For years, product teams have been told to focus on outcomes, not outputs.
Yet product teams in most organizations—even those with mature Agile and DevOps practices—still measure success by how much they deliver, not by what difference it makes.
Velocity charts improve. Roadmaps fill up. Releases go out the door. But the most critical question remains unanswered:
“Did any of this actually have an impact?”
This gap between what we do and what we achieve is exactly what product thought leader Matt Lemay calls out in his latest book, Impact First Product Teams. And it’s also the gap that ValueOps Insights was built to close—by making outcomes measurable, traceable, and predictable.
Now, as AI transforms how we build software, this shift has never been more urgent. When development cycles compress from months to days, and generative tools can deliver “working code” in hours, the question is no longer “Can we build it fast enough?”—it’s “Can we ensure it delivers the right value?”
Shipping software is easy to measure; creating impact is not.
Teams count stories completed, deployments made, and tickets closed. These are tangible, trackable numbers that say little about whether customers are actually more successful or whether business outcomes have improved.
Teams fall into what Matt Lemay calls the “output trap”—mistaking motion for meaning. They celebrate throughput instead of transformation.
Here are some of the most common symptoms of output-driven cultures:
AI now risks magnifying this trap. As generative coding tools accelerate output, the temptation to celebrate “more” will grow stronger. But speed without direction just leads you to the wrong place faster.
That’s why Matt’s message—put impact at the center—matters more today than ever before.
This all begs the question: How do we measure success of our product team based on the outcomes we achieve?
In Impact First Product Teams, Matt lays out a pragmatic path to refocus teams around impact—not intention, not effort, but evidence of real-world change. Here are some key principles of this approach:
Before committing to any feature, teams must clearly define what change they expect to create—for users or for the business.
AI can generate code in minutes, but only humans can define why that code matters.
Impact-first thinking isn’t the responsibility of product managers alone. It’s a shared contract across all functions. Everyone—from engineering to leadership—must know how success will be measured. In his book, Matt proposes the following model for how impact-first product teams can take responsibility for everything from delivery (output) to realization (impact):
Every release is an experiment, not a finish line. AI enables faster experimentation—but it’s still up to teams to close the loop, learn, and adapt based on what actually works.
Impact-first teams rely on data—not to report activity, but to learn from outcomes. They integrate delivery data, usage analytics, and customer feedback to continuously validate that the work is creating value.
It’s easy to talk about outcomes; it’s hard to measure them. Further, it’s harder still to connect outcomes to the messy, cross-functional reality of modern software delivery.
Here are just a few of the challenges:
This is where ValueOps Insights comes in. ValueOps Insights is a unified intelligence layer that connects strategic intent, execution, and impact realization across your digital ecosystem.
ValueOps Insights operationalizes the “impact-first” philosophy by connecting the why, what, and what happened across strategy and delivery—using real data, in real time.
Start by identifying your lagging outcomes—the measures that define real success:
These outcomes form the “North Star” layer within ValueOps Insights.
Next, define measurable leading indicators (LI) that signal progress toward outcomes. Using historical data, and machine learning techniques, ValueOps Insights automatically calculates the targets for LIs (based on mapped outcome targets), as well as the lead time between LIs and outcomes.
Here are some examples of how these capabilities can be applied:
ValueOps Insights connects these indicators to lagging outcomes, revealing which early signals predict success—or risk—before results show up in the lagging data.
ValueOps Insights enables integrations across a variety of tools, such as:
The result: one continuous view of how strategy turns into impact.
ValueOps Insights applies analytics and AI-driven modeling to generate predictive risk scores for each outcome.
By monitoring the variance between actuals and targets across leading indicators, the system highlights:
This represents proactive assurance—not reactive reporting. See the screenshot below, which provides an example of how ValueOps Insights uses leading indicators to predict business outcome confidence.
|
Phase |
Impact-first principle (Matt Lemay) |
ValueOps Insights capability |
|
Define intent |
Start with the change you want to create |
Define and track lagging outcome metrics |
|
Form hypothesis |
Treat delivery as an experiment |
Map initiatives and features to measurable hypotheses; identify leading indicators that measure impact across flow, adoption, and sentiment; set tactical goals for leading indicators based on lagging outcome targets |
|
Execute and measure |
Use data to learn, not just report |
Continuously track leading indicators against their goals |
|
Adjust and predict |
Iterate based on evidence |
Use leading indicators to predict confidence of achieving outcomes, and adjust and optimize based on those predictions |
Together, these capabilities form a closed learning loop—one in which delivery is guided by data, and impact is visible long before it becomes financial.
In the age of AI, the rules of product development are being rewritten.
AI has already shrunk the time between idea and delivery. Code generation, test automation, and intelligent design tools allow teams to move from concept to release in a fraction of the time it once took.
But this speed introduces a new problem: If you can build faster, you can also fail faster—unless you can learn faster.
The new challenge isn’t delivery—it’s discernment.
When features can be created in hours, the differentiator isn’t execution speed—it’s knowing which ideas are worth executing at all.
That means real-time outcome measurement becomes critical. As AI collapses development cycles, it also compresses feedback cycles—meaning teams must be ready to measure and interpret impact much more rapidly.
Without a clear, continuous connection between outputs, outcomes, and value, organizations risk drowning in AI-generated work that delivers no meaningful return.
In other words: AI accelerates the “how fast”—but only outcome measurement determines “how well.”
That’s why the fusion of impact-first thinking and ValueOps Insights’ predictive intelligence is so powerful right now.
AI makes it possible to move faster than ever—but ValueOps Insights ensures that every step taken actually moves you closer to your goals.
|
Old world (output-driven) |
New world (impact-first + AI-enabled) |
|
Success = Delivering scope |
Success = Delivering measurable change |
|
Metrics = Velocity, throughput |
Metrics = Adoption, engagement, ROI |
|
Feedback = Lagging and static |
Feedback = Continuous and predictive |
|
Delivery = Manual and slow |
Delivery = AI-accelerated and data-informed |
|
Decisions = Opinion-driven |
Decisions = Evidence-based and outcome-linked |
When Matt Lemay’s Impact-First mindset meets ValueOps Insights’ outcome assurance platform, organizations can finally translate the speed of AI into sustained, measurable value.
You get the best of both worlds:
To learn more about this new approach, please register for our joint webinar on this subject. This session will feature Matt Lemay, author of Impact First Product Teams, and the ValueOps Insights team.
In this webinar, you’ll learn:
AI is making it easier than ever to build software. But building software was never the goal—making an impact was.
As Matt Lemay reminds us, “Impact isn’t a byproduct of great products; it’s their purpose.”
With ValueOps Insights, you can now make that purpose measurable, actionable, and predictable—even at AI speed.
Because in this new era, success isn’t about building faster—it’s about learning faster, adapting smarter, and realizing value sooner with greater confidence.
If you’re an existing Rally customer, you can check out ValueOps Insights by clicking the appropriate links below and entering your credentials:
If you reside in USA/APAC: vsi.rallydev.com
If you reside in the EU: vsi-eu.rallydev.com
If you’re not an existing Rally customer, please contact us to set up a trial.