There is a team capacity problem in almost every business I work with. It is not a strategy problem or a systems problem. The people are there, the hours are being paid for, and nobody has measured whether those hours translate into proportionate output. That gap is quiet and expensive.

I was on day 2061 of my consecutive barefoot-style running streak this morning, covering another ten kilometres toward my goal of 40,075km. Distance covered to date: 15,935.93km, with 24,139.07km still ahead. I crossed paths with a couple of dogs along the route who had more conviction about their territorial claims than I was prepared to argue with, and I found myself thinking about something I encounter across almost every team I consult with: the invisible underperformance problem.

Team capacity planning sounds more technical than it is. The underlying principle is straightforward. Know how many hours a team member works. Know how much of those hours are accounted for by their assigned tasks. If the two figures are misaligned, you have either a problem or an opportunity, depending on which direction the gap runs.

Starting point: log the hours. When someone joins your team, record their contracted hours per week. A full-time employee works a standard 40-hour week. Log which days they work. If they are part-time or on a non-standard arrangement, capture that too. This is not about building a surveillance structure. It is about having accurate baseline data before making decisions with it.

The second step is task estimation. Every task in your task management system needs an estimated time field. It does not need to be precise to the minute. Working in intervals is sufficient: 15 minutes, 30 minutes, one hour, two hours, four hours, eight hours, two days, one week. Build a drop-down for those options and assign each one a value in minutes. Then the arithmetic runs itself.

The part most setups miss is recurring tasks. A daily task set to appear only when the previous one is completed will not show in a standard 30-day workload view. These tasks need to be accounted for separately. If a task recurs daily, it runs roughly five times a week. Multiply the time per occurrence by five to get the weekly figure, then multiply by 4.33 to reach the monthly equivalent. Weekly tasks get multiplied by 4.33. Quarterly tasks get divided by three to give the monthly figure. Six-monthly by six. Annual by twelve. Once this logic is embedded in your system, it runs without manual intervention.

Now you have two figures: total available hours for a given team member over the next 30 days, and total estimated hours of assigned work over the same period. Divide the second by the first, multiply by 100, and you have a capacity percentage.

The range I have settled on, having worked across multiple teams and businesses, is 75 to 85 per cent as the target.

Above 85 per cent means too much work is assigned. Quality will drop, errors will come in, and the team member will either start burning out or start cutting corners, often without raising either to management. The margin between 85 and 100 per cent disappears fast when you factor in meetings, admin, unexpected queries, and the natural inefficiency built into any working day.

Below 75 per cent means the team member is underutilised. Hours are being paid for and not being productively used. Over a month, the financial impact adds up. Over a year, it is a significant overhead without corresponding return.

When businesses run this exercise for the first time, the results are often not what they expected. In my experience, one or two people sit well above capacity, carrying more than their share of the load. Everyone else tends to be below it, some significantly. The imbalance creates two problems: the overloaded team members are prone to mistakes, and the underutilised ones either do not know they have space to take on more, or know it and say nothing.

The discipline of tracking capacity turns a vague, recurring problem into a solvable one. The output tells you when you need to recruit, whether your headcount matches your actual workload, and when redistribution is the smarter answer. Decisions made with this data behind them are consistently better decisions.

Worth saying clearly: this approach is not about pressuring a team to run at maximum. A team working at 80 per cent with appropriate challenge, clear direction, and genuine support will outperform a team running at 95 per cent every time. The goal is the right level of utilisation, not the highest possible one.

I think about this kind of discipline a lot on my runs. The streak I am on, 2,061 consecutive days of barefoot-style distance in Vibram FiveFingers, is built on the same principle: precise measurement of where I am, honest tracking of what remains, and no assumptions about progress. I know I have covered 15,935.93km. I know 24,139.07km remains to complete the full 40,075km goal. That number does not improve by hoping it will.

The same applies to a team. You get better output by measuring what is happening, not by assuming it is fine.

This run is part of a fundraising mission to raise £1M for children's causes, including Great Ormond Street Hospital and BBC Children in Need. Every day the streak continues and every person who follows the journey is another step toward a goal built on consistency, not occasional effort.

If you lead a team and have not looked at capacity in this way, the setup takes less than a day. Log the contracted hours, add time estimates to your tasks, account for recurring work, and run the calculation. What comes back tends to reframe how you manage people, and how you think about your cost base, permanently.

Watch the full episode: https://youtu.be/Sn7b3OwxlBo