3.3 Planning with Assumptions & Discovery-Driven Planning

Instead of writing a long fixed business plan, the lean approach says: plan to learn, not to predict. At the start, everything is just a set of untested assumptions or hypotheses. Discovery-driven planning is a way to manage this uncertainty. You make your key assumptions explicit (about customers, pricing, costs, etc.) and then test them with experiments. Funding or time is released in small chunks as you hit milestones. In other words, you treat your startup as a series of short “sprints,” each designed to answer a question. You might, for example, assume people will pay $5/month for your app; that becomes a hypothesis to test with a signup page or survey.

Eric Ries emphasizes that every startup is a “grand experiment”. The questions aren’t “Can we build this?” but “Should we build it, and can it support a sustainable business?”. By starting with experiments, you get real data before investing too much. Using discovery-driven planning, you keep a lean “minimum roadmap”: identify what you must learn next, design a quick test to learn it, and then update your plan. This way you avoid wasting time on ideas customers don’t care about.

• Make assumptions explicit: Write down the critical unknowns in your idea (market size, price sensitivity, behavior, etc.). Recognize that initially these are guesses or hypotheses.
  
  

• Plan to test: Instead of a fixed multi-year plan, use a discovery-driven approach. Allocate resources in phases and only proceed when earlier tests succeed. This reduces risk because you’re not betting the farm on unproven ideas.
  
  

Startup as experiment: Remember Ries’s mantra: treat your startup like an experiment. You will “iterate inch by inch” toward answers. If a hypothesis is disproven, adjust (or pivot) rather than doggedly executing a bad plan.