Ellen has run product for her group for years, and she can name the week the job changed. It was not a reorganization and no one announced it. The gap between strategy and delivery simply became amplified, one conversation at a time. The build engine was faster than it had ever been, and every team lead, stakeholder, and steering group brought her the same four words. What do we do next?
The question arrived faster than she could answer it. Decisions that once waited invisibly in a long development queue now waited visibly on her calendar. Feeding that calendar was a wall of options: each one better polished, each one possible, each one assembled in greater efficiency with an AI agent collaborative process, complete with requirements and a business case. Ellen’s own role had changed. She used to spend her weeks eliciting ideas and shaping them. What the agents cannot do is commit the organization to one, or answer for it. The judgment to decide, the one thing that did not scale, had become her primary job.
The Fuzzy Front End Lost Its Buffer
Donald Reinertsen and Preston Smith named this territory more than three decades ago: the fuzzy front end, the stretch between a market signal and a committed decision to act, where initiatives wander before development begins. The fuzz always had a cost, but a buffer absorbed it. When building took quarters, the long queue behind every decision worked as that buffer. Intent had time to firm up while the engine ground through the backlog. The fuzz was never only a discipline problem. What to build is genuinely hard to know in advance, and the front end rarely had a rigorous process for making it clearer. It stayed that way because the constraint lived downstream. Fuzz was not the bigger problem, so it was tolerated rather than fixed.
A fast, inexpensive build engine removes the buffer. Fuzzy intent no longer waits; it passes straight through the engine and ships. There is no interval in which clarity catches up, so half-agreed intent becomes shipped clutter at machine speed. It spends the customer’s limited capacity for change on things nobody agreed were the problem.
Fuzz was tolerated while the constraint lived downstream. The buffer is gone.
The Scarcity Is Decision Capacity
So if ideas, build capacity, and information (telemetry, synthesized feedback, and adoption signals) are abundant, what is the scarcity now? It is decisions, the organization’s capacity to converge and agree, quickly and repeatedly, on the next problem worth solving for the customer. Clarity alone is not enough. One person can make a choice, but a choice becomes a decision only when the organization is bound to act on it. That is what deciding means at organizational scale. McKinsey’s research on organizational decision making suggests how strained that capacity already is. Managers at a typical large company spend 37 percent of their time on decisions, and say most of that time is used ineffectively. Only one in five reports an organization that excels at deciding.
37 percent of managers’ time goes to making decisions. The majority of it, by their own account, is used ineffectively.
A faster engine does not need a better decider. It needs an organization that can decide well many times over, in parallel, without routing every choice through one calendar. That makes decisioning a core governance capability, one the operating model has to hold deliberately, with people accountable for it and measures that show whether it is keeping pace.
Part of building that capability is shrinking what has to be agreed. In place of a long-range roadmap, one testable intent comes forward at a time: the problem to solve, a value hypothesis, and a confirmation plan describing how the team will know it was right within weeks. Options stop being arguments and become candidates for evidence. Decisions get faster because the thing being agreed on gets smaller.
Agreement also has a clock, and almost no one reads it. The engineering side of the house already measures its half of the loop; in “Are You Building the Right Thing,” Adam Whaley clocks time to feedback, the interval from starting a piece of work until a real user responds to it. The upstream mirror is simpler than it sounds. Measure the elapsed time from an idea arriving to its entry in a product backlog as committed work. Call it upstream lead time. Nearly none of that interval is production; it is deciding and aligning, which is what makes it the most honest proxy available for decision capacity. Deciding will need its own family of measures, the way delivery eventually got its own; this one is the place to start, because it is the one every organization can already compute.
One guard keeps the measure honest. Entry into the backlog has to mean committed intent, not a parked idea. Otherwise the number improves while nothing has actually been decided. Ellen stopped asking her teams how much was in flight and started asking how long each intent had been waiting to become one. The items waiting longest are not the hardest problems. They are often the ones nobody is empowered to decide.
Redesign the Clocks, Not the Gates
The instinctive fixes fail in opposite directions. More gates make agreement slower, rebuilding the heavyweight front end that was survivable only when the build was slower still. No governance makes agreement meaningless, because nothing binds the organization to act. The redesign is about placement and cadence, who holds which decisions and how often each decision renews.
Placement
A decision belongs at the boundary where its information lives, and risk is what sorts it there. Two properties settle it: reversibility, and the cost of being wrong. Low-risk intents, inexpensive to reverse and contained if mistaken, belong in the queue directly. Agents rank them, the team picks, and the confirmation plan catches the errors. Higher-risk intents need a named owner inside an explicit allocation envelope, because someone has to commit the organization and answer for the outcome. Some decisions genuinely cross boundaries: moving money or people between products, retiring a bet, changing direction. Those travel upward. Where the right value measurement does not yet exist, compensating controls hold the line until it does. Coordinated decisions are the ones that queue; the design goal is to grade honestly, delegate everything the grade allows, and need as few of the traveling kind as possible. Ellen graded every option on those two properties before asking who decides, and kept the high-risk calls herself.
Cadence
Three tiers set the rhythm. Strategy moves slowly, and should; direction is expensive to whipsaw. Portfolio allocation renews quarterly or on evidence triggers, adjusting envelopes rather than re-litigating every line. Product intent renews at the speed of the learning loop. One rule disciplines all three. Governance has to renew faster than the assumptions it governs expire. When assumptions held for years, calendar planning worked. Telemetry now retires assumptions in weeks.
Governance design is placement and cadence, who decides and how often. Get either wrong and governance becomes the bottleneck
The three tiers are connected, and that is the warning. A system moves at the pace of its slowest clock. Anything left on a slower rhythm will set the pace for everything else. Pace also depends on the size of the work.
How the enterprise moves money, and how strategy above the portfolio keeps up, is a larger redesign that deserves its own treatment. However fast the front end learns to decide, everything connected to it has to be able to follow.
What Ellen Learned
By the second quarter, Ellen’s review looked different. Intents came forward monthly, in units small enough to decide and confirm. Of the last eleven ideas, five were stopped before the build, when the evidence said no and stopping was still cheap. Alex, her group’s delivery leader, asked what she would tell a peer walking into the same storm. Three lessons she held:
- Measure the front end as a queue. Upstream lead time is as measurable as the delivery lead time beside it, and until it is measured, the most expensive queue in the system keeps hiding in plain sight.
- Test governance against the pace of evidence. Check where each decision sits and how often it renews. If evidence arrives in weeks and permission arrives in quarters, the teams are not the problem; the operating model is.
- Sequence the redesign honestly. Start where the operating model can move now: placement and cadence. Then name what still sets the pace for everything connected to it.
The question that used to fill her calendar still arrives every week. What changed is that the organization can now answer it, at the speed the question deserves.
This post comes from our management consulting practice, which specializes in designing and implementing operating models that align governance, processes, and technology to drive measurable business outcomes.
Sources
Donald G. Reinertsen and Preston G. Smith, Developing Products in Half the Time, Van Nostrand Reinhold, 1991. Popularized the term “the fuzzy front end.”
McKinsey & Company, “Decision making in the age of urgency,” April 2019.
Adam Whaley, “Are You Building the Right Thing: The Metrics That Measure How Fast You Learn,” July 2026. Source of the delivery learning-loop metrics referenced.
Eliyahu M. Goldratt and Jeff Cox, The Goal: A Process of Ongoing Improvement, North River Press, 1984. Character homage, names only, in tribute.
Alien, directed by Ridley Scott, 20th Century Fox, 1979. Character homage, name only, in tribute.
