Effective Process Measures
Have you ever heard of the expression,
"Be careful what you measure, because it will get done."
Organizational process measures or metrics can become a proxy for leadership if the measures are well thought out and have a goal in mind. How might we leverage that expression to drive organizational behavior?
The purpose of this article will explore a few ideas of how to shore up process measures as well as share my favorite insights I routinely use for establishing meaningful measures for process improvement projects. These are only ideas so results will vary depending on project context.
Over the many years that I've taught and mentored process improvement initiatives, I've witnessed many variations of process measures resembling anything from complex formulae, adjectives, verbs, business outcomes, aspirations or nothing at all. In many cases these measures are not well thought out or understood. So let's first start by defining what common measures are and what they are purported to do.
Regardless of industry or organization, there are three tiered measures that if smartly assigned can be very useful in driving organizational change and improvement. Let's take a look at the following.
Business "Outcome" Measure - This measure should be aligned with organizational goals and objectives. This is usually expressed as a business outcome over a specified period of time typically monthly, quarterly or annually.
This measure is not actionable because it summarizes the effects of multiple processes and related business variables. Therefore, multiple process improvement projects need to be targeted to materially change a business outcome and it's measure. For this reason, business outcome measures are not suitable as a yard stick for process improvement projects.
Example Business Outcome Measures - customer retention, customer churn, CLV (customer lifetime value), revenue, cost of goods sold, customer satisfaction, net profit, etc.
Process Outcome Measures - A measure of process performance that mathematically influences a business outcome measure. It is typically expressed as a unit of output over a specified period of time. A process measure is actionable and is a suitable candidate for measuring the success of a process improvement project. In most cases these measures can be observed and measured in real time or within a typical work shift.
Example Process Outcome Measures - units per hour, work in process inventory, defects per hour, customer wait time, call handling time, etc.
Process Measure - A process measure is a behavior or work task that can be observed and measured in real time. Process measures will influence, correlate and/or drive process outcome measures. When selected properly, these measures target specific behaviors for process improvement.
Example Process Measures - task time per unit, task time per customer, task time per order, wait time per unit, wait time per customer, work-in-process at step D, temperature, pressure, etc.
Now that we have some context behind process measures, let's review 5 tips or guidelines to think about when assigning process success measures.
Feel the measure - Those closest to the process should be able to feel the process measure as they perform tasks or process work. In other words, they should know how they performed against this measure intuitively on an immediate or shift basis.
Similar to number 1, process metrics should be scoped to the hourly interval or not broader than one shift or work day. This keeps the process or behavior to be improved in front of those closest to the process. Providing process participants weekly or monthly process measures will only decouple the process doers from the goal at hand.
Avoid esoteric indices that are unfamiliar to the process participants and stakeholders. Any measure that requires a secondary reference or someone to explain it is not useful and will not connect to those whose behavior you're aspiring to change. Metrics such as Cpk, OEE, inventory turnover rate, etc. are not well suited to those closest to the process. These measures above have their place but not here.
Process measures should drive process behavior in the desired direction. For example, if you are trying to reduce average call handling time, this could lead to artificially concluding calls just to meet the numbers causing the frequency of calls to go up. Carefully choose a measure that does not sub optimize the current process at the expense of creating a new problem or measure downstream.
5. Use raw data measures only.
Ratios or percentages. Avoid these when possible. The problem with ratios or percentages is that you have to track two numbers, the numerator and the denominator. Either one could trigger an action or inaction.
Measures with built in standards and/or assumptions. One of my early injection molding material utilization projects way back last century had a built in 2% scrap factor. To correctly record improved material utilization I had to extract the 2% scrap factor from the analysis. Keep it simple, keep it real.
The Punchline - Driving organizational change can be an uphill battle. The role of process measures can enable change or distract it. Using the guidelines above should allow you to choose process measures that are intuitive, simple to understand, relevant to those closest to the process and drive target behaviors in the desired direction. I always encourage to keep it simple and keep it real. The rest will follow.
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