How to measure the progress of OKRs using Leading and Lagging Indicators

Ideally, Objectives and Key Results (OKRs) help express what you want to achieve, instead of only listing what you want to do.

Using OKRs in Product Management means that those Product Goals emerge from your Product Strategy Choices and serve as a bridge to inform your actions during Product Discovery and Delivery activities. Naturally, most product teams focus on metrics that capture the ultimate success from one of the most important strategic themes, like monetization, user engagement, growth, satisfaction, or process quality.

But the point of setting goals shouldn’t just be to measure success at the end of a goal cycle or fiscal year (which can often be seen in OKR Theater). Instead, the most significant benefit comes from regularly checking in on your progress and adjusting your actions accordingly.

Build-Measure-Learn Cycle of Product Goals

But to experience these benefits, product teams need to rely on metrics that respond to their actions as directly and quickly as possible, instead of just reflecting on results of the past.

Here’s how this article will help you:

• Using Leading and Lagging Indicators in Product Management
• Leading and Lagging Indicators in Product Management Practice
• Causation and Correlation in Lagging and Leading Indicators
• Identifying the Right Leading Indicators for Your Product
• Using Insights to Work Backward
• Adapting Leading Indicators to Outcome OKRs
• Moving beyond Outcomes ‘by the book’
• Takeaway: Prioritize Leading Indicators to Avoid Lagging Decision-Making

Using Leading and Lagging Indicators
in Product Management

Individual product teams often realize that their goals may be important on the company level but they may not“move the needle” to create real impact. Unfortunately, the pace at which these goals change creates a lag in how product teams can receive and act on feedback regarding their work’s impact. By the time metrics like company revenue or user growth have changed significantly, you can’t tie these lagging indicators to any of your previous efforts and are already working on the next initiative.

Yet there are (probably) plenty of metrics an individual team can more directly influence. At least in theory. To adjust actions based on continuously measured progress, teams need metrics that lead them toward creating and measuring success. This is why these are called leading indicators.

Leading indicators allow you to predict the future. They are hard to create but worth it for their predictive value.

In a nutshell, the key differences between leading and lagging indicators can be summarized like this:

The Difference between Leading and Lagging Indicators

Lagging indicators can also include metrics like revenue, NPS, or customer churn. Other typical examples of leading indicators could be “number of marketing emails sent,” “page views of product detail pages,” or “CTR of homepage banner.”

Leading and Lagging Indicators Examples

But, as so often in Product Management, there’s lots of grey in this seemingly black-and-white perspective on leading and lagging indicators. But the clear separation of leading and lagging indicators can serve as a critical input for the OKR definition of product teams.

Let’s unpack it.

Leading and Lagging Indicators in Product Management Practice

Imagine you’re part of the product team that works on an email service platform’s integrations. And, for the sake of example, let’s say your whole company cares about subscription revenue during a given goal cycle.

Naturally, an increase in revenue results from winning new customers, upselling users because they are particularly active, or reducing churn. And all three of those drivers will only change significantly through contributions from multiple teams working in different departments at the end of a quarter or even a year.

Working on the integrations feature within one of the departments, you now face two distinct challenges:

1. While you know where your department’s goals fit in with the bigger picture of the company, they still only allow you to review your actions’ impact in hindsight—at the end of the quarter.
2. And while you could develop more responsive metrics on a team-level, these wouldn’t have much impact on company or department priorities.

That’s one of the main challenges to deal with when identifying leading indicators for a team to act on: balancing certainty about indicators at a company level with responsiveness to team priorities.

One of the main challenges to deal with when identifying leading indicators is balancing certainty about indicators at a company level with responsiveness to team actions.

