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Product Planning with OKRs - Part 2

Part 1 - An introduction to Objectives & Key Results Part 2 - Using the Scientific Method Part 3
Product Planning with OKRs - Part 2
By Gannon Hall • Issue #4 • View online
Part 2 - Using the Scientific Method
Part 3 - Prioritization
Part 4 - Objectives as User Needs
Part 5 - Best Practices & Retrospectives

Part 2 - Using the Scientific Method
Product management is a science of experimentation and discovery. Early in our career, we learn that opinions, and in particular predictions about user behavior, are often wrong. It is a natural human instinct to assume that our rational assessment of a problem, based on our past experiences, will yield sound conclusions and represent the likely sentiment or behavior of others. But this is rarely true.
In reality, reliance on heuristics (the practice of using past experience to assess current circumstances) is no different then reliance on our biases.Cognitive bias is a systematic pattern of deviation from rationality in judgment. We create our own “subjective reality” from our perception of various inputs. Our subjective cognition of reality, not the objective input, dictates our opinions and the conclusions we draw. Thus, cognitive bias results in perceptual distortion, inaccurate judgment, illogical interpretation, or what can simply be called subjective irrationality.
A common misconception is that good product managers are gifted with “product instincts.” They have an innate ability to know what users want. This mystical ability doesn’t exist.
Like any other scientist, product managers must formulate a well-reasoned and well-researched hypothesis to solve a problem. And like a theoretical physicist, our ideas can only be proven through sound experiments and the objective analysis of empirical data.
Known as “The Scientific Method”, there is nothing innovative or novel about this approach. It has been in use since the 17th century by practitioners across a range of disciplines, from the social sciences to physics and mathematics. It is the standard process for the investigation of phenomena, acquiring new factual knowledge, or correcting previous assumptions. For a body of knowledge to be deemed scientific, to represent objective truth rather than subjective opinion, it must pass scrutiny based on empirical, quantifiable evidence subjected to well-established principles of scientific reasoning. Experiments are a procedure designed to apply scientific scrutiny to a hypothesis, resulting in factual, incontrovertible truth.
The method is a continuous process that begins with observations (e.g. user studies, user experience research, live experiments, etc.). Based on these inputs, product managers develop ideas about how to address a user need. A strong hypothesis can be thought of as a well-reasoned prediction that can be tested and validated.
But not every solution hypothesis can be empirically validated. While some hypotheses can be proven by carefully controlled experiments that gather empirical data, depending on how well additional tests match the predictions, the original hypothesis may require refinement, alteration, expansion or even rejection.
The following diagram helps to illustrate the process of validating a product hypothesis:
Blackstar – Medium
Blackstar Consulting
  1. BASIC ASSUMPTIONS: Validation of basic assumptions is presupposed (the outcome of ideation exercises)
  2. SOLUTION HYPOTHESIS: A proposed solution to a user need or problem based on information inputs
  3. INFORMATION INPUTS: Includes existing data and observable user behavior, user feedback, intuitive hunches, or the results of related studies or competitive products
  4. DATA INPUTS: Quantifiable measurements and observations subjected to systematized statistical scrutiny
  5. DISPROVEN HYPOTHESIS: A disproven solution hypothesis is often the result of incorrect assumptions about user motivation and behavior
  6. ITERATIONS AND IMPROVEMENT: Technology and user needs are constantly evolving; a solution that serves those needs must also evolve
Thanks for reading. In Part 3 we’ll look at prioritization.
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Gannon Hall

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Gannon Hall, 1856 Green Street, #3, San Francisco, CA 94123