In the last post we talked about the utilization rate you should aim for.  We now want to take a look at how this will affect your head count strategy, and some challenges with it. But first let’s look at some graphs.

Suppose that our consulting business is getting new projects at some rate L per month. And it takes on average M months to complete the work. And finally, let c be the number of consultants available to work on a project, one consultant per project. We also assume that we have very accommodating customers in that they are willing to wait forever if necessary to have their projects worked on by your organization. Great work to have such amazing customer loyalty! In this case, your utilization will equal

Utilization = r/c

where r = L/U. To increase L we need to increase our business development efforts. But U is a function of how fast we execute on the project. Assuming that is relative fixed in the short run, then the only lever we have to control utilization is our head count. But the trouble is the average number of projects queued up is

r/(1-r) + C(c, r)

where C(c, r) is some nasty formula that I will not inflict on you. The key here as r increases, so does the backlog. But we can plot it. On the graph below, I plot the utilization rate as I change the number of consultants between 1 and 10, and on the vertical axis the number of projects waiting to be worked on. I have four lines for different r = L/U values. As you can see, as the win rate approaches the service rate, the number of projects waiting in the wings increases dramatically! This is not good for your reputation. For this reason, we would advise moving the utilization target much above 80%. 

We want to maintain a head count that keeps the number of waiting projects low, but keeps our team busy most of the time. 

If you would like to discuss how to model your organization and optimize your organization’s size based on your type of projects, contact us on the contact page for a free, no obligation discussion.