A number of different maxims attest to the power of establishing goals. “What gets measured gets done.” “You get what you measure.” “What is the difference between a practice and a game? In a game you keep score.” The intent of goals is to focus attention and they do that very well. It becomes critical, therefore, to pay close attention on where focus is to be applied.
A mentor once shared his “universal measures” to provide a language to think about potential areas in which to set goals. Those included:
- Customer issues
- Employee issues
- Support of divisional or organizational strategy, and in some cases
- Innovation/pattern shifting
The universal measures are extremely valuable because of the precision they offer in goal setting. The kinds of improvements needed to reduce defects in a process are different than those needed to satisfy an employee complaint. Using a process or value stream map to identify wait-time reduction opportunities would highlight different elements of the process than using the same map to focus on reducing defects.
The downside of this precision and the differences it highlights is that there are often interactions between the different universal measures. Reducing defects might require the addition of new technology which would negatively impact cost. Deducing costs by layoffs will almost certainly increase the number of employee concerns and issues.
So what is a goal setter to do? One option, I suppose, is to throw in the towel – to admit that goal setting is “just too hard” and retreat to a softer expectation of “do better.” While an option, I don’t find that one very satisfying – and hope you don’t either.
A more rigorous second option would be to set a “goals matrix.” There are several versions of this. One version lists the universal measures across the columns of a spreadsheet. The primary measure of interest is given a quantitative target. Each of the other measures is then evaluated in the light of the opportunity for its interaction with the primary goal. In the case of a positive interaction, the complementary measure might have its own increased quantitative target entered into the cell, or in a slightly less rigorous approach the words “while also increasing” would be entered into those cells. In the case of a potential negative interaction, the words “while not negatively impacting” might be entered into the appropriate area.
A third approach is based on the assumption that humans act to maximize their own self-interest when confronted with a challenging performance situation. Maximizing self-interest might take the form of increasing positive outcomes, or decreasing the chance of negative outcomes. To the extent you believe this dynamic might be at work in your situation, it might be useful to ask yourself, “What would a person interested in maximizing his or her own self-interest start, stop, or do differently to maximize the metric that is being proposed?”
Here is an example that illustrates this dynamic. Seeking to maximize efficiency, leaders in a customer service call center established a new incentive program based on the number of calls each phone representative was able to handle in an hour. The intent was that more customers would be served in a given time and the percentage of value added work would increase.
In the first weeks of implementation, two significant results were seen. First, the representatives received significant increases in their compensation based on dramatic increases in the number of customers served per hour. The second outcome, though, was that perceptions of terrible customer service increased dramatically! The leaders were perplexed. They had accomplished their stated goal – yet had achieved an unintended consequence they could not understand.
Put yourself into the position of a phone representative. How would you maximize your own interests given this new goal? The reps learned quickly that the way to maximize their income was to wait approximately 30 seconds into any given customer interaction and then ask a question or make a request that they believed the customer could not answer at the time of the call. The rep would then very politely ask the customer to obtain that information and call them back. The rep would mark a completed call on their log and move to the next interaction where they would repeat the short period of time/ask for additional information cycle. At first, the customers felt that the additional information requests were reasonable and would call the rep back with the additional data. After another 30 to 60 seconds, the rep would request another piece of information the customer would likely not have immediately available, ask them to retrieve that information and call them back. Another completed call for the rep.
Not considered in this scenario was how the customer felt about being on a call, needing to retrieve additional information, wait on a call queue again, retrieve additional information, wait on a call queue again … the customers became very angry. After the second, third, or sometimes fourth called back customers became very agitated and asked to speak to a supervisor. The rap politely obliged, marking yet another call in their completed calls log, leaving their supervisor to deal with the disgruntled customer.
Once this dynamic was understood, it became clear that a different metric was required in order to drive the desired behavior of better and more efficient customer service. After deliberation, the leadership team established a new metric – the number of customers issues satisfied on the first call. The reps’ behavior changed overnight.
What measures and metrics are you focused on in your organization? Which of the universal measures do they emphasize? Have you consciously considered the potential interactions or checks and balances that might exist between your metrics and other potential measures? Have you asked the question, “How would someone looking to maximize their own interests based on this measure behave?”
Remember, “you get all of what you measure.”