Success in Agile portfolios often hinges on how well you navigate uncertainty. Traditional delivery metrics — velocity, burn-down charts, release frequency — might tell you whether the team is busy, but they don’t necessarily reveal if you’re making real progress toward strategic objectives. That’s where leading indicators come into play. These are the early, directional signals that suggest whether things are on track before the final results roll in. They don’t give you all the answers, but they nudge you toward asking the right questions—early enough to adjust course if needed.
Think of it like hiking through a foggy wilderness. The map represents your strategy, but leading indicators are the landmarks that assure you you’re heading the right way. Without them, it’s too easy to keep walking until you realize you’re miles off course. In Agile portfolios, this can look like delivering feature after feature, only to discover they don’t actually move the needle on business outcomes.
The challenge is that leading indicators are less obvious than traditional metrics. They’re not about finished work; they’re about patterns and signals that show how your efforts align with the bigger picture. Take customer engagement, for example. Rather than waiting to measure success by revenue after a release, you might track how many users explore an early version of a feature or engage with a prototype. It’s a sign that your solution is resonating before you’ve invested full-scale development effort.
Different portfolios require different indicators, though, which means there’s no universal, one-size-fits-all list. For teams working on innovative or complex initiatives, indicators often revolve around learning milestones. Did you validate the riskiest assumption yet? Are early adopters interested? Are there clear signals that this idea will scale? These are subtle but important measures of whether an initiative is strategically viable.
On the flip side, more operational-focused portfolios—where systems need to be efficient and scalable—might look at indicators like system uptime as teams roll out infrastructure optimizations or the pace of incident resolution. These forward-looking metrics act as early warning signs for whether the technical foundation you’re laying supports the organization’s ability to deliver value over time.
The real art lies in connecting these indicators to broader strategic goals. Too often, portfolios lose sight of why the work exists in the first place. They get mired in execution—hitting sprint targets, checking off epics, and cranking out velocity numbers. Valuable metrics? Sure. But if those measures don’t tie back to how your efforts are advancing a bigger business objective, they risk being irrelevant—or even misleading. When choosing leading indicators, start by asking: What are we trying to achieve at a strategic level? And how would we know, early on, that we’re headed in the right direction?
Here’s an example that always sticks with me. A team I worked with in the banking sector needed to increase customer retention. But their first instinct was to track internal metrics like completion rates on product enhancements. While those were great for monitoring team productivity, they were terrible at showing whether customers actually stuck around. After a lot of messy conversations, we shifted focus to an early indicator: user adoption of a specific set of loyalty features. That allowed them to pivot much sooner and test which interventions engaged customers enough to keep them loyal.
But there’s a flip side to all this: obsessing over indicators without clarity on why they matter. Leading indicators are only valuable if they come with the right context. Without that, they’re just numbers on a dashboard, giving whoever looks at them something to argue about. The process of defining indicators should include leadership, teams, and key stakeholders, so everyone gets aligned on the “why” behind what you’re measuring.
Once the right leading indicators are identified, they’re not static. Agile environments are inherently dynamic. Markets shift, priorities change, and even the best strategy evolves. If an indicator stops providing meaningful insights, it’s time to retire it and replace it with something more relevant. This is where frequent check-ins with stakeholders become invaluable. By routinely asking, “Is this still the best way to measure whether we’re making progress?” teams can avoid getting stuck chasing metrics that have outlived their purpose.
Sometimes, leading indicators reveal uncomfortable truths. They might point to slow adoption of a product feature, resistance from key users, or technical dependencies that could derail timelines. It’s tempting to dismiss these signals as noise, especially when the team feels pressure to show quick wins. But ignoring early-warning signs often leads to expensive course corrections later. Leaders need to create a culture where these indicators spark curiosity, not defensiveness. “What’s this data telling us? What do we need to learn here?” are the kinds of questions that encourage teams to act on insights, not shy away from them.
Now, here’s the catch: relying solely on leading indicators is also a trap. They’re directional, not definitive. They help shine a light on where things might be headed, but they’re not infallible. Balancing them with lagging indicators—those traditional metrics like customer revenue growth, defect rates, or time-to-market—creates a more complete picture of progress. Think of it as steering with both the rearview mirror and the windshield. You need to see the bumps coming but also understand what you just drove through.
In addition to balance, simplicity is critical. I’ve walked into more portfolio meetings than I can count where dashboards were overloaded with dozens of metrics, most of which weren’t actionable. Teams and leadership got stuck debating what mattered most, and nothing moved forward. Good leading indicators are few in number and crystal clear in intent. If you have to spend more time explaining the metric than acting on what it tells you, it’s time to simplify.
For organizations navigating areas of high uncertainty, one strategy I recommend is using shorter learning cycles to refine leading indicators. Treat them like hypotheses. For example: “We believe early user engagement will predict the adoption of this feature.” Then test that hypothesis quickly. If feedback doesn’t align with the expected result, either the indicator is off, or the hypothesis needs adjusting. The tighter the feedback loop, the quicker teams can course-correct without wasting effort.
It’s also worth pointing out how cross-team collaboration amplifies the value of leading indicators. A single team might surface a key metric—say, the number of integrations completed on a critical system—but unless the rest of the portfolio sees how that metric ties to progress at a strategic level, it’s just noise. Establishing regular alignment sessions where teams compare insights ensures the broader portfolio benefits from shared learning. This avoids siloed efforts and keeps everyone rowing in the same direction.
Leadership plays an outsized role here. If leaders only focus on delivering “outputs,” such as features delivered per sprint, it trickles down and narrows team focus. But when leadership embraces curiosity around progress toward outcomes—like how an enabler feature is reducing onboarding friction or improving time-to-value—it sets the tone for how teams prioritize their work. When outcomes are celebrated over raw productivity, teams start seeing metrics like leading indicators as enablers of smarter decisions, not just boxes to check.
At the heart of all this is trust. Teams need to feel they can surface leading indicators honestly, even if the data suggests trouble or complexity. Leaders, in turn, must resist the urge to micromanage or overreact when metrics uncover potential challenges. Instead, leading indicators should serve as a flashlight—helping you see what’s ahead, adjust your path, and maintain momentum toward your strategic goals.
The beauty of leading indicators is that they remind us Agile isn’t about blind execution. It’s about learning, adapting, and connecting our actions to bigger outcomes. The ability to measure progress in real-time, while maintaining alignment with strategic goals, isn’t just a technical skill—it’s an organizational habit. Done well, it doesn’t just guide delivery; it builds confidence that the work we’re doing truly matters.
