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012 // Want Better Outcomes? Find Better Problems.

Image with text. Text reads: Ideas from Dawan for people who think and solve like a designer.

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We create new things to generate the outcomes we want. Those outcomes might mean someone needs to buy or use what we’ve created to solve a problem they have. Those outcomes might mean a city service needs to produce different outcomes for the people who use it. Outcomes we want but can’t generate are what make us want to create something new; they stimulate inquiry, exploration and making. This urge also invites us to rush a terrible mistake.

Problem Spaces

The urge to create calls to us; it begs us to dive in and make something, anything. When we do, what we often miss is that the urge to create and generate the outcomes we need isn’t asking us to make a solution. The urge is asking us to understand the problem we are trying to solve as a question we are seeking to answer. When we dive right in we assume too much about what the problem really needs for us to do.

A problem space is the gap between the world we have and the world we want, where we search for ways to bridge that gap. For example, I want cookies. The world I have is barren and cookieless. The world I want is one with a large plate of fresh, and possibly warm, cookies.

People, context and history create the terrain we search through inside a problem space. The people you serve are the people who are experiencing challenges that are preventing the outcome/s you seek. Living the problem makes them, not us, the experts in how people experience that problem. Seeing the problem space starts with seeing what they see and how they make decisions as they seek to close the gap between worlds.

Next, we need to see the context or contexts where people are experiencing the challenge. Those moments, locations, systems, events, conversations, and interactions influence how people interpret things, behave, and decide. When we miss data and observation that reveals those influences, we miss too much of what forms the problem space.

The people and context have a history that reveals how they have changed over time and might change in the future. We miss valuable lessons, hints, predictions, traps, and opportunities when we ignore that history.

Problem Finding

When we dive into researching the people, context and history, we’re searching the problem space until we can describe its core and express the entire space well. Think of that expression of the problem as a bridge between the world we have and the world we want. The world we want is the world where what we’ve created, our solution, is generating the outcomes we want.

Problem finding is finding the bridge that, based on our problem-space exploration, is likely to take us from the world we have to the world we want. When we skip problem space work and immediately dive into solution space work, we’re guessing about that bridge and hoping we get lucky or can mitigate the damage. When we do the problem space work, the problem space teaches how we might fold everything we’ve learned into a question that guides our solution space work.

The urge to find and refine problems is unnatural. A missing solution creates a mental and emotional itch we want to scratch immediately. Our natural impulse is to race toward a solution. Part of the mental agility designers learn and cultivate is the ability to experience problem space exploration as a part of solving.

Current learning theory is highly focused on teaching these skills explicitly as a way of improving learners’ overall brain function. Thinking and solving like a designer also promotes living well by allowing for self-reflection and skills that spill into other spaces in our lives.

Folding Space

Framing is the art and science of folding problem space insights into a question. Framing, as part of problem finding, gives us something concrete we can use to guide our solving. We’re seeking to create a bridge between the world we have and the world we want. Framing is looking for a question that, when answered, will create the product, service, experience, or system that creates that bridge.

We’re looking for a question that asks, “How might we … ?” How might we use existing relationships with hospitals to combat disinformation? How might we destigmatize substance use and harm reduction in the eyes of local political leaders? How might we make mentally-healthy practices a natural part of how we learn and teach on campus?

A how-might-we question serves as an initial compass reading. Our solution space activities will require course corrections. As we do more research, create prototypes, and learn more about the people, context and history, we’ll need to adjust our how-might-we question as we better understand the problem space.

There’s a reason ambiguity and comfort with it is a popular design topic. Adjusting our how-might-we question as what we learn from actions we take while solving is one of the many feedback loops that prevent design from being a linear process. While nonlinear, the design process is time-bound: we run out of time eventually. Before that happens, we’ll be pulled from feedback loop to feedback loop inside the design process. Part of the comfort with ambiguity comes from seeing the framing looping as progress toward a how-might-we question that represents a more accurate understanding of the problem space. Additional comfort comes from experiencing what we’re able to do as we refine our how-might-we question.

Swiss Army Question

Folding a problem space into a how-might-we question supports the work of solving in many ways. When we do the problem space research and create a framing question, we are able to:

  1. Use the question to guide our research.
  2. Create with the people we serve and others because they understand the question we are trying to answer together.
  3. Adapt our problem space as we learn.
  4. Quickly explain what we are working on.
  5. Gauge when we might need to adjust our how-might-we question when we see our work start to answer a different question.
  6. Better evaluate how well potential solutions solve our problem.
  7. Design for solution adoption by communicating the connection between what we create and how people understand their problem or challenge.
  8. Develop solution performance measures that flow from our question and help us evaluate what matters most.

Good designers find ways to make individual actions or elements do multiple jobs. Problem space exploration yields a how-might-we question that will be useful in many ways during the life of an innovation project and beyond. Good designers also insist on cognitive diversity. The best solutions come from a diverse team of designers with different backgrounds, who can see the space differently. A lack of diverse problem-solving perspectives has hindered even our highest intelligence agencies.

There are entire books about problem space exploration and research methods. To help you jump right in, I created an Ask Like a Designer Thinking Tool for this article — the Better Outcomes Thinking Tool. Download it here. Get better results by creating a stronger basis for where you’ll focus your solution energy.


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