Avoid philosophical debates about uncertainty and experimental approaches. Instead, identify what the organization clearly wants to achieve—outcomes that keep coming up in product strategy, vision discussions, and understanding users. There's always inherent uncertainty about exactly how to deliver these outcomes, but there's also tremendous desire to find out. This creates space for experimentation.
Example
When product teams identify something as really important but cannot concretely describe exactly what to build in tech, focus there. Structure your recommendation around what you know with certainty, what data and information backs up your suggestion, and what specifically you don't know. Promise to deliver valuable insight rather than complete solutions. The deliverable becomes concrete knowledge that helps move forward, even if it doesn't totally answer everything. This approach works when there's already acknowledgement of complexity—outside that space, you'll face endless debate.
Context
This requires picking your battles. You cannot lead people who fundamentally refuse the premise that some uncertainty is acceptable. Facilitation requires consent. Look for the smallest bit of consent you can work with—something the person or organization is willing to try. When there isn't friction and you can facilitate, the actual work becomes the hardest part because you're uncertain too, experimenting alongside everyone else.
When This Might Not Apply
– Organizations demanding complete certainty and measurable metrics before any experimentation—philosophical debates consume all energy. – When no shared outcomes exist across leadership, product, and engineering—uncertainty framing fails without common ground.
Variations
– For remote sessions, use strategy canvases to visualize shared outcomes before proposing experiments. – When working with executives, tie outcomes directly to revenue streams or user value in 15-minute pitches.
