As many organizations begin their next performance cycle, I thought it would be good to show what makes for an effective process that managers, supervisors, and employees can actually look forward to.
3rd in a series
A senior-level manager showed me an interesting piece of information a while back. It was the compilation of the performance evaluations for a particular department. What initially caught my eye was that all of the individuals in the department had been rated as “above expectations.” I commented on the absence of the expected “bell-curve” distribution, which was the obvious conclusion, but then the manager pointed out that the department, as a whole, missed expectations by about 10%. He then asked the big question: “How can everyone be ‘above expectations’ when the group missed its year-end target?”
The answer is two-fold.
First, the supervising manager rated the individual employees on intent/energy spent, not the actual numbers. Out of fear of demoralizing the employees, the supervising manager ignored the reality of performance and basically gave them an “A” for effort. This is the business equivalent of giving everybody a trophy just for participating!
The root cause of this problem is a basic misunderstanding of the intention behind the performance management process. The performance management process is an accepted tool that is used to measure how well an individual (and group) is meeting the expectations of the department/organization. We talked earlier about the alignment of expectations – that the individual’s performance needs to be connected and seen as a part of the whole department’s performance – and on up the ladder. So expectations are established at the higher level and translated down to the department and distributed to the individuals in the group. If a supervising manager does not handle this distribution properly, you get into trouble later when it comes to evaluating performance.
Let’s use a manufacturing example…
Dept X, made up of 4 employees, needs to produce 100 widgets per day. Simple math would tell you that each employee would be required to produce 25 per day. The evaluation would be rather easy. If an employee produces 25 widgets per day, they would “meet expectations.” Produce 24 or less, they would be “below expectations.” Produce 26 or greater – “above expectations.”
But in the real world, people have different performance capacities. Let’s say that Employee A is considered a “high performer” – capable of producing far more than 25 widgets a day. Employees B and C are average performers – 25 widgets a day are just about right for them. Employee D is new to the job and is currently training into the position. To ask this employee for 25 would be considered a “stretch goal” for the time being. Eventually (s)he will get there, but not right now.
Here is how the distribution would look:
In this illustration, the lower number for employees A, B, and C would be the minimum expected (25) for a “meets expectation” rating. For employee D, a lower expectation of 18 is only during training and would be raised periodically throughout the performance cycle. It’s the high number on the range that is important here. This is the threshold that establishes where the “exceeds expectations” rating starts. Employee A’s threshold is higher because (s)he is a known high performer – more can be expected of them. Employee D’s high point on the range is currently equivalent to the average “meets expectations,” but only for this performance cycle. In the next cycle, his/her range will probably be equal to B’s and C’s. In this way, the supervising manager keeps the department numbers at the forefront, knowing how each individual will contribute to the whole expectation. As employee D’s performance some up to standard (25-27 per day), Employee A’s numbers can be called down to equal the rest of the group. However, this might cause employee A to be less challenged. So the supervising manager might add a new goal in a different area (i.e, learn a different skill set applicable to the current – or future – job) to further develop this high performing employee.
So in SMART terms, the written goal for the production scenario might look like this:
Produce widgets at an average rate of [low] to [high] per month.
SPECIFIC: Widgets being produced
MEASURABLE: [low] to [high] range
ATTAINABLE: The low number is the absolute minimum, the high number is the stretch goal.
RELEVANT: It contributes to the overall department/organizational requirements.
TIME-BOUND: The average will be calculated per month, allowing for some flexibility as long as the overall goal is met.
The low number of the range is the MINIMUM an employee would have to perform at to get a “meets expectations” rating. The high number in the range is considered the “stretch goal,” what would be considered “above and beyond” expected performance.
As long as the individual’s numbers meet expectations, the department should also be in that range. If one person’s numbers fall below expectations, in order for the department to meet expectations, someone will probably be performing in the “exceeds expectations” range. But now the performance results are based on specific, known data.
That’s Quantity – What About Quality?
OK, so they are pushing to get 25 widgets out per day. How do you make sure they are GOOD widgets? A second expectation is put into place. The first question is “What is an acceptable rework level?” A six sigma person will tell you that the number is extremely close to zero. But is that reasonable to expect? Probably not. It may be a stretch goal, but not a day-to-day type of number. So the base number must be calculated to a point of reasonableness. Then you can create your stretch goal point to be on the other side of the range. So let’s say that the company can tolerate two widgets being sent back per department per day. With four employees, that’s a rework rate of .5 per day. There is the top part of your range. The low number is the stretch goal. For sake of argument, let’s say .1 for the department.
The SMART goal would read:
Maintain a monthly widget rework average of between .1 and .5 per day.
If an employee has a rework rate greater than .5, they are “below expectations.” If their rework rate falls between .1 and .5 per day, they “meet expectations.” If their average rework per day number is lower than .1 per day, they would “exceed expectations.”
Again, this data can be easily monitored by both the individual and supervising manager so there are no surprises when a performance evaluation discussion takes place.
So you now have two goals that are easy to understand. They help the individual employees know how their work is connected to the department’s performance, and can be easily monitored and either reinforced (id performance is at or above expectations) or quickly corrected (if falling behind).
You have also split the performance expectation into two manageable areas – quantity and quality – measuring each separately.
In the next post, I’ll talk about how to conduct the Setting Expectations Discussion in a way that helps establish understanding and agreement.
John Lake has been a Business Culture and Performance Consultant/Trainer for over 20 years. JDLake Communications, LLC is designed to help organizations retain the talent they don’t know they are about to lose.