Separate outcome metrics from activity and initiative progress metrics to validate strategic hypotheses more effectively.
Metrics for Activities vs. Metrics for Outcomes
Consider a typical strategic objective such as Improve Customer Value.
The objective may be quantified by outcome metrics such as:
- Customer Satisfaction Score
- Customer Retention Rate
- Revenue per Customer
These metrics track the results associated with achieving the objective.
The same objective may also have several strategic initiatives:
- Redesign Customer Onboarding
- Improve the Support Process
- Introduce a Customer Feedback Program
- Enhance Product and Service Quality
Each initiative may have its own activity metrics, such as:
- % of Milestones Completed
- Implementation Progress, %
- Activities Completed, %
- Budget Utilization, %
One group of metrics quantifies the results we expect from the objective.
Another group helps us monitor the activities and initiatives intended to produce those results.
The Problem: Mixing Outcome and Activity Metrics
The problem begins when both groups of metrics are treated as if they measured the same thing.
In the example above, should initiative progress metrics contribute directly to the performance of the strategic objective? In most cases, the answer is no.
- Imagine that all strategic initiatives are 95% complete while the Customer Retention Rate continues to decline. If both are averaged together, the objective may still appear to perform reasonably well. That would be misleading.
The opposite is also possible:
- The Customer Retention Rate may improve while some initiatives are behind schedule because the improvement is coming from earlier work or market conditions.
Combining both groups of metrics into one average would hide what is actually happening.
The Correct Measurement Logic
The best approach in this case is to separate the activities and outcomes.
The execution of strategic initiatives should be evaluated using metrics that track activities, milestones, or deliverables. The objective itself should be evaluated using the metrics that quantify its intended outcomes.
If various metrics are combined, this gives us two distinct performance perspectives:
- The combined activity metrics show whether the planned initiatives are progressing.
- The combined outcome metrics show whether the objective is being achieved.
Both perspectives remain connected to the same objective, but they are calculated separately.
The Solution in BSC Designer
In BSC Designer:
- Metrics that measure achieved outcomes are configured as lagging indicators.
- Metrics that track activities or initiative progress are configured as leading indicators.
An activity metric should be treated as a leading indicator only when there is a reasonable hypothesis that the activity contributes to the intended outcome. Simply measuring that an activity was completed does not automatically make it a meaningful leading indicator.
If we have several objectives quantified this way, we can build a hierarchy in which:
- The outcome of one objective, quantified by lagging metrics, can become a leading input for another objective.
When building such hierarchies, we can reflect the cause-and-effect logic between objectives by deciding whether a child objective contributes to its parent as a leading (input) or lagging (outcome) type.
For example, improved employee capabilities may be the outcome of a training objective, while also serving as a leading factor for an operational-efficiency objective.
The Benefits of Tracking Activities and Outcomes Separately
One way to think about activity and outcome metrics is as a control system in which activity metrics quantify our efforts and outcome metrics validate the achievements.
What are the benefits of having this configuration of metrics?
- Confirming the initial hypothesis. In the best case, we will see efforts converted into achievements. If that is the case, we can assume that the initial strategic hypothesis was correct.
- Questioning assumptions. What if the outcome metrics do not validate the efforts? That is also valuable: we have an early signal that something is wrong with the initial assumptions. That becomes the starting point for discussion and learning.
- Making manipulation easier to detect. Separating activity and outcome metrics makes manipulation easier to detect, as strong reported execution must also be validated by the expected outcomes.
A bonus calculation may still include both types of metrics, possibly with different weights, but the distinction makes it harder to present completed activities as evidence of achieved results. The last statement does not contradict Goodhart’s Law; we discussed this in more detail in the article about gaming a measurement system.
Outcome Depends on the Planning Horizon
In the beginning, we introduced the idea of an outcome in the context of a certain objective. The “desired outcome” of executing a certain objective sounds like something natural that does not need any further definition.
That is true under the assumption that the outcome is immediately visible. For example, customers may be more satisfied with customer service, and we know this almost immediately through surveys.
But in some cases, the outcome lags in time. Think, for example, about typical training:
- there is an immediate measurable outcome, such as attendee satisfaction;
- there is an outcome with a longer measurement horizon, such as the number of ideas implemented in practice; and
- there may be even more long-term outcomes, such as the impact of those ideas on the organization.
All are valid outcomes — the measurement horizons are different.
A similar approach is promoted by the Results-Based Management Framework, where we are dealing not just with outcomes, but with outputs, outcomes, and impact.
The practical conclusion is that if your performance measurement system feels incomplete, you might want to look at a longer planning horizon and include long-term outcome and impact metrics.
Video Example of Implementation
In the accompanying video, I demonstrate this logic using an Excel spreadsheet and show how to implement it in BSC Designer using a practical strategic planning example.
Summary
For every strategic objective, calculate separately the performance related to activities and the performance related to outcomes.
This approach provides better visibility into strategy execution. It helps explain why certain activities are not converting into the desired outcomes, validates whether the initial strategic assumptions were correct, and highlights when those assumptions should be reconsidered.
Alexis Savkin is a Strategy Architect and founder of BSC Designer, a strategy execution software platform with the Balanced Scorecard at its core. He helps organizations translate strategy into measurable objectives, KPIs, and initiatives. Alexis is the creator of the Strategy Execution Canvas, the author of 100+ articles on strategy and performance measurement, and a regular speaker.