The Operating Model You’ve Been Looking For
The most effective leaders are already running a different system. They just don’t have a name for it yet.
At some point in the last few years, most Fortune 500 executives have had a version of the same conversation.
It usually happens informally. A business leader pulls a technology VP aside after a steering committee. A CDO grabs coffee with a CFO who just sat through another quarterly update. And one of them says something like: “Why does it feel like we keep building the right things at the wrong time?”
It’s not a question about talent. The talent is there. It’s not about investment — the investment is real. It’s not even about strategy. Everyone agrees on the direction.
It’s a question about something harder to name. A friction that planning cycles, governance reviews, and transformation programs haven’t been able to touch. The kind of friction that makes a perfectly sound strategy produce perfectly mediocre results.
If you’ve been in that conversation, you already know what I’m describing. You’ve felt it. You’ve just been missing the language for it.
That’s what this piece is about.
You’ve Already Seen the Answer
Before I name the problem, I want to start somewhere different — with something you’ve already witnessed.
At some point in your career, a team inside your organization moved differently than everything around it. It probably didn’t announce itself as a transformation initiative. It just produced results that didn’t match the timeline anyone expected. A twelve-month initiative collapsed into three. A product reached market impact in the timeframe the business case projected for year two. A problem that had been stuck in planning for six months got solved in a sprint.
Most experienced executives can name at least one moment like that. And when you look back at how those teams actually operated, certain things were true.
Business leadership was close to the work — not reviewing it periodically, but actually in the room, in the trenches, talking strategy WITH delivery. Someone on the business side could see progress weekly and change direction without triggering a governance review. The technology team wasn’t asking “what do you need built?” They were asking “what problem are you trying to solve?” Prototypes reached real users within weeks, not months. The signal from those users shaped the next iteration directly, rather than being filtered through a change request process.
And perhaps most distinctively: nobody was entirely sure whose job it was. When something didn’t work, the whole team owned fixing it.
You’ve seen this. You probably chalked it up to a lucky combination of people. An unusually collaborative team. The right personalities in the same room at the right time. Often times, I have seen this level of operational success written off as something that is not sustainable.
It wasn’t luck. It was a different operating model, running informally inside the formal one.
That’s the recognition I want you to hold onto as you read the rest of this.
Why the Current Model Creates the Friction
The operating model that dominates most Fortune 500 organizations today was built on a sensible assumption: business strategy and technical execution are different enough that they need different people, different timelines, and different governance. Business sets direction. Technology executes. Governance ensures the handoff is clean.
For most of the last thirty years, that held. Technology execution was slow and predictable enough that strategy could afford to lock in before execution began. The gap between planning and delivery — eighteen months, twenty-four months — was roughly the same for everyone. The friction was real, but it was symmetric. Every competitor paid the same tax.
That symmetry is gone.
Technology teams with modern AI tools can now prototype a strategic hypothesis in two weeks that would have taken six months five years ago. They can test market assumptions with real customers before a business case is written. They can validate feasibility at the speed of a conversation rather than an architecture review cycle.
The execution half of the equation has fundamentally changed. The organizational model hasn’t caught up.
So strategy still hardens on the old timeline — locked in by budgets, headcount, vendor contracts, and governance calendars — while the technology team’s actual capability has blown past what the model was designed to manage. The friction you feel isn’t a people problem or an alignment problem. It’s a timing problem baked into the model’s architecture.
What the New Model Actually Looks Like
Here’s where I want to be concrete, because “move faster” and “collaborate better” aren’t mechanisms — they’re aspirations.
The teams that move differently have made three specific structural shifts, and once you see them you’ll recognize them immediately in the moments I described earlier.
The first is that strategy and execution happen simultaneously rather than sequentially. In the traditional model, strategy is upstream — it gets converted into requirements, handed to technology, and built to spec. The handoff is where things harden. In the new model, business leadership holds the strategic context continuously throughout execution: the market opportunity, the competitive threat, the outcome they’re actually trying to achieve. Technology builds toward that context in real time, feeding discoveries back to business strategy as they go. Strategy doesn’t get handed off and locked. It stays alive, shaped by what’s actually learned in the field.
The second shift is from requirements documents to continuous context. Requirements documents exist to carry intent from one world to another when those worlds don’t share a working environment. The problem is that documents are static and intent is dynamic. By the time the document reaches execution, the business has moved. The new model doesn’t try to build better documents — it eliminates the communication gap that made documents necessary in the first place. Business leaders stay close enough to the work that their guidance is ongoing. Technology brings back working software, real customer responses, measurable outcomes — things a business leader can actually react to — rather than status updates against a plan that was written six months ago.
The third shift is the hardest one to make, and the one most executives feel most viscerally when it works. Stage-gate governance was designed for a world where the primary risk is building the wrong thing. It makes sense: put checkpoints in place to validate alignment before you spend more money. But in a world where the bigger risk is learning too late that you’re building the wrong thing, stage-gates don’t protect you — they slow down the learning that would protect you. The organizations that operate differently haven’t abandoned governance. They’ve replaced periodic checkpoints with continuous visibility. Leadership sees real progress weekly — working software, live metrics — which means they have enough current context to trust teams with real autonomy. Governance becomes about whether the team is learning fast enough, not just whether they’re on schedule.
The Phrase That Changes the Conversation
There’s a single sentence I’ve used with leadership teams that consistently lands differently than anything else I’ve offered them.
In the AI era, strategy and execution are no longer separate phases. They’re the same activity happening at different altitudes.
What I’ve watched happen when that sentence lands — and I’ve watched it happen in enough rooms now to trust the pattern — isn’t that people learn something new. It’s that they finally have language for something they already knew. Something they’d observed in the teams that moved differently. Something they felt but couldn’t articulate clearly enough to act on deliberately.
Once you can name it, you can see it everywhere. Which parts of your organization are already running this model, even informally. What made the difference in the projects that moved. What would need to change structurally — not culturally, not individually, but structurally — to replicate those conditions intentionally.
The operating model isn’t something someone hands you. You’ve already seen it working. This is just the language to build it on purpose.
Next in this series: “The Talent You’ve Already Built” — Why the technology teams inside your organization have evolved into strategic partners you’re still managing like execution arms, and what that costs you every quarter you don’t adapt.
Matt Keane is a Chief Data and AI Officer, Professor of Data Science and Analytics, and AI researcher with 20+ years of Fortune 500 transformation experience. His upcoming book, The Last Paradigm: Leadership at the Speed of AI, explores how organizations can eliminate the alignment tax and build competitive advantage in the AI era.
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