May 17, 2023
Our focus on intelligent experiences is a reaction to both increasing customer expectations and the possibilities afforded by new technologies. But how does an organization start building these data-powered experiences and deliver the new era of intelligence?
For us, it’s down to the product team and its specific focus on outcomes rather than features.
Agile was a reaction to protracted software development projects that taught us how to ship working software faster. Interaction design was a reaction to software being cumbersome to use. It taught us how to make software more usable and desirable.
Product management was forged a decade later, as a reaction to unsuccessful software projects that didn't achieve their intended outcomes. It is largely the art of achieving outcomes with technology.
Many product teams set up as if every idea they adopt is going to work the first time. They exclusively work on big features and celebrate shipping software. Their teams have little incentive to measure results, as they’re always moving onto the next project.
We must remember Marty Cagan’s "two inconvenient truths of product management":
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Half of our ideas aren’t going to work.
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Even ideas that do have potential take several iterations to work.
High performing product teams prioritize achieving outcomes, not shipping. They build intelligent experiences. They know the rate at which they learn determines their effectiveness in the long run.
5 Tips for product teams
1. Win an outcome remit
Successful product teams clearly define the outcome they’re trying to achieve. They take the time to agree and communicate this with their stakeholders. Then they barter accountability for the freedom to choose how they approach tackling that outcome.
2. Practice Product Kata: Be comfortable with the 3 forms of execution
Product teams with a project mindset lose flexibility over time. Soon the only thing they can do effectively is build big features. Instead, teams need to get into a mindset of continuous improvement.
Melissa Perri coined the term "Product Kata.” The process is simple: A team’s agreed business outcome sets the direction for the team and forms our strategic intent. The team must then assess the current state and what problems they can address to tackle the challenge from a product perspective. Then they must identify the next most valuable step toward that goal.
Product teams need to be flexible and comfortable operating in three different modes:
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Problem exploration (research)
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Solution exploration (building features and prototypes)
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Solution optimization (experimentation and incremental improvements)
3. Choose metrics carefully
Successful product teams can generate clear hypotheses, or proposals for how they’ll influence their agreed business outcome. They understand the assumptions included in their hypothesis and they find fast ways to test them. They identify the metrics that will help them test and track progress.
Most business outcomes are lagging metrics (e.g., customer churn) but the best product metrics are leading. Teams should be able to quickly understand if changes they’ve made are getting them closer to the desired business outcome. For that reason, it’s also important that metrics are tractable (the team can influence them through product changes).
When you’re identifying and sharing success metrics, less is often more. Keep them simple and meaningful. Don’t just choose the metrics that are easy to measure. Many vanity metrics are easy to measure but not strategically meaningful.
Consider using guardrail metrics or anti-goals to check that you’re not over-optimizing for the metric you’re trying to move.
4. Keep learning loops tight
What you learn must influence what you do, or else you’re not learning. Established companies have a slow heartbeat. They tend to react over quarters and years. Product teams need to move faster. Don’t outsource product analytics to an insights team, presenting findings to leadership at quarterly meetings is too slow.
Embed data expertise in your product teams to create faster learning loops. Teams should adjust their approach weekly, having reviewed the latest research, experiment results and analytics.
The best product teams can accelerate their learning beyond the weekly Product Kata. Recommendations and personalization are a good example of automating the learning process. Models can be updated with fresh data hourly and retrained daily. User behavior data drives better recommendations over time. Such models aren’t ‘set and forget’ though. Product teams need to constantly review their performance and effectiveness.
5. Liberate data
Product teams can also help other teams learn faster, through the gift of data. Exhaust data from your product could have transformational value to another team in your organization.
Keep your head up and give the gift of data back to your organization when you can.
The best teams have a clear outcome and track their progress towards it. Win the outcome remit, practice Product Kata, choose metrics carefully, keep learning loops tight and liberate data beyond your team.
