Planning Product Discovery

Marty Cagan argues that most discovery work needs little planning, but larger efforts such as multi-team initiatives call for deliberate framing before diving in. He describes two goals: aligning the team on the problem, target users and measures of success (tied to OKRs), and surfacing the biggest risks early. He warns that teams often gravitate toward comfortable risks like technology or usability, while neglecting value risk and a range of stakeholder risks such as financial, legal, brand and ethical concerns. Validation effort should be concentrated where significant risk exists or the team disagrees, rather than testing every assumption. He illustrates the point with the difficult problem of fake news on Facebook, where many non-technical risks shape the viable solution.

01Key takeaways

• Plan discovery deliberately for big projects and multi-team initiatives, but don't over-plan simple problems.
• Get the team aligned on the problem, the target customer, and how success will be measured, tied to OKRs.
• Deliberately surface value and stakeholder risks, not just the technology or usability risks teams prefer.
• Check with finance, legal, marketing, sales, partners and ethics early when a solution might affect them.
• Reserve intensive validation for risks that are significant or where team members disagree, and otherwise move to delivery.

02Key sections

When planning is worth the effort

Cagan notes that simple problems can move straight to delivery, while big projects and multi-team initiatives benefit from up-front planning. Discovery sprints suit only intense, short-deadline decisions.

Aligning the team

The first goal is shared clarity on the specific problem to solve, the users it serves, and how success will be measured, ideally linked directly to OKRs.

Identifying the big risks

Teams tend to focus on the risks they are most comfortable with, such as technology or usability, when value and stakeholder risks are often more important and harder to tackle.

Stakeholder and value risks

Cagan lists financial, business development, marketing, sales, legal and ethical risks, along with the core question of whether customers actually want the solved problem.

Where to spend discovery effort

When no significant risk is seen and the team agrees, proceeding to delivery is preferable to exhaustive testing; validation is reserved for real risks or disagreement.

The Facebook fake news example

A fake-news problem shows how questions about truth, free speech, culture, monetization and product vision shape solutions far beyond the machine-learning technology.

03From the post

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04Frameworks mentioned

Summary and takeaways written by PM Atlas; quotes are short excerpts. © the original author.