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The Art of the Sound Decision: Jonathan Gowens’ Framework

June 10, 2025

“When you understand the way of the sword, you understand yourself, and when you understand yourself, you understand the world.” — Miyamoto Musashi

In our book, Practical Product Management for Product Owners, Robbin Schuurman and I explore the stance of the Decision maker. In any professional setting, and especially the Product Owner, the ability to make effective decisions is paramount. Yet, the process is often approached haphazardly, leading to inefficiencies or outright failures.
 

Jonathan Gowens’ framework offers a structured approach to making what are termed high-quality decisions — choices rooted in a rigorous process, designed to maximize the likelihood of a favorable outcome. This isn’t about guaranteed success, but about disciplined execution in decision-making.

Components of a High-Quality Decision

1. Well-Framed

A decision begins with clarity. Before any solution can be considered, the decision itself must be precisely framed. This involves defining what is being decided, what constitutes success, the relevant context, and any existing constraints. Without this foundational understanding, efforts can be misdirected, leading to ambiguity and subsequent missteps.

2. Clearly Understand the Problem

Effective decision-making necessitates a thorough understanding of the problem. This requires dedicated time to analyze the root causes, identify affected parties, and comprehend the implications of the problem if left unaddressed. Rushing to solutions without a deep grasp of the underlying issue often results in addressing symptoms rather than the actual problem.

3. Explore Options

Once the problem is understood, the next step involves exploring a range of potential options. This counters the tendency towards “narrow framing,” where the first plausible solution is often adopted without sufficient consideration of alternatives. Generating diverse solutions, even those initially seeming unconventional, broadens the scope for optimal outcomes.

4. Gather Relevant Information (Evidence-Informed)

High-quality decisions are evidence-informed. This requires drawing upon various sources of information, typically categorized into three lenses:

1.) Intuition: Insights derived from experience and tacit knowledge.
2.) Data: Quantitative facts and metrics.
3.) Feedback: Qualitative insights from stakeholders and users.

Reliance on a single source of information can be misleading. A comprehensive approach integrates these elements to provide a more complete and nuanced understanding, even when advanced tools are available for analysis.

5. Consider All Trade-offs

Every decision involves trade-offs. A disciplined approach requires evaluating the pros and cons of each explored option. This critical comparison highlights the implications of selecting one path over another. Communicating the rationale for the chosen option, including the sacrifices made, is essential for gaining organizational alignment and understanding.

6. Take Action

A decision remains theoretical until action is taken. The culmination of the decision-making process is the implementation of the chosen course. For decisions to be effective and sustainable, clear organizational alignment is necessary, ensuring all relevant parties understand their roles in executing the decision and contributing to its intended outcome.

I found that Jonathan Gowens’ framework provides a pragmatic roadmap for navigating complex choices. By systematically addressing each of these six components, individuals and teams can enhance the quality of their decisions, fostering a more effective and reliable operational environment.


Big thanks to Phil Hornby for making me remember it.


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Comments (1)


Mattias Wahlberg
05:40 am June 13, 2025

While Gowens’ framework provides valuable structure, it reflects a deterministic mindset that doesn’t align well with software product development’s inherent uncertainty. The framework implies that following six steps correctly leads to the “right” decision, but this treats decisions as one-time events where enough analysis yields optimal outcomes.

In reality, user behavior is unpredictable, market conditions shift rapidly, and technical assumptions prove wrong. This creates false confidence that we can “solve” our way to success through better analysis alone.

Modern product management instead embraces decision-making as hypothesis formation and testing. Rather than seeking the perfect decision, we frame choices as bets: “We believe that [user value hypothesis] will result in [expected outcome]” with explicit confidence levels and assumptions. The goal shifts from decision quality to learning velocity - making smaller, reversible decisions quickly while building feedback loops to validate assumptions rapidly.

This means managing decision portfolios rather than individual choices, balancing high-confidence/low-impact decisions with low-confidence/high-impact bets. We embrace probabilistic thinking - “This has a 70% chance of improving user retention by 15%” - and update beliefs based on evidence rather than defending initial decisions.

The fundamental shift is from “How do we make the right decision?” to “How do we learn our way to better outcomes while managing downside risk?” This probabilistic approach acknowledges that uncertainty is a feature, not a bug, of product management and builds decision-making systems that thrive in ambiguous environments rather than trying to eliminate ambiguity through analysis.​​​​​​​​​​​​​​​​