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12 Characteristics of Effective Metrics

Creating performance metrics is as much art as science. To guide you in your quest, here are 12 characteristics of effective performance metrics.

1. Strategic. To create effective performance metrics, you must start at the end point--with the goals, objectives or outcomes you want to achieve--and then work backwards. A good performance metric embodies a strategic objective. It is designed to help the organization monitor whether it is on track to achieve its goals. The sum of all performance metrics in organization (along with the objectives they support) tells the story of the organization’s strategy.

2. Simple. Performance metrics must be understandable. Employees must know what is being measured, how it is calculated, what the targets are, how incentives work, and, more importantly, what they can do to affect the outcome in a positive direction. Complex KPIs that consist of indexes, ratios, or multiple calculations are difficult to understand and, more importantly, not clearly actionable.

"We hold forums where we show field technicians how our repeat call metric works and how it might impact them. We then have the best technicians meet with others to discuss strategy and techniques that they use to positively influence the metric," says a director of customer management at an energy services provider.

3. Owned. Every performance metric needs an owner who is held accountable for its outcome. Some companies assign two or more owners to a metric to engender teamwork. Companies often embed these metrics into job descriptions and performance reviews. Without accountability, measures are meaningless.

4. Actionable. Metrics should be actionable. That is, if a metric trends downward, employees should know what corrective actions to take to improve performance. There is no purpose in measuring activity if users cannot change the outcome. Showing that sales are falling isn’t very actionable; showing that sales of a specific segment of customers is falling compared to others is more actionable.

Actionable metrics require employees who are empowered to take action. Managers must delegate sufficient authority to subordinates so they can make decisions on their own about how to address situations as they arise. This seems obvious, but many organizations hamstring workers by circumscribing the actions they can take to meet goals. Companies with hierarchical cultures often have difficulty here, especially when dealing with front-line workers whose actions they have historically scripted. These companies need to replace scripts with guidelines that give users more leeway to solve problems in their own novel ways.

5. Timely. Actionable metrics require timely data. Performance metrics must be updated frequently enough so the accountable individual or team can intervene to improve performance before it is too late. Some people argue that executives do not need actionable or timely information because they primarily make strategic decisions for which monthly updates are good enough. However, the most powerful change agent in an organization is a top executive armed with an actionable KPI.

6. Referenceable. For users to trust a performance metric, they must understand its origins. This means every metric should give users the option to view its metadata, including the name of the owner, the time the metric was last updated, how it was calculated, systems of origin, and so on. Most BI professionals have learned the hard way that if users don’t trust the data, they won’t use it. The same is true for performance metrics.

7. Accurate. It is difficult to create performance metrics that accurately measure an activity. Part of this stems from the underlying data, which often needs to be scanned for defects, standardized, deduped, and integrated before displaying to users. Poor systems data creates lousy performance metrics that users won’t trust. Garbage in, garbage out. Companies should avoid creating metrics when the condition of source data is suspect.

Accuracy is also hard to achieve because of the way metrics are calculated. For example, a company may see a jump in worker productivity, but the increase is due more to an uptick in inflation than internal performance improvements. This is because the company calculates worker productivity by dividing revenues by the total number of workers. Thus, a rise in the inflation rate, which artificially boosts revenues—which is the numerator in the metric—increases worker productivity even though workers did not become more efficient.

Also, it is easy to create metrics that do not accurately measure the intended objective. For example, many organizations struggle to find a metric to measure employee satisfaction or dissatisfaction. Some might ask users in surveys but it’s unclear whether employees will answer questions truthfully. Others might use the absenteeism rate but this might be skewed by employees who miss work to attend a funeral, care for sick family members, or stay home when daycare is unavailable.

8. Correlated. Performance metrics are designed to drive desired outcomes. Many organizations create performance metrics but never calculate the degree to which they influence the behaviors or outcomes they want. Companies must continually refresh performance metrics to ensure they drive the desired outcomes.

9. Game-proof. Organizations need to test all performance metrics to ensure that workers can’t circumvent them out of laziness or greed or go through the motions to make a red light turn green without making substantive changes. “Users always look for loopholes in your metrics,” says one BI manager. To prevent users from “fudging” customer satisfaction numbers, one company hires a market research firm to audit customer surveys.

10. Aligned. It’s important that performance metrics are aligned with corporate objectives and don’t unintentionally undermine each other, a phenomenon called “sub-optimization.” To align metrics, you need to devise them together in the context of an entire ecosystem designed to drive certain behaviors and avoid others.

11. Standardized. A big challenge in creating performance metrics is getting people to agree on the definitions of terms, such as sales, profits, or customer, that comprise most of the metrics. Standardizing terms is critical if organizations are going to distribute performance dashboards to different groups at multiple levels of the organization and roll up the results. Without standards, the organization risks spinning off multiple, inconsistent performance dashboards whose information cannot be easily reconciled.

12. Relevant. A performance metric has a natural life cycle. When first introduced, the performance metric energizes the workforce and performance improves. Over time, the metric loses its impact and must be refreshed, revised, or discarded.

"We usually see a tremendous upswing in performance when we first implement a scorecard application,” says a program manager at a major high tech company. “But after a while, performance trails off. In the end you can’t control people, so you have to continually reeducate them about the importance of the processes that the metrics are measuring or you have to change the processes."

Posted by Wayne Eckerson on April 19, 2010


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