Ultimately, the more precise categorization of what makes a metric leading or lagging depends on the context. Here are some flavors I'd consider:

• How the metric is measured: Technically, an NPS measurement could be more leading than revenue just based on the theoretical user journey. But when the metric is only evaluated once or twice a year, it becomes more of a lagging indicator due to its almost non-existent detectable change for a team.
• The level you want to measure: Revenue, etc. are probably fine for the company- or department-level OKRs that are only evaluated at the end of a cycle in hindsight or throughout a year. But for a product team that wants to check whether they are on track every one or two weeks, that doesn't work. Trade the certainty for something less certain, but more responsive.
• How you want to work: Will the success of the team only be measured by the contribution to revenue, NPS, etc.? Can you enable the team to find the leading actions that will contribute to said metrics, and judge their success based on individual measurable changes in behavior?

Causation and Correlation in Lagging and Leading Indicators

While lagging indicators like revenue growth come with the downside of being difficult to change and slow to act on, they also come with a substantial upside: Certainty.

Because lagging indicators measure the efforts of the past, focussing on changing them comes with high certainty that you’re working on the right priorities. Tying actions to lagging indicators means that you are more likely to demonstrate that your efforts directly caused your results, even if this proof can only happen in hindsight.

By nature, leading indicators are less direct than those lagging indicators. Because they represent more tactical changes that are easier to make in the present, they may only correlate to, not cause, those lagging indicators’ future success.

In our example, the integrations team might arrive at leading indicators they could use to prioritize their day-to-day work that look like this:

Leading Lagging Indicators Outcome and Output Sequence and Difference

Trying to move a lagging indicator (e.g. revenue) ties your actions to a more absolute, non-negotiable result - But the metrics move much slower. Whereas working on a more responsive metric (ie. page views) can't be tied to changes of a "more important" metric like revenue. You trade feedback and responsiveness, for absolutism about the metric you work on.

But how did they get there?

Identifying the Right Leading Indicators
for Your Product

Swapping more certain lagging indicators for harder-to-measure but easier-to-respond-to leading indicators is crucial to creating an efficient  “build” cycle.

But those tactical changes don’t always have to be metrics within your product. Using a set of guiding questions to identify leading indicators can help you move in the right direction as a product team.

Leading and Lagging Indicators Guiding Questions

A crucial mind shift is to look beyond changes aimed at your users. Especially when you work on a product with insufficient quantitative data, considering actions and behaviors from stakeholders or team members can produce ideas for leading indicators much more quickly. A helpful lens for broadening your perspective beyond direct users is Impact Mapping and its ‘Adjacent Actors’ categorization.

Using Insights to Work Backward

From a product team’s perspective, the core idea is to work backward when trying to identify leading indicators to act on. Start by using metrics that might be lagging and are still in plain sight.

In our example, you don’t want to start with a customer upsell event, but something more tangible, like the active use of integration. It still ticks most of the boxes of a lagging indicator but is closer to the integrations team’s core actions and thereby more leading-ish.

Your team can now use the guiding questions to identify branches of leading indicators that match the criteria for leading indicators they are looking for.

The leading indicators you want to identify are

a) directly linkable to the team actions. 

b) predictors of future success (like the integration use, or ultimately, the customer upsell).

c) changing significantly throughout the goal cycle.

This diagram shows how you might work backward from a lagging indicator to discover leading indicators. The idea behind the different branches in the diagram is to give space to the various themes that might be behind several leading indicators,  which might drive the same lagging indicator.

For example, one branch could be focussed on the series of actions and behaviors that result from a marketing customer journey, whereas another mirrors the order of technical backend processes.

For our email platform integrations team, this exercise might lead them (pun intended) to a selection of possible leading indicators like this:

Identifying Product Management Leading Indicators by asking WHAT

This exercise provides a better overview of the different leading indicators and has more context about whether pursuing one of them matches a team’s capabilities. For example, the product team would want to focus on indicators that they have the most control over, as opposed to ones that are dependent on another team’s actions, which makes them lag very quickly.  The diagram mainly identifies the kind of metrics that could be used as a predictor of future success. It’s not about selecting and setting ambition levels, yet.

After choosing an indicator, you have to understand your customers, colleagues, or stakeholders’ main problem when executing that action. That’s the problem space that will inform the kind of solutions you want to validate and build—using your chosen leading indicators to measure your work’s success.

