Do you measure outcome, activity, or both?

There are many different ways to look at the data in your organization. Two of the most common types of metrics look at activity and outcome. Activity-based metrics measure the effort that is applied to the work being done. They are typically some measures of volume and velocity. Outcome-based metrics measure what happens at the end of work performed.

We can look at several examples to break these down for different industries.

For organizations measuring their sales performance, metrics like units sold are activity-based, whereas gross margin would be an outcome.

For insurance companies, metrics like written policy counts are activity-based, with policies in force being outcome-based.

When organizations start to combine both metric into their reports and dashboards, they can understand the value of their efforts. When an organization combines their units sold with profitability, they see what effort they are exerting for the overall return. If a company moves a large number of units but only has a small return on that effort, it can evaluate if the action is worthwhile. If a product has large profitably with a limited number of units, the information can be understood to see if a pattern can be repeated with other sold items.

An area of interest for activity-based metrics is workforce management. Within teams, managers seek to have a balance between team members to make sure the load is shared. Insurance companies often have teams of claims adjusters that work together to settle and resolve claims. Using analytics and activity reports, managers can understand if certain team members are overloaded or underutilized and adjust work patterns accordingly.

Using the same data set and monitoring outcomes, like the total time to settle a claim, managers can also understand who within the team is a top performer or where team members might need assistance or training to improve performance.

When working with a data set, picking and choosing the right metrics is important. However, having a mix of activity and outcome metrics will allow the analyst to see a bigger picture of how much effort is allocated to tasks and see if the right value is produced.

An easy way to understand groupings of data is using scatter plots, with one dimension being the activity metrics and the other being the outcome. In most cases, the dots within the scatter plots should be clustered with a path that shows as the activity increases, so does the outcome. When outliers don’t meet this expectation, they are immediately visible, as they won't follow the path outlined by the majority of the data, they will either show more activity for less outcome or more outcome for less activity. These anomalies are the ones that should be studied and reviewed, as they are where the interesting information is.

Every organization and even department within an organization will have different metrics to measure, but having a mix of both activity and outcome values will allow the user to contextualize the information and understand the value for effort equation.