The Scientific Method: Reframing An Underutilized Tool for Product Management
Mike Hyzy
kHUB post date: July 12, 2023
Read time: 8 minutes
While performing research for a healthcare consulting project, I stumbled upon the overview of the scientific method and thought, “There are parallels here in how we work in product management…blog” The neurons began firing, and the whiteboard was drawn upon. In our little dynamic corner of the product development universe, various tools and strategies are deployed to drive innovation, facilitate problem-solving, and create products that resonate with consumers. From feature prioritization frameworks to user journey mapping and customer feedback analysis to data-driven decision-making tools, product managers have a vast arsenal at their disposal. However, one instrument that stands out due to its time-tested effectiveness and universal applicability is the scientific method.
What is the Scientific Method?
The scientific method, a cornerstone of scientific inquiry, is a process employed to understand phenomena and answer questions. It offers a systematic, structured approach to problem-solving, making it an invaluable tool not just in science but in a plethora of disciplines — including product management.
The steps of the scientific method are simple:
- Formulate a Question
- Perform Background Research
- Create a Hypothesis
- Run an Experiment
- Collect and Analyze Data
- Interpret Results and Draw Conclusions
- Communicate Findings
Each step aids in transforming a raw idea into a viable, market-ready product that fulfills user needs while creating business value.
The Origins and Purpose of the Scientific Method
The scientific method traces back to ancient civilizations when scholars began to seek evidence-based answers to their questions rather than relying on superstition or conjecture. Notable philosophers like Aristotle and Euclid employed systematic observations and logical reasoning to understand the world around them, laying the groundwork for what would eventually be refined and formalized into the scientific method we know today.
The method gained prominence during the Scientific Revolution of the 16th and 17th centuries, championed by luminaries like Galileo and Newton. It’s now widely adopted across scientific disciplines for its ability to foster objective, reproducible results.
In a business context, the scientific method helps teams better understand market dynamics, customer behaviors, and the potential impact of their decisions, reducing uncertainty and driving informed, effective action.
Applying the Scientific Method in Product Management
Now that we have established the scientific method and its purpose let’s delve into its application in product management.
Inception: Asking the Right Questions
Product development begins with a question. Why? For product managers, this translates into identifying the problem their product will solve or the needs it will fulfill. They must ask: what is the primary issue we are addressing? Who is our target user? Why is our solution needed?
As Hal Gregersen eloquently illustrates in his book, ‘Questions Are the Answer: A Breakthrough Approach to Your Most Vexing Problems at Work and in Life,’ the inception of any significant innovation begins with asking the right questions. This principle is the foundation of the scientific method and, by extension, a cornerstone in the realm of product management. To understand the primary issue that a product aims to solve or the specific needs it strives to fulfill, product managers must be adept in posing these pivotal questions.
Exploration: The Power of Research
As scientists delve into existing research before formulating their hypotheses, product managers conduct similar explorations to gather crucial market insights. This process involves various activities such as market research, user interviews, focus groups, competitive analysis, and trend watching.
The similarity to the scientific method lies in the systematic approach and the aim to form an objective, evidence-based understanding of reality (most of the time). Scientists use their research to formulate hypotheses that they test experimentally, while product managers use theirs to make informed decisions about product features, positioning, and strategies. Both are engaged in a quest for knowledge to reduce uncertainty and make more effective decisions.
This exploratory phase helps validate the initial product idea and provides valuable insights to shape its design and strategy. By immersing themselves in research, product managers — like scientists — ground their work in data and evidence, increasing the likelihood of creating a product that stands out in a competitive marketplace.
Forecasting: Hypothesis Formation
It’s vital to continually assess and iterate on your product to better meet your users’ needs. One of the crucial stages in this process is forming a hypothesis — a predictive statement that sets a clear, measurable goal.
Let’s take an example. Suppose you’re responsible for a digital platform designed to help patients manage chronic conditions. After conducting comprehensive market research and user interviews, you uncover a consistent concern among users: they struggle with medication adherence due to complex prescription schedules.
Given these findings, you hypothesize that introducing a feature to simplify and automate medication reminders would improve medication adherence among users by 25% within six months. This hypothesis sets a clear and measurable goal, making it easier to determine its success.
The hypothesis formulation stage is pivotal because it sets the course for the feature development and the metrics you’ll track. Whether the hypothesis is validated or refuted, you gain insights that help in enhancing your product. Just as scientists iterate on their theories based on new data, as a product manager, you would iterate on your product features based on user feedback and measured outcomes, aligning your work with the principles of the scientific method.
Verification: Experiments and Prototypes
In healthcare product management, validating hypotheses via experiments or prototypes is crucial. For instance, if our hypothesis is “Implementing an automated medication reminder will improve adherence by 25% in six months,” we would create a core version of this feature for testing.
Ensuring regulatory compliance, we roll out this feature to a representative user segment, ideally a group that represents your primary target demographics well. By observing its use and gathering feedback, we assess its effectiveness and understand its pros and cons.
