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Part 2: Understand Your Capacity

This is the second part of the ‘Do the most valuable thing, unless you can’t’ article. In this part we look at capacity as a constraint and discuss how we might model our available and effective capacity to help in the sequencing of work.

‘Capacity’ is defined as a quantitative constraint and is often defined in terms of the number of available people with particular skills or the availability of systems, information and other resources required to do the work. But it’s not as simple as that.

The capacity of a machine that makes widgets (or sausages) can be calculated simply by the number of widgets (or sausages) it can make in a specified period of time. In contrast, a team’s capacity, in particular their capacity to do really useful work, is a little more complicated than that.

People, unlike machines, don’t work at uniform rates. This is especially true when we are doing ‘thinking-work’. We often need time to prepare work. We need breaks. We can’t be efficient for 100% of the time. And our different levels of competency and experience naturally means the same piece of work will take different amounts of time depending on the person doing the work.

To take on a more realistic quantity of work through sequencing, we need to have a better understanding of what we can do in the time we have available. Most people are (too) optimistic and take on way more work than they can actually do. This leads to pieces of work being started but not finished (and little or no value delivered), too much work-in-progress (or WIP), or commitments being made to complete work that have no chance of being met.
 

Understanding your (real) capacity

Ideally teams can represent their own capacity in a meaningful way and can best state how much of that capacity a piece of work might take. An important technique to help understand effective (real) capacity is to break it down into chunks, based on the different types of work being done, using the following three steps:

  1. Calculate our Total Capacity by multiplying the number of working hours in a day by the number of days in a working period or iteration, say, two or four weeks. This is a very simple calculation, purely theoretical though because we know that we can’t possibly work all the working hours in a day. There is time where we are simply not available to do work and we need to allow for that.
  2. Subtract unavailable time like non-working days, annual and long service leave, mandatory training and other time away to leave our Available Capacity. Already we are starting to create a more realistic view of the time we have available within which to fit our work.
  3. Subtract incidental work (work that doesn’t create direct value but may be necessary to support value-creating work; this can include business-as-usual work) and non-value work (pure waste that adds no value at all) from our Available Capacity to give our Effective Capacity.


Capacity model

Simply doing this exercise (and we recommend it be done with pen and paper first to get a quick, rough view of capacity) can identify huge chunks of time and effort being spent on non-value creating work which we can critically analyze for elimination or minimization. The remaining capacity, our effective capacity, is our capacity to do valuable work and it is into that capacity that we fit our prioritized work.
 

Balancing between cyclic and discretionary work

We often come across the challenge of striking a balance between ‘known’ or ‘cyclic’ work (things that we have to do) and discretionary work (where we need to employ prioritization). If we subtract the time to do known or cyclic work from effective capacity, we get our Responsive Capacity. But how should we treat it? Known or cyclic work should be scheduled and, in ideal situations, rescheduled to smooth the flow. Discretionary work is sequenced around that known work in such a way as to maximize value while maintaining an awareness of the capacity requirements.

However, this doesn’t mean that known or cyclic work is simply accepted as business-as-usual. This kind of work should be scrutinized for the value it creates and, where possible, eliminated, automated, optimized or delegated to increase our responsive capacity to do more valuable work.


Model your capacity process

Making room for contingency

A common error when looking at capacity is to aim for maximum allocation as a proxy for efficiency. Traffic controllers know that as expressways fill up with cars, lowering the speed-limit actually enables greater throughput. Likewise, reserving a Contingency Reserve of between 15% and 20% of Available Capacity, where that capacity is left unallocated, provides the space needed to maximize the flow of work and value delivered as counter-intuitive as this may appear to some!

The Contingency Reserve doesn’t mean that we will work 15% to 20% less than before. It just means that we don’t allocate 100% of our available capacity to upcoming work. We use the Contingency Reserve to accommodate overruns (where some work takes a bit longer than anticipated), genuinely urgent work (where something needs to jump to the front of the queue), and unexpected events as well as to continuously improve the ways we work.

One more thing, this exercise is not just for “your people and their teams to do”. It’s a practical exercise for everyone, from senior executives and managers down. Everyone can benefit from having a better understanding of how much they can do. The information and insights you gain makes for meaningful, data-led conversations, across all levels of the organization, about how you reduce waste and maximize the time you have to deliver value.

In the third and final part of this article we look at the process of sequencing prioritized work within capacity constraints and discuss the challenges facing many organizations today.

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