The Christmas and New Year is always a good time to take some time off the hurly burly of daily grind and reflect on how things are going. Towards the end of the year I did some work on what metrics would help us run our PMO more efficiently. Metrics are always difficult to establish, especially as they only tell a story once you have a baseline to measure against. This is probably a heavy topic for the first post of the year. Apologies for that.
While I see a pressing need for making decisions on evidence, I am also cautious against spurious interpretations of metrics, which can easily happen if taken out of context. You only have to look at statistics driven sports such as baseball or cricket where fans and officials will take diametrically opposing views of players or tactics using different statistics. Numbers are just that. What you interpret from them is what gives them meaning.
The first task was to explore what type of metrics would be useful for our business. I work for a IT professional services firm. It has unique challenges from other types of businesses. I did some research on what other similar organisations are doing. I found this compilation from OpenAir and excellent resource. There are three articles in this and the first one by Thomas Loh is by far the best. This was an excellent start. The key is not to go chasing every metric under the sun, but the ones that you need to measure. That is even more crucial when your PMO is lean and you are in the process of building its maturity. Capturing metrics and analysing them takes effort and time. You cannot afford to be spending either frivolously.
The standard metrics of utilisation, profitability, billing rate etc are quite easy to measure after the effect. We were looking at getting at least one forward looking metric that can help validate our decision making. We decided to invest in our effort in an area that is most challenging for a services business like ours – that is the pull between resource and demand.
In services business you either have too much work or too many people. It is crucial to have a good handle of this to maximise profitability. The cycle of winning new business always takes time. If you have left your efforts to bring in new work too late, you will inevitably have periods of low revenue. Unlike products which you can sell at a later time and recoup some revenue, if not all, lost consulting time cannot be archived and sold. That is effectively lost.
To ensure an optimum work pipeline, we can use the charge rate to either stick to our margins, because work is plentiful or use discounting effectively to be more competitive than usual in tough market times. We want to be making a decision on them at the correct times (i.e., not stick to higher margins when market is tough or give away margins when not necessary). We are looking at using Backlog (total value of contracts yet to be executed) as a forward measurement for that.
The aim is to look at recording the backlog value three months out and updating the actuals at the end of the month. As we currently do not have a baseline, I do not expect us to be able to use this effectively in the next year. However, once we have built a picture, we should be able to predict with some confidence what it means to be at a certain point in our backlog and what that is likely to mean in terms of likely actual income.
Because we are looking at it three months out, we’re likely to have enough time to win new business to fill up the pipeline if it is looking less than promising. If pipeline is strong, we know we do not need to compromise on margins. There is likely a follow up on this topic this time next year on how this measurement plays out. Hopefully my challenge is not unique to me and the process is helpful for others to reflect on.
I am keen to understand what predictive measurements you have successfully implemented.
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