Concepts
In order to validate a hypothesis, it is crucial to select an appropriate experiment. It can be a complex process and it often requires an understanding of the context, the problem at hand, and the factors being tested. The role of a Certified Scrum Professional-Product Owner (CSP-PO) in this scenario is essential. They are required to comprehend the hypothesis completely, choose the right test, and analyze the results accurately to drive the product development in the right direction.
Understanding the Hypothesis
To begin, you can best understand a hypothesis as an educated guess or prediction regarding a possible outcome. It could be related to a new feature, change in design, cost reduction initiative, or any other change proposition that you expect will lead to an improvement. It comes as part of the validate-learning process, which comprises three steps: build, measure, and learn. In this process, the hypothesis forms the basis of what you intend to learn.
Testing the Hypothesis
To effectively test a hypothesis, you would need to come up with an experiment that closely aligns with it. Ideally, the experiment should enable us to compare different outputs under controlled conditions. Some of the commonly used experiments types include:
- A/B Testing – This is widely used in software development and involves comparing two versions (A and B) of a product or feature to see which one performs better. It helps in taking data-driven decisions and reducing uncertainties.
- Multivariate Testing – These tests review multiple variables to understand which mix drives the most effective outcome.
- Blue-Green Deployment – This approach involves making the new version of the application (green) available alongside the old version (blue) to a portion of users to gather feedback.
While choosing an experiment, consider the difficulties of each approach. A/B testing might not be an ideal choice if there are multiple variables that affect the outcome. Multivariate testing, although it allows you to evaluate multiple changes concurrently, may be overkills when there are fewer variables, making A/B testing more efficient in that case.
Also, hypothesize the cost and risk involved. High-risk, high-cost hypotheses might need more rigorous testing or piloting before taking them live.
For instance, if you aspire to add a new feature to your product and want to test if this change increases user engagement, you might create a hypothesis like, “By adding a feature X, we anticipate user engagement will improve by Y%.” To test this hypothesis, you could opt for an A/B test where version A does not have the feature, and version B does. By exposing subsets of your users to both versions, you can compare results and evaluate if version B improves user engagement.
Conclusion
In conclusion, as a CSP-PO, remember, the trick to selecting an ideal experiment for testing a hypothesis is not just about picking an experiment based on what is convenient but what is the most applicable in that specific context. It involves a methodical evaluation of the hypothesis, the potential impact of the anticipated change, and the risks involved. It might take a bit of trial and error, but the process and the learnings along the way will surely help in driving the product towards success.
Answer the Questions in Comment Section
True or False: In Scrum, all testing and experiments should be left until the final stage of the project.
- True
- False
Answer: False
Explanation: In Scrum, testing and experimentation should be ongoing throughout the project, as it allows for regular feedback and iteration based on results and findings.
Multiple Select: Which of the following are key elements to consider when selecting an appropriate experiment to test a hypothesis in Scrum?
- A. Relevance to project goals
- B. Availability of resources
- C. Time needed for the experiment
- D. The color of the Test Lead’s shirt
Answer: A, B, C
Explanation: The test’s relevance to the project, resource needs, and time consumption are all critical factors to consider when selecting an appropriate experiment. The color of the Test Lead’s shirt has no relevance to this decision.
True or False: The Sprint Review is the appropriate meeting in Scrum to plan and decide experiments for testing hypotheses for the next sprint.
- True
- False
Answer: False
Explanation: The appropriate meeting for deciding experiments for the next sprint is the Sprint Planning meeting. The Sprint Review is for inspecting the increment and adapting the Product Backlog.
Single Select: Which of the following is not an appropriate way to validate a hypothesis in Scrum?
- A. A/B Testing
- B. User Testing
- C. Peer Review
- D. Guesswork
Answer: D. Guesswork
Explanation: Guesswork is not a valid or reliable way to test a hypothesis. Techniques such as A/B testing, user testing, and peer reviews offer more stable and rich insight.
True or False: Only the Product Owner can decide on appropriate experiments to test a hypothesis.
- True
- False
Answer: False
Explanation: While the Product Owner has a key role in prioritization, the whole Scrum team, including developers and the Scrum Master, should also be involved in collaborative decision-making process.
Multiple Select: What should be incorporated while creating testable hypotheses in Scrum?
- A. The change you want to make
- B. The impact you expect it to have
- C. Who you believe it will affect
- D. Your favorite color
Answer: A, B, C
Explanation: Incorporating the expected change, its impact, and the affected party/party’s are key elements of a testable hypothesis. Personal preferences such as favorite colors are not relevant.
True or False: In Scrum, it is not necessary to consider the feasibility of an experiment when selecting it to test a hypothesis.
- True
- False
Answer: False
Explanation: Feasibility, in terms of time, resources, and alignment with business goals, is crucial to consider when selecting an appropriate experiment.
Single Select: If the experimental results do not support the hypothesis, what should the Scrum team do?
- A. Abandon the Scrum project
- B. Change the hypothesis
- C. Ignore the results
- D. Repeat the exact same experiment
Answer: B. Change the hypothesis
Explanation: If the experimental results don’t support the hypothesis, it doesn’t mean the project should be abandoned. Instead, the team should iterate and adjust the hypothesis based on the information obtained.
True or False: Data collected from the chosen experiment should be used to evaluate the product increment in the sprint review.
- True
- False
Answer: True
Explanation: Data from experiments should definitely be used in the sprint review. It provides valuable insights that can give direction for changes or improvements.
Multiple Select: Whose input is valuable when selecting an appropriate experiment to test a hypothesis in Scrum?
- A. Product Owner
- B. Development Team
- C. Stakeholders
- D. Scrum Master
Answer: A, B, C, D
Explanation: Everyone involved in a Scrum project, including the Product Owner, Development Team, Stakeholders, and Scrum Master, has valuable input when it comes to selecting an experiment to test a hypothesis. Each person’s unique perspective and knowledge can contribute to a well-rounded decision.
Great post! Can someone explain the best experiment to test the hypothesis of a new feature’s impact on customer satisfaction?
Thanks for the information!
How does one ensure the validity of an A/B test when dealing with a large user base?
Fantastic blog post as always!
I think you missed discussing multivariate testing as an alternative method.
Could someone clarify the difference between hypothesis testing and exploratory data analysis (EDA)?
Interesting perspectives on testing! Appreciate the insights.
The post is good but could have covered more on the advantages and disadvantages of different testing methods.