A priority list with thirty items on it isn't a strategy — it's an admission that no one was willing to choose.
Ask a leadership team to name their top three priorities and you'll often get twelve. It feels safer that way — no one has to be the person who told a sponsor their initiative doesn't matter this quarter. But declining to choose doesn't remove the constraint on capacity; it just hides it, and it moves the cost from an uncomfortable conversation in a planning meeting to a much larger, quieter cost paid every week after, in the form of everything taking longer than it should.
The Arithmetic of Attention
In *Quality Software Management: Systems Thinking* (1992), Gerald Weinberg published a widely cited estimate of what happens to a person's effective output as the number of concurrent projects they're assigned to increases. On one project, someone contributes something close to 100% of their capacity. Split across two, Weinberg's estimate isn't 50/50 — it's roughly 40% to each, with about 20% lost outright to the overhead of switching between them. Add a third project and it drops further, to around 20% each. Weinberg was explicit that these were heuristic estimates rather than laboratory measurements, but they remain some of the most cited figures in the field precisely because nothing more rigorous has displaced them — and because they match what most delivery leaders observe when they actually track where time goes.
What Cognitive Psychology Actually Measured
Weinberg's estimate has independent support from experimental research. In a set of controlled experiments published in the *Journal of Experimental Psychology: Human Perception and Performance*, researchers Joshua Rubinstein, David Meyer, and Jeffrey Evans had participants alternate between tasks of varying complexity and measured the time cost of each switch. The switching cost wasn't trivial, and it grew with the complexity of the tasks involved. Summarizing this line of research, the American Psychological Association has noted that the mental blocks created by task-switching can cost as much as 40% of someone's productive time — a figure that lines up closely with Weinberg's independently derived estimate from a completely different field two decades earlier.
Exhibit 1
Priority A is in progress
Priority B interrupts to claim the same capacity
Mental context for A has to be reloaded later, from scratch
Attention residue from A drags down performance on B
Both A and B take longer than if either had run uninterrupted
Why parallel priorities create serial delay.
A list where everything is priority one is a list where nothing has actually been decided.
The Residue Effect
Organizational behavior researcher Sophie Leroy documented a related and specifically damaging effect in a 2009 study published in *Organizational Behavior and Human Decision Processes*. When people are interrupted before finishing one task and moved to an unrelated one, part of their attention stays stuck on the unfinished task — what Leroy termed "attention residue" — and measurably degrades their performance on the new task, especially when the interrupted work was time-pressured or incomplete. This is the mechanism behind a familiar organizational pattern: an initiative gets 70% built, gets deprioritized for something more urgent, and when it finally resurfaces, the team working on the "urgent" thing is quietly worse at it than if the first initiative had simply been finished or formally shelved instead of left hanging.
40%
of someone's productive time that cognitive-psychology research shows can be lost to task-switching alone
Source: Rubinstein, Meyer & Evans (2001), Journal of Experimental Psychology: Human Perception and Performance; American Psychological Association research summary.
Strategy Is a Subtraction Exercise
Michael Porter's 1996 *Harvard Business Review* article "What Is Strategy?" made the case that operational effectiveness — doing more things, doing them well — is not the same as strategy, and is not sufficient for competitive advantage because it's easy for competitors to copy. Real strategic positioning requires trade-offs: choosing what not to do is as important as choosing what to do. A prioritized portfolio works the same way. If your list of priorities doesn't exclude anything, it isn't a set of priorities — it's an inventory of hopes, and the organization will unconsciously ration capacity across all of them, in exactly the diluted, switching-cost-heavy way Weinberg and Rubinstein's research describes.
Why More Priorities Feels Like Progress
Part of why this keeps happening is that starting something new feels like momentum, while saying no to a sponsor feels like conflict. A kickoff meeting is visible and exciting; a deliberate "not now" is neither. So organizations default to accumulation — every credible initiative gets a slot on the roadmap, and capacity gets sliced thinner with each addition, without anyone ever making an explicit trade-off decision. The result is a portfolio that looks busy and feels responsive, while the switching costs described above quietly consume a large share of the very capacity everyone is fighting over.
What Actually Changes
Fixing this isn't about working harder or multitasking better — the research above suggests that's close to a contradiction in terms. It's about making the trade-off explicit instead of implicit: deciding, in the open, what capacity is protected for the top priority and what everything else has to wait for, instead of letting every initiative silently compete for the same finite attention.
