Measuring process improvements
One of the most common driving factors behind an organization’s pursuit of process management is the goal of continuous improvement – the state of consistently evaluating and improving the efficacy of organizational processes. Despite many organizations desiring continuous improvement, I often encounter a hesitancy when it comes to creating the necessary foundation for improvement – that being well-defined and measurable processes. In this blog post, I will endeavor to identify why this hesitancy exists and outline some simple categories organizations can use to help build measurable qualities into their process designs.
Why does it matter?
Before we go through all the trouble – why is measuring process improvements important? Quite simply, measuring success allows us to show the effectiveness of our process management efforts and keep momentum with the larger group of stakeholders within the business. As John Kotter states in his book Leading Change:
“Most people won’t go on the long march [of change] unless they see compelling evidence within six to eighteen months that the journey is producing expected results. Without short-term wins, too many employees give up or actively join the resistance.”[1]
Getting to the point where we can measure and communicate the success of process improvements demands certain prerequisites – namely, processes must be understood intellectually, documented explicitly, and managed intentionally. However, beyond these basic requirements, it is prudent to establish certain benchmarks before seeking to improve a process. A benchmark is simply a standard by which to judge or measure other things. From a process perspective, benchmarks allow us to compare the performance of a future state process to a current state process.
What are we measuring?
Going a bit further, our benchmarks must have certain measurable qualities if we are to quantify change between a current state and proposed future state. This is where organizations new to process management can be unnecessarily intimidated. They – rightfully so – see the initial process documentation to be a task in-and-of itself and are hesitant to press their process owners further to incorporate measurable qualities into their process designs. They do not want to ask too much from their process owners – especially at the outset. My message is that building these measurable qualities into a process does not have to be overly complex – particularly at the beginning.
So, what qualities should be measured in a process? Well, the answer to this question can vary based on organizational goals, available data, and numerous other factors. At a high level, I find it helpful to categorize process improvements into two groups – qualitative measurements and quantitative measurements. Qualitative measurements are non-numerical in nature and more focused on how proposed process changes “feel” to the end user. For this reason, they are more subjective by nature. Qualitative changes can be made more objective and measurable using tools such as “employee engagement” surveys. In this blog post, I am not going to focus on qualitative measurements.
Quantitative measurements, on the other hand, are numerical in nature, rooted in objectivity, and thus, more easily measured. Three quantitative measurements that are universal across most processes are time, cost, and quality. Each of these can have varying levels of depth and complexity, but for our purposes, we will look at:
Time as the active time spent by a resource to complete work and the wait time felt by the process customer
Cost as reflecting the human resources expensed
Quality as the customer’s (internal or external) satisfaction with the output of work.
Simple application of quantitative measurements
Remember that gathering this time, cost, and quality information does not have to be overly difficult. Most process owners will be able to provide the initial data. If they want to verify or test their assumptions, simply have them ask a few process doers for feedback. As Karen Martin and Mike Osterling state, “directionally correct data” is the goal:
“Most of this data is obtained by questioning the relevant process workers. Keep in mind that you want to obtain directionally correct data; that is, the data needs to be accurate enough to result in solid conclusions and relevant decisions regarding prioritization. You don’t need to conduct operational research and measure with high degrees of precision to achieve these objectives.”[2]
Time
As stated above, time can be understood as active time and wait time. Active time is sometimes referred to as processing time or service time. Active time is meant to capture the time a performer spends completing a particular activity in a process. Wait time (or lead time) captures the total elapsed time of an activity – this includes any time spent in queue, batching of work, interruptions to work, plus the active time of an activity. Wait time is representative of what the customer feels while awaiting the output of a process. Both active time and wait time can be calculated at the activity level and then aggregated at the process level. Also, identifying large gaps between active and wait time often highlights opportunities for further improvement.
Cost
Although measuring the cost impact of your processes can be quite complex and include human resources cost, technology cost, material cost, etc., when just starting out, I recommend focusing on the cost per human resource required to complete an activity or process. To calculate this, you simply multiply the active time of an activity by the cost of the resource (an active time of 90 minutes performed by a resource that carries a cost of $35/hr yields an activity cost of $52.50). Yes, this calculation is simple, but the effect can be quite profound. Showing a simple cost calculation like this across a process can open the eyes of many stakeholders and help motivate improvement.
Quality
In measuring quality, the goal is to identify defects generated in the process. As a process flows from beginning to end, multiple “provider-customer” relationships are established. The provider is the owner of the upstream activity, while the customer is the owner of the downstream activity. To assess the quality of work, the customer should provide an assessment of the provider’s output. This can be achieved by using the metric of percent complete and accurate[3]. To obtain this metric, simply ask the customer how often they must correct, complete, or clarify the work received from the upstream provider. If out of 10 process cycles, they must correct, complete, or clarify information 2 times, then the providing activity has a percent complete and accurate of 80%. This metric can also be aggregated across the process for a total process percent complete and accurate measurement.
As mentioned above, generating quick process improvement wins and communicating those wins with business stakeholders is key to keeping momentum. As we move into a new year, I encourage you to consider incorporating some of these simple measurable qualities into your process designs. Doing so will give you the data you need to prove that your process improvements are making organizational processes faster, cheaper, and better.
[1] John Kotter, Leading Change (Boston, MA: Harvard Business Review Press, 2012), 11.
[2] Karen Martin and Mike Osterling, Metrics-Based Process Mapping (Boca Raton, FL: CRC Press, 2012), 27.
[3] Beau Keyte and Drew A. Locher, The Complete Lean Enterprise (New York, NY: Productivity Press, 2015 edition).
