A common standard

Suppose there was no such thing as money and you needed to go shopping. Imagine how difficult and onerous it would be to try and have to establish exchange values for the things you had to trade and the things you wanted to buy. Money makes the whole thing so much easier. What money is, is a common standard of value.

Something similar to the bartering example occurs in businesses. Each type of work that a person is doing may be measureable, but if you have people doing different kinds of work, or different people doing different mixes of different kinds of work, it can be difficult to determine how productive everyone is.

The solution may be to create a common standard.

In one business I have been working with, staff performed a range of seven different kinds of work. The organisation knew how much time each person was at work (after deducting sick and other kinds of leave) and they knew how much of each type of work different people were doing, but they were stuck as to how to measure productivity.

They had six months worth of data for each person, so a multiple linear regression was done to determine how much time each type of work was taking. As a model it turned out quite well with an r-squared value of 0.91, indicating a strong correlation between time spent at work and amount of work completed (which is what you would hope!) The co-efficients from the linear model were used to weight each type of work in terms of a 'standard work item' which for ease of calculation was defined as taking 10 minutes. If the model said that a particular kind of work generally took 22 minutes then it was given a weight of 2.2 standard work items.

What this meant was that for the first time it was possible to define everyone's performance in terms of a common standard, by weighting the work they actually completed to give a total number of standard work items. Since the time each person was at work was also known, for each person a measure could be calculated ( minutes per standard work item) and compared to the same measure for the unit as a whole.

The results were enlightening to say the least! Some staff had productivity as low as 60% of the average while others had up to 170% productivity, with most staff fitting within the 80%-120% range. Of course, quantity without quality would be worse than useless, but using a separate measure of quality showed that the most productive staff also performed quality work.

Supervisors in this business had previously suspected that some of their staff were unproductive, but they had previously had no objective measure to enable them to quantify this. But now they could tell exactly how productive each member of their team was, both in absolute terms and compared to the other sixty staff in the business. Since the same data sources were used for all staff for time worked and amount of work completed and the work was weighted in the same way for everyone, there was also no scope for anyone to argue that they were being singled out or treated unfairly.

By creating a common objective measure, it was now possible to start having discussions with less productive staff to determine whether there were training or behavioral issues that needed to be addressed. However it was also now possible to start looking at the high performers to see how they achieved their results and whether there was anything which could be learned that might be transferable to other less productive staff.. As a result they had increased scope for improving the collective productivity of the business as a whole.

One side effect was that now that staff were getting regular feedback on their relative productivity, there was both the information and the motivation for everyone to try and improve their performance.