Take a look at your product metrics. If your biggest success metric is "we shipped it," you might be managing activity, not impact. And guess what? Your customers can tell, I promise you.
Most roadmaps don't fail. They just succeed at the wrong thing.
I'm Lance Dacy, otherwise known as Big Agile, and today we're going to kick off the week with a reset a lot of teams need in 2026: stop shipping features, start proving outcomes.
We learned this in Scrum training. Stop starting, start finishing. You hear it in Kanban and any kind of agile process. But we're going to take it a level up to the business. In the next few minutes, we'll talk about how to translate that into better things you can do at your organization.
We're going to cover how well-intentioned leaders accidentally create feature factories. We see it all the time. What is the data out there saying about high-performing organizations in 2026? I'll give you two real-world examples where I see this happen quite a bit, a B2B product and an internal one. And then a simple weekly ritual that I like to call an outcome review that actually helps teams reset without chaos.
This is not about blame. Change is hard. If this were easy, everybody would be doing it. I'm simply trying to help and call to focus some of the problems we see in product development. This is not chastising you. I'm here to help.
Why Feature Factories Keep Showing Up
Let's talk about feature factories. They're not good. We don't want to organize our product development that way. So why do feature factories keep showing up? We want learning factories, not feature factories.
Most leaders do not wake up and say, "Today I'm going to destroy learning." But they're certainly not waking up going, "We need to learn more." Most organizations don't do that.
Feature factories usually come from good intentions paired with old habits. I'm talking about habits from 150 years or more of building things at scale. Here's what I see over and over again. I don't always claim to be the expert. I just claim to have a lot of scar tissue. I work with a lot of organizations, I see a lot of things, and this is what I see over and over and over again.
Roadmaps tend to be treated as commitments instead of hypotheses, which is what we really want. Success is typically measured by delivery dates and budget, not customer behavior. Teams are rewarded for finishing work, not necessarily learning from it. And leaders ask, "Did we ship this?" instead of "Did it change anything?"
It starts with the leaders, even product management leaders.
Over time, what that builds out is teams actually stop asking why. They used to push back and say, "Why are we doing these things?" But we start teaching the teams to optimize for throughput of features, not the impact of those features. And now you have nobody pushing back on that.
The irony is this: it feels productive. Lots of motion, lots of things happening, lots of output. But there's very little proof.
What the Data Says About Real Performance
Let's talk about what the data says about real performance, because we're getting better and better at tracking these things. I still like the 2024 DORA research, and I think it still makes it perfectly clear.
High-performing organizations do not win by shipping more features faster. That's a myth.
What they win by is tight feedback loops, clear problem framing, fast learning when bets are failing, and leadership behaviors that reward evidence over optimism.
DORA even expanded its model to include organizational success factors, sometimes referred to as DORA plus one. That is showing that delivery performance alone is not enough. Outcomes come from how leaders shape the systems, not just how teams execute inside the systems.
If you want credibility in 2026, you need evidence of impact, not just a release calendar that you publish. You can look at those metrics at dora.dev and their research articles for more on that.
Example One: The B2B SaaS Reporting Dashboard
Let me show you how I see this play out. Example number one is from a SaaS product I've worked with a lot, a B2B SaaS product.
The B2B team I worked with shipped a highly requested reporting dashboard. Everybody wants reporting. It was on time, it was polished, it looked good, and sales loved it. When we showed it to them in the demo, they said, "Oh yeah, this is going to sell like hotcakes."
Three months later, you go look at the adoption of that reporting dashboard. It was under 20%. Support tickets had actually increased, and customers were still exporting the data. They went back to spreadsheets.
What was going on there that caused the customers to do that?
The feature itself was not wrong. We needed some kind of reporting tool. But the assumptions of how they would use that feature was wrong. No one had defined the outcome as "customer can complete analysis without exporting." We should have just focused on that. But what they did do is measure completion, not behavior change.
Once they reframed the outcome, the product team did a great job of this. They started reframing the outcome. Then the next iteration was smaller, messier, and wildly more effective because we were grappling with what it means that they don't do analysis outside spreadsheets. So we had to go talk to customers. Imagine that.
Example Two: The Internal Provisioning Platform
Another example I have is an internal platform team that was building provisioning tools. Leadership demanded faster self-service provisioning for the marketing team. The developers took down all the features. Check, we delivered it.
What did not change? Marketing still bypassed the tool. Manual requests stayed flat. Trust in the platform did not improve.
Why?
Because the outcome was never "portal shipped." The real outcome was: did the marketers choose to use the new provisioning platform without being forced?
Nobody really wants to use anything they're forced to do. We built it for them. We thought we were building all the features for it. But nobody really stepped back and said, "What is it that we really want to see? What's the behavior change?"
Once the leadership acknowledged that, the work shifted from features to friction removal for marketing. And adoption soon followed because we were building tools that limited friction in the workflow.
Leaders, it starts with us.
How to Reset Without Chaos
How can we reset without having a whole lot of chaos? Here's the key move in my opinion: you want to separate delivery from learning. If we put both of those together, you're going to have a hard time.
Shipping is not bad. We want to definitely be efficient and fast at shipping things out the door. But shipping without evidence is bad.
That is why I coach leaders to do little things like run a simple weekly ritual. I call it the outcome review. You can come up with a better name for that. This is not a status meeting, by the way. This is not a working demo. It's not a blame session. It's a learning loop. You start demonstrating this as a leader and baking it into the organization's behavior.
The Weekly Outcome Review Ritual
The time box for this thing is typically 30 minutes. Obviously when you first start, it can be longer. And I want leaders to only ask these questions:
What problem did we believe we were solving? What behavior did we expect to change? What evidence do we actually have? What surprised us? And what is the smallest next bet that we would place now?
When bets fail, and they will, take note of that. The leader's job is to protect learning, not punish honesty. That's where we all too often go, asking "Why did that happen?" and pointing fingers.
Psychological safety does not mean lowering standards. It means making it safe to tell the truth early.
Remember what I keep saying about problems: solving them earlier is always typically less expensive than learning late.
Your Roadmap Reality Check
In closing, I want you to look at your roadmap. If your roadmap is full but your confidence is still low, if your teams are busy doing a whole bunch of stuff but your customers are no better off, if you feel like you're shipping a lot and you do pretty good at that but you're proving very little to anyone this week, stop.
Stop asking for more features.
Step back and start asking: what outcomes can we stand behind?
Run the outcome review. Collect the evidence. Make smaller bets and hypotheses. Learn faster. We all know breaking the work down is what we want to do.
Follow along this week because we are going to dig deeper into those metrics you can track and how to keep those reviews safe when the data says the bet failed.
Leaders, it starts with us.
Ready to transform how your teams deliver real customer value?Explore Big Agile's training courses to build the leadership mindset and practical skills that turn feature factories into learning organizations.