by Ibrahim Saleh | The Mplus Group
In today's continuously evolving digital era, measuring our progress is becoming more critical than ever. This evolution has moved performance measurement from simple accounting to complex key performance indicators. This article aims to demonstrate eight metrics that can measure any process; these metrics exist in all types of operations. For less complex processes, these metrics are often clear operational key performance indicators on a dashboard; however, in more complex functions, these metrics can be more of categories that have multiple metrics.
Before talking about measuring a process, let us define it first. A process is a series of definable, repeatable, and predictable steps. Definable means you can draw a picture of it, and the process has a clear start and end. Repeatable means expecting the same results every time you use the process. Predictable means you know ahead of time how long the process will take. With this definition in mind, I’ve developed eight metrics to measure any process; these metrics are (1) volume, (2) turnaround time, (3) cycle time, (4) on time completion, (5) quality defects, (6) abandon volume, (7) budget & cost, and (8) experience. It's important to note that these metrics are not new or a breakthrough, but these eight metrics demonstrate a structured way to measure a process's performance without getting overwhelmed with the vast amount of data available or without becoming tunnel-visioned into specific metrics.
I will use three examples from manufacturing, administrative, and clinical to help explain how the eight metrics translate to different operational settings. For manufacturing process, consider a generic assembly line where materials are assembled into a final product. For administrative process, consider a call center receiving phone calls from customers. For clinical process, think of scheduled clinical office visits for patients who come to a doctor's office. These three examples will help demonstrate examples for each of the eight metrics.
Volume - this metric focuses on the number of times the process is used. This metric can be seen as the volume requested from the process. This concept applies to both batches and single-piece flow; for batches, the volume is the number of units within a batch, and for single-piece flow, the volume is the number of pieces flowing through the process. An example of this metric for an assembly line would be units produced. An example of this metric for a call center would be calls received. For an office visit an example of this metric would be scheduled visits.
Turnaround time - this metric focuses on the total time it took the volume to go through the process from request to delivery. This metric can be looked at in two ways; the first is how long the process took to turn around an entire batch. The second way is how long the experience is through the process. Both look at the time spent from the customer's perspective. An example of this metric for an assembly line would be order to delivery time. An example of this metric for a call center would be dial-to-hang up time. An example of this metric for an office visit would be door to door time.
Cycle time - this metric focuses on the total time the process took to complete the requested volume. In a batch, cycle time can be considered the time spent on each unit multiplied by the number of units in the batch. In a one-piece flow, cycle time is the time spent on a single piece multiplied by the number of pieces. Both look at the time spent from the operation’s perspective. An example of this metric for an assembly line would be time per unit. For a call center, an example of this metric would be time per call. An example of this metric for an office visit would be time per visit.
On-time completion - this metric focuses on the percentage of volume the process could complete within a specific requirement. Considering that when the request was placed into the process, a promise was made to turn around the request within a particular parameter, this parameter may be a time limit or due date. This metric focuses on measuring to what extent the process kept that promise. An example of this metric for an assembly line would be units delivered within the target. An example of this metric for a call center would be calls completed within the target. An example of this metric for an office visit would be visits completed within the target.
Quality defects - this metric focuses on the number of times the process did not proceed as planned but was still completed. This metric measures how often the process did not flow smoothly, and additional steps had to be made to correct the flow and complete the process. An example of this metric for an assembly line would be units reworked. An example of this metric for a call center would be calls redirected. An example of this metric for an office visit would be rescheduled visits.
Abandon volume - this metric focuses on the number of times the process did not proceed as planned and was not completed. Unlike the previous metric, this looks at how often the process wasn't completed and either had to be restarted or canceled. An example of this metric for an assembly line would be units scrapped. An example of this metric for a call center would be calls dropped. An example of this metric for an office visit would be visits canceled.
Cost budget - any process operates within budgeted resources to deliver requests, this metric focuses on if the process performs within those budgeted resources. An example of this metric for an assembly line would be the cost per unit produced. For a call center, an example of this metric would be staff overtime. An example of this metric for an office visit would be clinical overtime.
Experience - this metric focuses on the experience through the process. This metric can be looked at in two ways; the first is through a specific score based on a satisfaction survey, and the second is through the previous seven metrics meeting their targets. An example of this metric across all three examples would-be customer, caller, or patient satisfaction scores.
In conclusion, no matter what the metrics are, the important thing is to be clear on how the metric connects to the process and what behaviors influence which metrics. Those who understand what they are measuring, are more likely to be able to influence their processes appropriately to improve their metrics.
M+ is a virtual learning and coaching platform for performance improvement practitioners and business leaders. Performance Improvement depends not only on data, algorithms, and processes, but also on Emotional humans. Beyond the traditional focus on machines and methods, the elusive factor of how humans think/feel has been referred to by terms like culture or mindset. We believe it goes beyond that, even if there is more than the limitations of a single word. Leading people in an enterprise is more than mindset or milieu...it’s M+.
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