Identify and Prioritize Opportunities for Workflow Improvements Fin Analytics

Identify and Prioritize Opportunities for Workflow Improvements


In this post, we’ll offer a formula for ranking workflow improvement opportunities, provide a framework for how to size those opportunities using data distributions, and discuss how to measure the impact of changes made.


When thinking about workflow improvements and how to prioritize them, it make seem like the obvious thing to do first would be to either start with the workflow that is most commonly used or has the highest error rate, assuming that change will have the biggest impact on the overall organization.

But, if something is very broken, but only happens 1 in 10,000 times, it probably shouldn’t be the first thing to focus on. Likewise, if a workflow occurs frequently, but is already very optimized, it’s also not the right place to start.

How do you know where the greatest opportunities for workflow improvement exist, and which to prioritize?

In this post, we’ll offer a formula for ranking workflow improvement opportunities, provide a framework for how to size those opportunities using data distributions, and discuss how to measure the impact of changes made.

Prioritizing opportunities for improvement: Size x Frequency x Difficulty

When looking at and prioritizing opportunities for workflow improvement, there are three vectors to consider in making your decision. The biggest areas for improvement can be found at the intersection of size (How big an improvement can you make?), frequency (How often does this come up?) and difficulty (How difficult will it be to make this change?)

These are three key questions to consider when deciding which workflows to work on, and in what order. It may sound obvious, but it’s an important formula to keep in mind, which yields the overall opportunity of the change.

How to size an opportunity: Focus on the P50-P80

When it comes to then sizing an opportunity, we’ve found that averages can actually be very deceptive, as can outliers. If you only look at the averages across your workflow data, the data will always ‘wash out,’ and it becomes difficult to see where opportunities are. Similarly, if you only look at outliers, you may find that your workflow is generally good, but there are a small number of edge cases that were a total disaster (and often for reasons beyond the workflow’s impact).

Rather than focusing on averages and outliers, we instead recommend focusing on the P50 to P80 cases when sizing opportunities.

Anything above the 80th percentile (the longest cases) are useful for other types of analyses, but these are typically representative of the outliers mentioned previously. Instead, ask what the best and worst performance looks like within the P50 to P80 cases, and that delta will be a strong indicator as to where to focus.

Ask what workflows or coaching efforts you can work on to move the P80 to the P50 most efficiently. By moving that distribution over, you will unlock massive efficiency gains for your organization.

Measuring the impact of workflow changes:

Once you’ve made a change to a workflow, how do you measure the impact? First, it’s important to, as much as you are able, hold as many other variables constant as possible. If you improve a workflow, but also change the agents using that workflow, for example, it’s easy to lose sight of the impact the change actually had.

Second, measure work continuously. By analyzing process data, you will be able to see how agents interact with the new workflow, how processes adapt, and whether the change you made is having the desired impact.

Once you’ve held all other variables constant and begin to capture your team’s process data, you can analyze whether the changes you make have a meaningful impact on the team’s averages and outliers, and whether you are moving numbers within the P50 to P80 range.


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