I suppose the moment of truth came a few months ago during a business update presentation. I work for a huge business, which has interests in all sorts of different markets in different areas of the globe. The update could have taken hours to run through, but the information had been condensed down onto just two PowerPoint slides. Admittedly the slides were busy, but even so it was an impressive example of getting to the point. Vast sums of money and hours of activity boiled down to a few simple numbers which indicated how the performance of different areas compared both to the forecast and the previous period.
This set me thinking; what is the real value of my metrics? What do actually they mean to others?
I first started collecting data on my departmental activities to get a sense of the scale of the work being carried out. Being new into the job, I wanted to gain a better understanding of the volume of transactions, requests and complaints. The data has been very useful and has helped to inform and educate our customers as well as provide evidence that can be used to support our claims and refute misconceptions.
It's was all very useful stuff and I was generally quite happy with how my numbers were performing until one day I noticed that they had started to turn on me.
It all started out, as it so often does in this line of work, with a sunny morning and a tripped out air handling unit. A few days later it happened again.
For several months I'd been very pleased to report a gradual decrease in the volume of issues logged about the comfort cooling as my engineers and I had gradually learned more about how to best squeeze performance out of the systems. Suddenly, two unexpected events had thrown that out of the window.
On paper, August looked dreadful; an architectural monstrosity that blemished the otherwise tranquil skyline of my bar chart. I felt cheated. Yes it had happened, but it was a freak event, the data wasn't really reflective of the real story. It was then that I realised I needed a new metric.
 |
| This graph shows the number of issues logged over the course of the year to date |
That was the day I stopped focusing on the volume of issues logged and started focusing on the volume of satisfaction instead. It sounds like much the same thing, but it's not. Rather than reporting the number of people that said they were unhappy in a given month, I started looking at more positive metrics instead. One of my current favorite metrics, is the percentage of working days where no one logs a complaint. It doesn't matter too much if the chiller breaks down one day a month causing a spike of calls, the positive message is that for the other 19 days of the month, nobody called. You can choose to report that as 10 complaints or 95% compliance.
 |
| This graph shows the same set of data, but presented as the percentage of complaint free days |
Sometimes I like to combine the compliance metric with a qualifier, to improve it further. You could argue that because people vary in their perceptibility to heat and cold, that one swallow does not a summer make. You could choose to set a threshold level to make the metric work harder; if you ignore those instances when only a single person feels too cold, you could get a better picture of just how often the system really fails to perform.
Some people might see this as "spinning the facts", but as long as you present your data with integrity and are very clear about what your metrics really mean, they will generally be well received; especially if you are prepared to explain why you have chosen to measure in that way. After all, the real value in metrics for the customer, is in comparing how you are doing, with how you were doing and how you hoped to do.
One last thought about metrics, is that there is one that set of data you should always record. In FM, thank you's can be few and far between; make sure you record every single one so that you can look back on them with pride during difficult days.
No comments:
Post a Comment