Navigating the Pitfalls of Productivity Measurement
Measuring the productivity of employees is undeniably important in allowing managers to actively manage, diagnose problems, and incentivize improvement. However, measuring individual productivity is not always as simple as output volume/labor hours.
It is not uncommon to find businesses overstating individual productivity by including non-productive tasks in their output measurement. Activities such as rework, unnecessary meetings and any activity not bringing value to the business should not be included in the productivity measurement. By measuring unproductive tasks, the measurement is overstated and fails to incentivize employee’s productive activities.
Another common obstacle in measuring the productivity of employees can be comparing individuals on a level playing field. Difficulties arise when comparing employees with varying task complexity and varying task cycle times.
Let’s look at an example: We have Employee A completing Form A which typically takes 1 hour and is more complex. We have Employee B who processes Form B, takes 20 minutes and is less complex. If Employee A completes 2 forms per hour and Employee B also produces 2 forms per hour, both employees appear to have the same productivity when looking at forms per hour. We know Employee A has outperformed Employee B but this is not clear because the measurement does not capture the varying complexity and cycle time of each form.
One solution to this problem can be moving to an Earned Hours model. This requires the organization to define and measure the “Standard Time” or “Average Task Time” for each work item. To calculate Earned Hours, multiply the Output Volume by the Average Task Time. In our example, Employee A would have 2 Earned Hours while Employee B would have 0.6 earned hours. If we go further and divide Earned Hours by Total Hours worked we get an Earned Value % and a much more comparable productivity measurement. Employee A would have an Earned Value % of 200% and Employee B an Earned Value % of 60%.
This blog was written by Mark Beairsto, Consultant at Trindent Consulting. He has experience improving the efficiency and effectiveness of organizations in the healthcare, energy, and financial services industries.