There are many different ways this could look and play out—depending on your product, team structure, and available data. The most important thing is that you stay close to the core intent of identifying directly influenceable metrics that change at a pace that allows you to course-correct within your goal cycle.

Adapting Leading Indicators to Outcome OKRs

Objectives and Key Results (OKRs) is one of the most popular frameworks to structure Product Goals. Using OKRs already poses many challenges for product teams that have to manage identifying their Product Strategy patterns or Product Discovery decisions as well. But the most common challenge is to choose Key Results that balance tasks or artifacts (ie. Output OKRs) with changes in behaviors that create results (ie. Outcome OKRs).

Comparing Output and Outcome OKR Examples

An often-used exercise to turn Output Key Results into more Outcome-ish ones is to ask “Why?”

“Do a Competitor Analysis!”

WHY?

“Create more app ideas.”

WHY?

“Drive the engagement of our mobile users.”

...and so on.

Leading and Lagging Indicators Matrix

But when also trying to capture Key Results that are more leading than lagging, it’s vital to add a second dimension. One that helps develop a shared understanding of how leading OR lagging your Output or Outcome Key Results might be.

Applying Guiding Questions for identifying Leading Indicators

The visualization above is meant to be a guide for you to move from one quadrant of potential Key Results to the other. This matrix doesn‘t offer a right-or-wrong perspective. Instead, it can serve as a tool that allows you to make informed choices about what kind of metrics work best for your team and your company to measure progress as you work. It will help you make trade-off decisions about the goals you want to achieve instead of blindly following a dogma.

What would this matrix look like after one of our integrations team’s Key Result ideation sessions?

From Lagging to Leading Indicator as a Product Team

As you can see, the team started with a set of leading but Output-oriented Key Results. To arrive at a more Outcome-oriented flight level for their Key Results, they used the question “WHY is this important?” to move up.

And while they technically identified an Outcome Key Result, it would have been only somewhat measurable at the end of a cycle. So the team members asked, “What actions do our customers have to do more of for us to succeed?” This conversation generated ideas for more leading-ish yet still Outcome-oriented Key Results.

This process won’t be as straightforward as in our example. But it illustrates the kind of thinking you can use to check what kind of Key Results you are discussing or measuring in your team and how to shift course—If you want to.

Moving beyond Outcomes ‘by the book’

Setting Outcome OKRs creates great benefits for Product Teams. They get more autonomy to pursue the exact solution to achieve the goal on their own, and they measure progress towards a result instead of ticking off tasks.

But Outcome OKRs do not automatically lead teams toward creating and measuring success. It’s entirely possible to define Key Results that describe a behavior change but isn’t measurable within and don’t change throughout a goal cycle. 

Therefore, teams need to be aware of whether they discuss Outputs or Outcomes as ideas for Key Results AND how leading or lagging these are.

After all, what’s the point of setting and measuring a goal that checks all the boxes of being an Outcome but doesn’t help you adjust your actions along the way?

After all, what’s the point of setting and measuring a goal that checks all the boxes of being an Outcome but doesn’t help you adjust your actions along the way?

Ultimately, the decision to focus on leading or lagging indicators and balancing Outputs and Outcomes shouldn’t just be the result of a colorful matrix. It should be guided by your individual OKR System and it should help you use OKRs as a framework for setting and measuring Product Goals in YOUR company.

Takeaway: Prioritize Leading Indicators to Avoid Lagging Decision-Making

Remember that leading indicators are a means and not an end. Listing as many leading indicators as possible won’t automatically create product success and can be a path toward getting distracted by vanity metrics. But they can be a useful lens to measure the direct impact of your actions as a product team instead of waiting for end-of-cycle feedback on whether you succeeded.

And please don’t treat this process as a siloed craft. Choosing indicators based on how responsive they are to your team’s actions can be incorporated into your existing goal-setting processes and frameworks like OKRs. Use leading indicators to enhance how you work today to avoid worrying about making decisions based on feedback that arrived too late to inform your work.