We gain invaluable insights if the feature increases medication adherence as hypothesized or if the data suggests adjustments. This scientific approach facilitates continual, informed product refinement, aiming for a better fit with user needs and enhanced health management.
Reflection: Data Analysis and Conclusions
Put on your white lab coat; analyzing the data from experiments or user interactions with a prototype provides a concrete foundation for decision-making.
Let’s take our medication reminder feature example. Once the feature has been rolled out and used by a subset of users, it’s time to dig into the data. This could include quantitative metrics such as user engagement rates, adherence improvement percentages, or app usage patterns. Qualitative feedback from user surveys or interviews adds richness to the data set.
With this data, we determine whether the reality aligns with our hypothesis of a 25% improvement in medication adherence. If the data support the hypothesis, it’s a solid signal to further refine and fully develop the feature.
However, if the data doesn’t support the hypothesis — say, the medication adherence only improved by 5% — then we must revisit our assumptions. The feature needs tweaking to be more user-friendly, or a different solution would better address the medication adherence problem.
Regardless of the outcome, every analysis is a learning opportunity. The scientific method isn’t a linear path to success but an iterative learning, adapting, and improving the process. By using this approach, you can incrementally enhance your products, ensuring they effectively meet user needs and contribute to improved health outcomes.
Articulation: Communication of Findings
Now take off your lab coat and put on your consulting suit. It’s time to spend the next three weeks in PowerPoint. Tactical communication is the capstone of the scientific method in product management, and this is even more true in a complex sector like healthcare where the collaboration of diverse stakeholders is vital.
Following our medication reminder feature example, the next step is to share these findings with the broader team, stakeholders, and investors after analyzing the data and making decisions based on the outcomes. This communication is not just about presenting numbers — it’s about telling a story.
A well-structured report or presentation would start by revisiting the original hypothesis and the reasons for testing that specific feature. It would then delve into the methods used for testing, clearly outlining the user segment involved, the duration of the test, and the key performance indicators tracked.
Next, you’d present the data. Use visually engaging graphs or charts to illustrate the changes in medication adherence rates. But don’t stop at just presenting the raw data; interpret it. Explain what these figures mean for the product and the company. For instance, a 10% improvement in medication adherence might mean fewer health complications for users and a potential reduction in healthcare costs, positioning the product favorably in the market.
Then, discuss the lessons learned, whether it’s the validation of the initial hypothesis or the need to rethink your approach. If the feature needs tweaking or a new hypothesis is formed, outline the next steps in a roadmap format and have tangible milestones with outcomes.
Finally, invite questions and feedback. Encourage a two-way dialogue to ensure alignment and buy-in from all stakeholders. A shared understanding of the product’s direction fosters collaborative effort towards shared goals.
Transparent, timely, and engaging communication helps maintain trust among stakeholders and ensures everyone is aligned with the strategic direction of the product. It turns the scientific method from a solo endeavor into a shared journey toward building an impactful healthcare product.
The Iterative Nature of the Scientific Method
One of the most potent aspects of the scientific method is its iterative nature. This means that each step of the process could lead back to a previous one, fostering continuous refinement of ideas, features, and overall product strategy. If the data collected does not support the hypothesis, product managers loop back — adjusting the hypothesis or redefining the initial problem.
This iterative process, intrinsic to the scientific method, mimics the agile development cycles that many product teams employ. It ensures the product adapts to user feedback and market changes, allowing the team to continually refine and enhance it until it meets user needs and market expectations.
The Expanded Role of the Scientific Method in Product Management
The scientific method provides a rigid structure to the product development process and teaches a culture of curiosity, experimentation, and learning within the team. It helps instill a discipline of questioning assumptions, validating hypotheses, learning from data, and iterating on results.
Moreover, this method makes the decision-making process transparent, collaborative, and evidence-based rather than being guided by intuition or opinion. By grounding decisions in data and observable facts, product managers can drive stakeholder buy-in, align team efforts, and avoid costly mistakes.
Wrapping Up
In summary, the scientific method — an old tool with a fresh twist — can be a game changer in product management. It offers a proven, systematic approach to building outstanding, user-centric products. Product managers can navigate the complexities of their role more confidently by fostering a culture of asking insightful questions, conducting robust research, formulating hypotheses, experimenting with prototypes, analyzing data, and effectively communicating results.
Remember, the scientific method isn’t a static, one-and-done process — it’s an iterative loop of learning, refining, and improving, marking a roadmap toward consistent product management success. It’s time we leverage this underutilized tool more consciously to navigate the intricacies of building incredible products that users love and markets reward.
About the Author
Mike Hyzy is a Senior Principal Consultant, Author, Speaker. Driving transformative change. Inspiring with strategic insights. Making an impact in consulting and beyond.
For more information or to get in touch, visit www.mikehyzy.com
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