As I help my daughter through her decision regarding which college to attend, I can’t help but think how powerful it would be to be able to try out a decision and seeing the projected outcome before actually committing to the decision.
This would also have distinct value for operational performance management. Improving operational performance relies on identifying the performance bottleneck and taking action to remove or optimize that issue. In many cases there may be alternative actions that could be taken to reduce or eliminate the bottleneck, and it can be difficult to determine which action will lead to the optimal result.
Scenario analysis could help with this by allowing the decision maker to see the potential outcomes and then select the action with the highest potential for a successful outcome. To be most effective, scenario analysis should be easy enough for any decision maker to use, and should also present results with low latency so as not to interrupt the decision-making process.
So the next question is what metrics we should focus on with scenario analysis. Applying scenario analysis to high-level Key Performance Indicators (KPI metrics) would not really provide much value since KPIs represent desired outcomes and are not really actionable. Actionable metrics can be found in one of two ways:
- Drill into a KPI to get to a low enough level of granularity that a single person can affect that outcome, or
- Determine the Key Performance Drivers (KPDs) that affect the KPI outcomes.
For example, if Revenue is below target, then we could drill into the Revenue KPI until we find the location(s) and channel(s) that are contributing most to the shortfall. Then by analyzing different scenarios such as increasing sales through a specific channel or in a specific location, we can determine which would have most impact on the total Revenue. In this way, we could identify in priority order the actions that should be taken.
Similarly, if Gross Margin is under target, we could look at the drivers, one of which would be Cost of Goods Sold (COGS) by product line. By analyzing different scenarios such as changing product mix, we could determine the most appropriate mix for optimizing both Revenues and Gross Margin.
There is much that could be done to improve operational performance by equipping decision makers not only with the ability to understand the holistic performance of a value stream or business process through and interactive dashboard, but also providing them with the ability to interactively conduct “what if” scenario analysis and immediately receive the answers. “Trying before committing” would significantly improve operational decisions. There is more to come on this topic….
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