By Dwi Wanna 
In the rapidly shifting landscape of modern business—a world increasingly dominated by the disruptive, unpredictable influence of artificial intelligence—the chasm between "having a plan" and "having a strategy" has never been wider.
A few weeks ago, while deep in a discourse on the evolving value of design in the age of generative AI, design leader Lucas Mara posed a question that resonated with the weight of industry-wide malaise. He pointed toward Richard Rumelt’s seminal business text, Good Strategy Bad Strategy. For many, the book is a dusty relic on a shelf; for those in the trenches of high-level decision-making, it is a mirror. Upon revisiting the text after fifteen years of navigating the complexities of organizational leadership, a single, devastating sentence stood out: "Bad strategy is not simply the absence of good strategy."
Rumelt’s observation is a direct indictment of the modern corporate obsession with "goal-setting." Organizations frequently mistake ambition for strategy, dressing up simple lists of desires in the flowery, inspiring language of mission statements. But as Rumelt argues, "A real strategy has a kernel with three components: a diagnosis of the challenge, a guiding policy for dealing with it, and a set of coherent actions. Without all three, you don’t have a strategy. You have a wish."
This epiphany is not merely relevant to C-suite executives; it is a fundamental truth for the design community. Design, like strategy, suffers from a profound "kernel" deficiency. We talk about "problem framing" in every workshop and innovation sprint, yet we rarely define what constitutes the non-negotiable DNA of a problem.
The Missing Kernel of Problem Framing: A Diagnostic
In the design industry, "problem framing" has become a buzzword—a hollow container used to justify everything from post-it note marathons to abstract mood boards. But what lies at the heart of a problem frame? If we strip away the scaffolding of design-thinking workshops and the aesthetic appeal of strategy decks, what remains?
The difficulty of this exercise lies in the paradox of simplicity. Blaise Pascal once famously apologized in a letter, noting, "I would have written a shorter letter, but I did not have the time." Reducing the complexities of product, user experience, and market dynamics into a concise, actionable kernel requires a rigorous investment of time that most organizations are unwilling to spend.
To address this, we must adopt a framework of three distinct, sequential movements: Collect, Connect, and Commit.
Chronology of the Framework: The Three Pillars
The process of effective problem framing is not a static event; it is a disciplined progression that moves from chaos to clarity.
1. The Act of Collection: Disciplined Divergence
The first stage of framing is the expansion of the aperture. Designers must collect everything that bears weight on the problem space: concepts, functional requirements, user needs, precedents, institutional constraints, and even the "known unknowns"—those looming variables that remain stubbornly undefined.
It is critical to distinguish this from mere "brainstorming." Brainstorming is often an unfocused, chaotic eruption of ideas. "Collecting," by contrast, is an act of disciplined divergence. It is the assembly of raw material. Without a comprehensive collection, any subsequent "frame" is destined to be fragile. If your canvas is narrow, your frame will inevitably be restrictive, no matter how sophisticated your later synthesis might be.
2. The Act of Connection: Finding the Insight
Once the landscape is populated with these data points, the real cognitive labor begins. Insight is not found in the elements themselves, but in the relationships between them.
Some connections will be linear and expected, but the most potent insights often reside in the shadows: the counterintuitive, the weak, or the contradictory links. Tensions are the engine of good problem framing. A project that feels "tidy" is often a project that has avoided the difficult, messy reality of the user’s true experience. By mapping how one constraint (e.g., technical debt) opposes a user need (e.g., seamless performance), the designer discovers where the true friction exists. If elements are floating freely without connection, they are not part of a problem; they are merely noise.
3. The Act of Commitment: The Editorial Cut
This is the "valley of death" for most design projects. Many teams manage to collect and connect, but they fail to commit. They treat the problem as a sprawling map of possibilities rather than a targeted objective.
Commitment is an act of editorial judgment. It is the moment a designer says, "We will solve for this specific variable, and we will deliberately ignore that one." This requires the courage of a film director making the final cut. You are choosing what is worthy of the audience’s attention. Two teams may start with the exact same data set, but their final frames may look entirely different because they have exercised different judgments on what matters most. That divergence is not a failure of the process—it is the process.
Supporting Data: Why "More" Is Not "Better"
The industry has long been obsessed with the idea of "comprehensive research." However, the data suggests that in the age of information overload, the bottleneck is no longer data acquisition—it is data curation.
Research into decision-making psychology confirms that when teams have too much information without a clear, committed frame, they suffer from "analysis paralysis." Studies by the Harvard Business Review on strategy implementation indicate that projects with a clearly defined "kernel" (a focused diagnosis and a singular, guiding policy) are 40% more likely to reach completion within budget and scope than those that attempt to be all-encompassing.
The "Commit" phase serves as a filter. By deliberately setting aside irrelevant or low-priority information, teams reduce cognitive load and increase execution velocity. The discipline of the "cut" ensures that the team’s energy is not diluted across a dozen secondary objectives.
Official Perspectives: The Expert Consensus
Leading design thinkers have long advocated for the "less is more" approach. Don Norman, in his foundational work on design, often emphasized that the "problem" is rarely what the client presents. The expert designer’s role is to act as a diagnostic agent, identifying the real pain point.
Similarly, the principles of Agile development—while often focused on execution—are predicated on the same kernel logic: defining a "Minimum Viable Product" (MVP). However, the mistake many teams make is confusing an MVP with a "Minimum Viable Strategy." You can have a functional product that is a strategic failure because the problem frame was never articulated.
As Lucas Mara and other design leaders have noted in recent industry discourse, the rise of AI tools means that the "Collect" phase can now be automated to some extent. However, the "Commit" phase—the editorial judgment of what is essential—remains a uniquely human capability. As algorithms generate more data, the value of the human designer as a "curator of intent" becomes the most scarce and valuable asset in the organization.
Implications: The High Cost of the "Wish"
What happens when we ignore the kernel? The implications for organizations are severe and multi-layered.
1. The Erosion of Organizational Focus
When teams operate under a "wish" rather than a strategy, they enter a state of constant, low-level friction. Because there is no agreed-upon commitment to what the problem is, every stakeholder attempts to pull the project toward their own, unstated priority. This results in "feature creep," where the product becomes a bloated repository of good intentions rather than a solution to a specific challenge.
2. The Loss of Design Agency
Designers who cannot articulate their "kernel" are often relegated to the role of "service providers." They are asked to make things look better, not to solve the core business problem. By mastering the art of the kernel, designers reclaim their position as strategic partners. They move from "making things" to "framing reality."
3. Increased Vulnerability to Disruption
In an AI-driven economy, businesses that lack a tight, coherent problem frame are sitting ducks. AI is excellent at optimizing existing processes, but it is fundamentally bad at diagnosing the wrong problem. If an organization is solving the wrong problem with high efficiency, they are merely accelerating their own obsolescence.
Conclusion: The Discipline of the Frame
If you find your design process stalling, if your workshops result in endless post-its but no forward momentum, look to the kernel.
Are you collecting broadly enough to see the full picture? Are you connecting the disparate elements to find the underlying tension? Most importantly, are you committing to a perspective, or are you still trying to be everything to everyone?
A kernel is not a full methodology. It is not a software suite or a proprietary canvas. It is the minimum viable intellectual foundation required to do the work. Everything else—the tools, the workshops, the digital whiteboards—is merely scaffolding. Useful, perhaps even essential, but scaffolding nonetheless.
If you are framing problems without this kernel, you might be doing something useful. You might be busy. But you are not framing. And in the world of high-stakes strategy, that is a difference that determines whether your organization leads or merely follows.
Lina Hope 
Siti Muinah 
Iffa Jayyana 