Product wants velocity on new features. Engineering wants to reduce technical debt. Customer Success wants immediate fixes for top clients.
Everyone’s optimising their piece of the puzzle and the enterprise is breaking.
I see this pattern constantly. Each department builds the perfect solution for their world. Product gets their sprint velocity. Engineering carves out time for the refactoring they need. Customer Success gets an escalation path for their biggest accounts.
Six months later, nobody can execute cross-functionally. Product ships features that create support chaos. Engineering’s architectural decisions slow Product’s roadmap. Customer Success commitments override the capacity model everyone agreed to.
What went wrong? Everyone optimised locally. Nobody optimised the system.
Real operating model design means making deliberate trade-offs. It means Product might slow down feature velocity because Engineering needs infrastructure stability. It means Customer Success accepts that not every client request jumps the queue because the enterprise needs predictable delivery. It means Engineering tolerates some technical debt because speed to market matters more right now.
The goal isn’t to make every function happy. It’s to make the enterprise work.
This is hard. Function leaders are measured on their domain. They’re incentivised to optimise their piece. Asking them to accept “good enough” for their area so the whole can function better feels like losing.
But that’s exactly what systems thinking requires.
Three questions to ask:
🔹 Are we optimising for local efficiency or enterprise effectiveness?
🔹 Where are the handoffs breaking because each side optimised their end?
🔹 What would we design differently if we started from “what does the enterprise need to execute” rather than “what does each function want”?
The strongest operating models aren’t built by making every function perfect. They’re built by designing deliberately for how work actually flows across the seams.