This lesson teaches innovators how to prioritize assumptions to form well-crafted hypotheses, guiding experiments that yield the most impactful insights. Doing so reduces risk and waste while maximizing learning and confidence.
Skills: [Assumption Prioritization] [Risk Assessment] [Hypothesis Development] [Experiment Design] [Mission Alignment] [Iterative Learning] [Data-Driven Decision Making]
Time of lesson: 7 min 45 sec
Overview:
Imagine you’re working on an app that helps people track their water intake. Before diving in, your leader asks, “What’s your highest-priority assumption?” You realize your assumption is that users will actually take time to log each glass of water they drink. Instead of guessing, you form a hypothesis: “If users value hydration tracking, then they’ll engage daily.”
You design a simple experiment—a basic app prototype—to measure engagement over a week. This quick test confirms that users need automated tracking, not manual input. By prioritizing the right assumption, you’ve saved time and resources and avoided a costly misstep. 🚰🔬
Key Concepts Covered:
- Identifying Core Assumptions: How to determine which assumptions are fundamental to the success of the innovation and align with the mission.
- Assessing Risk and Impact: Evaluating the potential risks of each assumption and its impact on the project’s success to prioritize the most critical ones.
- Hypothesis Formation: Crafting clear hypotheses from prioritized assumptions to run effective experiments that validate or invalidate key beliefs.
- Experiment Alignment: Ensuring experiments are structured to fit within organizational constraints and resource availability.
- Learning and Adaptation: Using experimental outcomes to inform the next steps, build trust, and make data-driven decisions about pivots or next iterations.
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Want to learn more?:
Check out these resources!
- “Innovation Risk: How to Make Smarter Decisions” by Harvard Business Review - This article discusses how to use risk as a factor in prioritizing assumptions. It explains how leaders and teams can focus on high-impact areas, testing the riskiest assumptions first to inform decision-making and adjust their approach based on experimental outcomes.
- "How to Use Multiple Prioritization Frameworks" by ProductPlan - This guide on assumption mapping helps innovators identify and prioritize assumptions based on risk and potential impact. This resource offers a practical framework to ensure experiments are focused on the most critical assumptions, maximizing learning while minimizing resource use.
About the instructor: 
Jeff “Smoker” Adling enlisted in the Air Force in 2002 from Dallas, Texas, and later earned a commission through Officer Training School. Over the course of his diverse career, he held key roles as a communications technician, logistics officer, inspector general, and special operations pilot with over 2,000 flying hours in remotely piloted and nonstandard aircraft. As a Lean/Six Sigma Black Belt, he channeled his passion for organizational behavior and problem-solving into unlocking the potential of diverse teams, addressing even the most challenging issues. He is also an experienced innovation coach, utilizing the science of storytelling to empower Airmen in advocating for their solutions.
Prior to joining the Productable team, Jeff was the Master Process Officer for Air Force Special Operations Command, spearheading continuous improvement and innovation throughout AFSOC. He is currently pursuing a Doctorate of Business Administration from The University of Florida and spends his free time perfecting his photography.