth look at PE acquisition criteria for manufacturers, the episode gives owner-operators a clear-eyed view of what the investment committee scorecard really looks like.
Here's what the episode covers:
The episode also addresses supply chain diligence — country-of-origin concentrations, dual-sourcing plans, and vendor scorecards — as a now-standard part of competitive auctions. The full source article, frameworks, and threshold data are at Manufacturing.co. For more on how AI decision-making intersects with operational strategy, check out the Development episode The Handoff Trap: Designing AI Agents That Know When to Stop.
Software and web development from the side that has to ship it and then live with it. Architecture decisions with a cost attached, scoping, technical debt, hiring and vendor selection, and the AI tooling question every engineering team is now answering whether they planned to or not.
Each episode takes one decision — rewrite or refactor, framework choice, build versus buy, how to scope a fixed-bid project honestly — and works through the tradeoffs, including the ones that only show up in year two. Written for engineering leads, technical founders and the people who fund them. Five or six minutes, no hand-waving.
Topics include rewrite versus refactor, build versus buy, scoping fixed-bid work honestly, technical debt you should keep, framework and platform choices, hiring and vendor selection, code review culture, and where AI tooling actually helps.
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