Identifying Appropriate Metrics

Metrics Make Informed Decisions

To make decisions that improve your organisation’s success (and to avoid those that could hurt it), you need to rely on data that’s derived from metrics. This data has to be relevant, recent, and actionable, because it is displayed on your dashboard.

Metrics should be aligned to the organisational goals and should provide answers to the following questions.

• What are the goals (future)? List your organisation’s top priorities or strategic objectives.
• What happened (past)? This includes historical results, but more importantly, the trends over time.
• Which targets did we reach? List all the targets you met.
• Which targets were missed? Investigate these to discover why they were missed.
• Should something be improved? Narrow down the options with feedback and surveys.

Metrics Work Together

Although metrics should always be aligned with objectives, more than one metric might contribute to achieving them. You might also identify leading or lagging indicators that contribute to a metric. These are worth monitoring because they can provide insight into why a metric suddenly changed (a lagging indicator) or help predict that a metric might change (a leading indicator).

For example, the percentage of a population using masks is a leading indicator of a decline in new COVID-19 cases.

More Examples

A subscription-based software company has a target of $10 million annual recurring revenue (ARR). The executives have flagged retaining and growing top talent as a key priority alongside disrupting the market with new technology.

On the strategic dashboard, the metrics aligned to these objectives might include several possibilities.

• ARR: Although this is the most obvious metric, supplementary or complementary metrics could be tracked to help provide additional context, or to show how they might affect the achievement of $10 million ARR.

  Some examples of these metrics are:

  • Forecasting ARR: What predictive metric forecasts the projected ARR, based on current actuals?
  • Key accounts (percentage of portfolio and customer satisfaction): What percentage of the customer portfolio is represented by the largest accounts? What happens if they churn? How likely is it that they will churn (satisfaction of key accounts)?
  • Renewal rates and/or account churn: What percentage of existing customers renew, and how does that percentage align with internal targets and industry benchmarks?
• Retain top talent: eNPS is an increasingly common metric for measuring employee satisfaction but other factors may also be monitored, including:
  • measuring key criteria against industry benchmarks such as salary packaging and benefits, annual leave, parental leave, and so on
  • employee satisfaction across other factors (location, view of manager, perception of career progression, self-assessed stress levels, and so on)
  • a target for employee retention (this needs to be defined and then monitored; eg, employee turnover <90% year after year).
• Disrupting the market with new technology: This will vary, based on the nature of the industry, but leadership usually identifies the criteria that make them ‘disruptive’ and then metrics can be aligned with those objectives.

Which Metrics Should You Use?

Before creating any metrics, determine the objective. Interpretation is never accurate, so be as specific as possible. Consider an example in which the objective is to ‘increase customer satisfaction’. That’s straightforward, right? But this could mean different things for different teams.

• To the technical support team, it might mean monitoring support-ticket response time to ensure it’s within a threshold.
• To a customer success manager, it might mean ensuring that the customer’s time to value (TTV) is within 2 months.
• To a sales manager, it might mean ensuring that >90% of accounts renew.

Before trying to decide which metrics to use, follow the steps below.

1. Identify the objective (or intended result).
2. Determine whether the intended objective can be measured directly. (For example, if the intended result is to increase product sales, the direct measure is sales revenue.) Select the right measure for the objective.
3. Set targets and thresholds.
4. Define and document metrics.

This last step is crucial, particularly because there are often multiple stakeholders with a variety of opinions on things such as frequency, or who might need access to the data.