Results monitoring serves as a tracking mechanism to reflect performance. Superb results imply that work is being carried out in excellence. Poor results indicate that there are hiccups somewhere along the way. A savvy manager would learn about the excellent execution and seek to replicate success. At the same time, he would investigate causes of the hiccups and make improvements. This is assuming that the measurements are monitoring the right results. On the contrary, measuring inappropriate results would lead the manager to spend disproportionate effort on irrelevant work.
There are three signals you need to watch for.
Tasks are done with little results to show
When the focus is on monitoring the progress of work, completion is top-of-mind. Your team would get busy and attempt to complete the work as quickly as possible. That is good only when the right work is done.
Consider the design of a web form. There are different options. The simplest approach is to lay out the data fields and arrange them in a logical sequence. A more comprehensive approach is to incorporate a link to a related database so that archived data are extracted and auto-populate the web form. This minimizes the effort for manual data input. The simple solution is quick to build but the comprehensive solution is a productivity booster.
Results don’t spell success
The reported results don’t get people excited. You report on a measure for years. Every year, a target is set. There is a formal routine to collect the data and compile the result. The indifferent attitude signals irrelevance or complacency.
For an IT support group, systems outage is a common measure. The goal of keeping all the systems up 99.5% of the time has been met and exceeded consistently. The team doesn’t see any stumbling block that would deter them from achieving that goal. It feels that operating in status quo is adequate. There is no need to change how it operates. A tired measure, though useful, might not be motivating to your employees.
Complexity kills purpose
A good translation of any language requires sophistication in using the language just like mother-tongue. Otherwise, the meaning could be less impactful. Similarly, a complex measure makes it difficult to understand the implications of the results.
The employee engagement score is a composite number built on many attributes that constitute engagement. The respective weight assigned to each attribute vary. When the engagement score drops 1%, you need to dive into the source data to uncover what effected that change. Some companies might group similar attributes into an intermediate score. When you are challenged to explain the meaning of a score, it is better to break the measure down and use additional measures. When people don’t understand the result, they ignore it.
Results monitoring should help, not stifle performance. In determining whether the measures that you have in place are effective, look for the above signals in your communication of the results.