How do you prioritize your product's core assumptions and hypotheses?

I have found assumptions fascinating in how they drive product vision. Assumptions are accepted as true without proof based on prior knowledge, while hypotheses are testable propositions. Both help in prioritizing product vision. Make sure your vision incorporates these defined concepts and explain why. Assumptions provide foundational beliefs that shape the direction and goals of the product. Therefore, as a product manager, it is crucial to take the right direction in making assumptions.

Key: Prioritize assumptions and hypotheses based on impact and evidence. ?? Identify critical assumptions for your product's success. ?? Rank them by potential impact if proven false. ?? Gather evidence to support or refute each one. ?? Prioritize testing those with high impact and low evidence. ?? Adapt your product strategy based on test results.

Assumptions: These are beliefs or statements taken for granted or accepted as true without proof. In the context of product development, assumptions are the underlying beliefs about your target users, market, or problem that inform your product strategy. Hypotheses: These are educated guesses or proposed explanations for a phenomenon, often based on limited evidence. In product development, hypotheses are statements that articulate what you expect to be true about your product or its impact on users.

To prioritize your product's core assumptions and hypotheses, start by defining them clearly. Assumptions are beliefs taken for granted without proof, while hypotheses are testable propositions. This distinction is crucial for a solid product vision. ?? Next, use an impact-uncertainty matrix. Rate each assumption and hypothesis on its potential impact and level of uncertainty. Focus on those with high impact and high uncertainty first, as these can significantly influence your product's success. ?? Finally, conduct experiments to test these prioritized assumptions and hypotheses. Use feedback and data to validate or invalidate them, iterating based on your findings. This approach ensures a data-driven and resilient product vision. ??

Both assumptions and hypotheses pose risks to your product vision. It is crucial to mitigate these risks promptly. In my experience, gathering data and evidence early on to support them strengthens the product vision. For instance, consider an assumption based on past experiences outlined in the product vision; by addressing it early with supporting data, the product vision gains greater alignment and approval from stakeholders.

Prioritizing assumptions and hypotheses helps focus limited resources on testing the most critical aspects of your product concept. It ensures that efforts are directed towards validating or invalidating the key assumptions that underpin your product's success.

Prioritizing assumptions and hypotheses helps focus limited resources on the most impactful and uncertain areas. ?? This reduces the risk of building unwanted features and increases the chances of product success. Addressing key assumptions early validates your vision and aligns with customer needs. ??

Use criteria such as impact, uncertainty, and dependencies to prioritize assumptions and hypotheses. Impact refers to the potential effect on the success of your product; uncertainty reflects the level of unknowns or risks associated with an assumption or hypothesis, and dependencies highlight the interconnectedness between different assumptions or hypotheses. Another approach is to conduct user research or market analysis to gather data that informs the prioritization process. Feedback from potential users or experts can help identify which assumptions are most crucial to validate first.

Use an impact-uncertainty matrix to prioritize assumptions and hypotheses. ?? Rate each one based on its potential impact on your product's success and the level of uncertainty. Focus on those in the high impact/high uncertainty quadrant first, as these pose the greatest risk and opportunity. ??

Matrix give structure to your ideas. For Assumptions and Hypothesis these are much more helpful. First, think about the big assumptions and ideas behind your plan. Then, rate each one based on how important and how uncertain it is, using things like customer feedback or market trends. Next, put each assumption or idea on the matrix based on its rating. Finally, look at the ones in the high importance/high uncertainty part of the matrix – those are the ones you really need to check out first.

A prioritization matrix, such as an Impact-Uncertainty Matrix or a Dependency Matrix, can help visualize and prioritize assumptions and hypotheses. In an Impact-Uncertainty Matrix, assumptions or hypotheses are plotted based on their impact and uncertainty levels, while in a Dependency Matrix, you map out the interdependencies between different assumptions or hypotheses.

To use the matrix, brainstorm assumptions and hypotheses, rate them on impact and uncertainty, and plot them on the matrix. ?? Analyze the high impact/high uncertainty items and prioritize them for testing. This structured approach ensures you address the most critical areas first. ???

Make sure the Experiments are designed well as per my experience. Develop experiments tailored to each prioritized assumption or hypothesis. Consider the type of experiment—qualitative or quantitative, low or high fidelity—and choose the most appropriate method based on your goals, resources, and constraints. Analyze the collected data to evaluate the validity of your assumptions and hypotheses. Look for patterns, trends, and insights that emerge from the experiments. Assess whether the evidence supports or refutes your initial assumptions, and use this information to iterate on your product vision accordingly.

Develop experiments or tests that allow you to gather data to validate or invalidate your assumptions and hypotheses. These tests can range from user interviews and surveys to prototype testing and A/B testing. The goal is to gather evidence that either confirms or challenges your initial beliefs.

Yes we can prioritise on both like assumptions on a positive side likewise hypotheses in guidance with principles let's make an effort in not arguing but coming a statements 2 statements for both. Assumptions are very attractive let's say youth leaders when they talk it's very attractive I find leaders attractive but not impulsive. Assumptions generate positive beliefs. Hypotheses is a dictation of what is already noted down by someone else. Hypotheses has an outcome.

Design experiments to test prioritized assumptions and hypotheses. ?? Use methods like interviews, surveys, landing pages, and A/B tests to gather data. Choose the approach based on your goals and resources. Analyzing results helps validate or invalidate your assumptions systematically. ??

Continuously monitor the results of your tests and experiments. If an assumption or hypothesis is validated, incorporate it into your product development process. If it's invalidated, reassess and refine your approach based on the new insights gained. Iteration involves making incremental improvements based on feedback and learning from each iteration to refine your product further. This process is often referred to as the Build-Measure-Learn loop, popularized by the Lean Startup methodology.

Analyze experiment results to compare expected and actual outcomes. ?? Use tools like the lean canvas to update your vision based on findings. Document learnings and share with stakeholders. Decide whether to persevere, pivot, or perish, and repeat the process until achieving product-market fit. ??

I suggest documenting the assumptions thoroughly and being open to communicating the basis of these assumptions. Review the assumptions and gather feedback from diverse stakeholders. You will gain valuable insights both in support of and in contradiction to the assumptions.

Document assumptions thoroughly and communicate their basis clearly. ?? Gather feedback from diverse stakeholders to refine and challenge assumptions. Regularly revisit and update assumptions to ensure alignment with evolving market conditions and customer needs, fostering continuous improvement. ??