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Robert, a Measure Up subscriber, asked how can you demonstrate results when your job is to make sure something doesn’t happen. He’s basically asking how can you measure what you want to prevent?

There are many situations where organisations or businesses are trying to prevent things from happening:

• Accidents, injuries and deaths
• Non-conformances in regulation
• Terrorist attacks
• Pandemics
• National security threats
• Domestic violence

To know how well we’re doing this preventing, and how to do it better, we need to measure our prevention processes. But if measures are evidence of results, and evidence is observable only in the physical world, how could we possibly measure something that doesn’t happen? Of course, we can’t. So we need to think differently about it, to piece something useful together for monitoring prevention activities.

Firstly, we still need evidence of the ultimate outcome we want. We can’t measure if it doesn’t happen, but we can measure if it does. If we want to reduce the rate at which an undesirable event happens, then one way to measure that would be the time between those events. A good result is that the time between those events gets longer and longer.

For example:

• In safety, the undesirable events are injuries and deaths.
• In auditing, the undesirable events are non-conformances.

These are the lag measures of prevention, and they’re useful but not enough to be actionable. We need more.

So secondly, we want to understand what factors have the most power in preventing those undesirable events. These factors might include attitudes, knowledge, skills, practices or behaviours, or ‘near misses’ (where the event almost happened but was successfully prevented or luckily didn’t eventuate). These occurrence of factors – once we work out which have the most power in preventing our undesirable events – should also be measured.

The second piece is really about finding the lead indicators of the undesirable event (the lag effect, measured by a lag indicator). For safety, the lead indicators might be number of near misses, average number of overtime hours worked, or average test score of participants completing safety training. For auditing, the lead indicators might be percentage of prescribed work practices adhered to, or average time to put new recruits through training on work standards.

For both the lag and lead measures of prevention, we need to start with clear articulation of the lag results and lead results that matter, before we choose measures. In PuMP, Step 2 provides the Measurability Tests to help articulate measurable lag and lead results, and the Results Map helps us explore and test the lead-lag relationships. Then in Step 3 of PuMP, the Measure Design technique makes it easy to find the right lag and lead measures.