OKR, leading and lagging indicators

In this post, we’ll look at what leading and lagging indicators are, and how they can be used with OKR to achieve the business outcomes you’re looking for. While all this might sound a bit technical at first, it’s pretty simple to grasp, so let’s jump in.

Inputs, outputs & outcomes

Outcomes vs outputs. This is a theme you’ll hear often associated with OKR. You’ll hear that OKR helps companies to focus on achieving ‘outcomes’ rather than simply increasing ‘outputs’, and while the former is true, that doesn’t mean the latter isn’t important or contrary to OKR.

Input and output measurement are terms used in economics and systems design and have become increasingly popular in the field of performance management.

In simple terms, an input into a management system can be things like time, or money, or effort. An input is usually something within the direct control of a person, a team or the organization.

An output is something you can measure, is the result of a process, and almost exclusively, can only be measured once it’s been produced. An output of a management system could be products, revenue or closed support tickets, to name a few.

An outcome, by contrast, is an important consequence that has a meaning. A positive outcome isn’t a number, it isn’t something you do, it’s a changed state you reach that’s better than where you began. In OKR, your Objective is your outcome.

OKR is a system, which means it has inputs and outputs, and when you understand these and how they’re connected, you’ll be able to use OKR to achieve any outcome you like.

Leading and lagging indicators.

We recently wrote a comparison of OKR vs 4DX, a popular management framework that uses leading and lagging measures extensively. So what are they?

Leading indicators simply measure inputs to a system, lagging indicators measure outputs. Or put another way, lead measures are within your control, lag measures aren't.

For example, take the human body. Your body is a system that requires inputs, like food and water to function. How healthy a body is, can be gauged using a number of different measurements. The most popular lag measurement most people use is weight.

It’s scientifically accepted that if you want to lose weight, you need to watch your calories. Since calories contained in food are a good lead measure of what you input into your body, if you want to reduce your weight, you reduce your calories.

While your weight isn’t something you can directly control (unless you chop off an arm or leg) and therefore a lag measure, if you want to influence it, you can do so through direct control of a lead measure like the number of calories you consume.

Change your lead measure, and your lag measures should follow.

Another way to reduce weight is to burn calories through exercise. If you decide to lose weight through exercise, instead of measuring calories consumed as your lead measure, calories burnt becomes a lag measure since burning calories is an output of exercise. The time you decide to spend exercising becomes your lead measure since this is something you can directly control. The more time you spend exercising, the more calories you burn, the more weight you lose.

The way in which lead measures influence lag measures is an important concept to keep in mind when we look at how this works with OKR.

So to recap:

A lead measure is:

• A metric
• A measure of input into a system
• Something you have direct control over
• Something you can act on and change, like an action or task

A lag measure is:

• A metric
• A measure of output from a system
• Something that you don’t have direct control over
• Something that’s already happened, a result of something.

Tying this together with OKR

The simplest way to tie this into OKR is to think like this.
Objective, Key Result, Initiative = Outcome, Lag Measure, Lead Measure

Your Objective always describes the outcome you want to achieve, the future place or state you want to get to that’s better than now. It’s not a number or a measurement, it’s always a description of what you want to achieve.

Key Results are always lag measures since they always measure something you want to influence, not something you control. People often get lead and lag measures mixed up when creating Key Results and turn them into things they do rather than actual results.

Initiatives can be lead measures since they’re the things you have direct control over that should influence your Key Results. If you’re looking to increase a lag measure with a Key result like Increase NPS to 75%, a good lead measure for an Initiative would be “increase our support team to 20 people”.

Here’s another example:

If your Objective is “To become healthier than I’ve ever been” and your Key Results are “Weight is 75kg”, “Resting heart rate is 55bpm” and “BMI is 19” your Initiative could be “Increase distance run to 5k”, “Reduce daily calories to 1600”, and “Maintain at least 8 hours per night”.

Since your Initiatives all contain lead measures, you can track these and change them if you need to, to influence your Key Results. If your Initiative “Increase distance run to 5k” becomes too difficult to achieve the beauty of Initiatives is, you can change them. For example, you could change your Initiative to something like “Increase days run to 3 per week” and see how this affects your Key Results.

Put simply, by understanding lead and lag measures in OKR, your Initiatives become powerful measurements that you control that directly affect your Key Results. The difficult part is, as always, choosing the right things to measure, which you can read about here in the anatomy of a Key Result.

Conclusion

Lead and lag measures popular in performance management take on an extra dimension when combined with OKR. They make outcomes not only measurable but also controllable and predictable by combing Objectives, Key Results, and Initiatives into a powerful system of outcome measures that’s simple, agile and effective.

Change your Initiatives, and your Key Results should follow.