Instead of complex prioritization frameworks like RICE, designers can use a more intuitive model based on Value, Cost, and Risk. This mirrors the mental calculation humans use for everyday decisions, allowing for a more holistic and natural conversation about project trade-offs.
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To de-risk innovation, teams must avoid the trap of building easy foundational parts (the "pedestal") first. Drawing on Alphabet X's model, they should instead tackle the hardest, most uncertain challenge (the "monkey"). If the core problem is unsolvable, the pedestal is worthless.
Not all design impact can be quantified with metrics. When data is unavailable, frame your value by highlighting contributions to competitive parity, internal team efficiency, or bug reduction. This holistic view of business health resonates with leadership beyond just product managers.
Allocate 50% of your roadmap to core functionality ('low delight'), 40% to features blending function and emotion ('deep delight'), and 10% to purely joyful features ('surface delight'). This model ensures you deliver core value while strategically investing in a superior user experience.
To get product management buy-in for technical initiatives like refactoring or scaling, engineering leadership is responsible for translating the work into clear business or customer value. Instead of just stating the technical need, explain how it enables faster feature development or access to a larger customer base.
Effective, fast research isn't about skipping steps but about rightsizing the effort. Instead of defaulting to a previous method like "10 interviews," teams should determine the minimum insight needed to mitigate the specific risk at hand, using that to define the research scope and approach.
Organizations suffer from an excess of priorities, a modern phenomenon since the word was originally singular. To restore focus, use the "hell yes" test: if a new initiative doesn't elicit an enthusiastic "hell yes" from stakeholders, it's not a true priority and should be dropped or postponed.
To find valuable AI use cases, start with projects that save time (efficiency gains). Next, focus on improving the quality of existing outputs. Finally, pursue entirely new capabilities that were previously impossible, creating a roadmap from immediate to transformative value.
To build a successful product, prioritize roadmap capacity using the "50/40/10" rule: 50% for "low delight" (essential functionality), 40% for "deep delight" (blending function and emotion), and only 10% for "surface delight" (aesthetic touches). This structure ensures a solid base while strategically investing in differentiation.
Before starting a project, ask the team to imagine it has failed and write a story explaining why. This exercise in 'time travel' bypasses optimism bias and surfaces critical operational risks, resource gaps, and flawed assumptions that would otherwise be missed until it's too late.
When teams constantly struggle with prioritization, the root cause isn't poor backlog management. It's a failure of upstream strategic filters like market segmentation, pricing, and product discovery. Without these filters, the feature list becomes an unmanageable mess of competing demands.
