Authority calculator
Decision Latency
How long does a decision actually wait before the person who owns it makes it?
The average wait in calendar days, what the queue costs across a year, and the two levers that move it.
All readiness calculatorsThe math
Here is the equation, so you can argue with it.
W = L / λ
Divide the number of decisions waiting by the number closed each week. The result is how long a new decision waits, in weeks, before it is made.
- L
- Decisions waiting on this decider right now
- λ
- Decisions this decider closes in a week
- W
- The average wait a new decision faces
Where the numbers come from
- A count of decisions currently sitting with one decider, from a ticket queue, an inbox folder, or a standing agenda.
- How many of those that decider closes in a typical week, averaged over a month rather than taken from a good one.
- Optional. Roughly how long anybody spends actually working on one, from reading it to saying yes.
Your numbers
What this needs from you
Everything stays in this browser. Nothing is sent anywhere, nothing is stored, and reloading the page clears it.
Count them today. A standing agenda, an approvals queue, or the folder everyone forwards to.
Averaged over the last month. Use the ordinary weeks, not the week somebody cleared the backlog.
Reading, asking, and deciding. Leave at zero if you do not know, and the flow efficiency is left out.
The wait the business actually needs. Set it from a customer or a delivery commitment, not from ambition.
The answer
The average wait in calendar days, what the queue costs across a year, and the two levers that move it.
These calculate and they do not diagnose. Every field asks for a figure your organization already keeps, from a calendar, a queue, a ledger, or a ranking your team wrote down, and what comes back is arithmetic on what you entered. Nothing here asks you to rate a condition from one to five, nothing here produces a score, and no answer on these pages is a reading of your organization. Where you want a measurement rather than a calculation, the diagnostics do that and they publish what they cannot tell you as well. An answer here is exactly as good as the figure you put in, which is why every calculator names where its inputs come from before it asks for them.
Average wait before a decision is made
40 days
calendar days
- Decisions a year
- 312
- through this queue
- Decision-days waiting
- 12,376
- per year
- Flow efficiency
- 0.7%
- time somebody is deciding, against a forty hour week
- To hit the target
- 47.6 a week
- or a queue of 4
What the number says
With 34 decisions waiting and 6 closed a week, a decision that arrives today waits 40 days before it is made. Nobody has to have measured that. It follows from the two counts.
Across a year, roughly 312 decisions pass through this queue and spend about 12,376 decision-days waiting in it.
Somebody is actually working on the decision for 0.7% of that elapsed time, measured against a forty hour week. The rest is queue.
What to do about it
- To bring the wait to 5 days there are exactly two levers. Close 47.6 decisions a week instead of 6, or let only 4 decisions sit in the queue at a time. The first asks one person to work harder. The second asks the organization to decide what stops reaching them.
- At 0.7% flow efficiency, asking this decider to be faster optimizes the small part. Name one class of decision that leaves this queue permanently and give it to the level that already holds the information, which is the only move that shortens the wait without asking anybody to work more.
- A decision at the back of this queue waits over a month, so the information in it is over a month old by the time it is read. Check whether the decisions being made at the front are being made on facts that have already moved.
Before you act on this
What this can and cannot tell you
Read this before acting on anything above. It is here to make the result more useful, not to hedge it.
1 of 4
A reading is one vantage point, not the organization
Every score here comes from what people could observe and were willing to report, from where they sit. A senior view stops where the information stops reaching it, and a team view is bounded by what the team has been told. That is a real signal about the organization, and it is not the same thing as ground truth. Treat a result as a claim to check against records, calendars, and the people closest to the work, not as a finding that has already been checked.
2 of 4
A recommendation is a hypothesis, not an instruction
What this produces is the most defensible next question given the pattern in the answers. It has no access to your funding cycle, your contracts, your regulator, your technology estate, or the person who is about to resign, and any one of those can be the real constraint while the instrument points somewhere else. The recommendation is worth acting on when your own judgment, and the evidence you can gather, agree with it. It is worth arguing with when they do not, and the disagreement is more useful than the score.
3 of 4
Outcomes are decided in execution, by people and by systems
Reading a diagnostic changes nothing. What changes an organization is a specific person with authority making a specific decision, and then the follow-through surviving contact with the work: competing priorities, staffing, incentives, contracts, data quality, system limits, vendors, and everything else outside these questions. Two organizations with identical results can end a year in opposite places, and the difference is what they did and what happened to them, not what they scored.
4 of 4
Conditions move, so a result has a shelf life
These readings describe a moment. A reorganization, a departure, a new system, or a change in demand can move a condition faster than any plan built on the old reading. Measure again rather than assuming a result still holds, and treat a number that has not moved as a question about whether anything actually changed.
What this one cannot do
Every calculator fails differently, so each says how.
This is an average across one queue, so it says nothing about the decision in front of you, and a queue where urgent items jump the line has a much longer tail than the average suggests. It also assumes the queue is not growing without bound. Where arrivals exceed closures every week, the wait is not an average, it is a trend, and the figure here understates it. Counting the queue honestly is the hard part, because the decisions nobody logged are exactly the ones that have been waiting longest.
Reading path
The argument this equation came out of, in order.
A number changes a decision only when somebody already believes the thing it measures matters. These are the pieces that make that case, shortest first.
Step 1 of 4
Executive Decision VelocityHow fast decisions actually move, where they stall, and why velocity is an authority problem before it is a process one.
Step 2 of 4
The Decision Backlog AI CreatedAI generates options faster than any organization can decide on them. Where authority is unclear, more output does not accelerate the organization, it enlarges the queue in front of an unchanged bottleneck.
Step 3 of 4
The Quiet Authority ProblemThe most expensive authority failures are silent: decisions never made because no one believed they had the right to make them.
Step 4 of 4
The Knowledge-Authority GapKnowledge accumulates at the front. Authority accumulates at the top. The gap between them is where organizational performance goes to slow down.
Where the math comes from
- Little, J. D. C. (1961). A proof for the queuing formula: L = λW. Operations Research, 9(3), 383-387. doi:10.1287/opre.9.3.383
- Rogers, P., & Blenko, M. W. (2006). Who has the D? How clear decision roles enhance organizational performance. Harvard Business Review, 84(1), 52-61. hbr.org
- U.S. Department of the Army (2019). ADP 6-0: Mission command, command and control of Army forces. Headquarters, Department of the Army. armypubs.army.mil
Keep going
The other calculators, and the instruments that do measure.
Attention
Attention Concentration
We say we have eleven priorities. How many is the calendar actually running?
Alignment
Ranking Concordance
Everyone in the room said yes. Do they actually hold the same order of priorities?
Adaptability
Signal Response Lag
The world moved in March. When did the plan move?
Across the four
Time Saving Realization
The pilot saved two hours a week per person. What is that worth?
Where you want your organization measured rather than your own figures calculated, the diagnostics do that. See what each one answers, including what it cannot tell you.