Problem Framing
How a problem is framed determines what solutions become visible — and what gets built.
Problem framing is the process of determining what needs to be solved before deciding how to solve it.
How a problem is framed determines what solutions become visible.
A poorly framed problem can lead to the wrong research, the wrong decisions, or the wrong systems.
Before committing resources, technology, AI, or implementation, it is worth making sure the right problem is being solved.
Problems can be framed too broadly, too narrowly, aimed at the wrong target, or accepted without being questioned.
Too Broad
“We don’t have good visibility into what’s happening.”
That sounds like a problem.
But what exactly is the problem?
Too broad means action becomes guesswork.
Too Narrow
“We need to build a dashboard.”
Maybe.
But it could also be:
Too narrow means useful alternatives are excluded too early.
Misplaced
“We need to improve our website.”
The problem may be real, but it may not be the most important problem.
It could also be:
Misplaced means the wrong thing may be built well.
Inherited
“Customers want more features.”
This assumption may be correct. But has it actually been examined?
Questions worth asking:
Inherited means old assumptions keep directing new effort.
AI helps expand the frame. Human intelligence decides what matters.
AI-assisted exploration
Human judgment
In practice, problem framing is usually an iterative process: AI helps surface possibilities, humans evaluate them, and the frame is refined before significant resources are committed to execution.
When working through a new problem, several questions repeatedly prove useful.
Not the visible symptom. What are we really trying to solve?
What has been accepted too early? What is being treated as obvious?
What alternative interpretations exist? What adjacent possibilities deserve consideration?
What defines the boundary of the problem? What should remain outside the frame?
Only after the problem becomes clear can implementation become clear. This is where execution begins.
Organizations have access to capable people, powerful software, and increasingly capable AI. Yet projects still fail because the problem itself was never framed correctly.
Better framing improves the quality of insights, decisions, and systems.
If the problem is misunderstood, research may answer the wrong question, decisions may target the wrong objective, and systems may be built for the wrong purpose.
A better frame does not guarantee success, but it improves the chances that effort, resources, and intelligence are directed toward the right target.
Clarify what is actually being solved before anything is built.
Decide what belongs to software, AI, and human judgment.
Produce the type of solution the problem requires.
Whether the outcome is an insight, a decision, a system, or a combination of them, better results begin with a better understanding of the problem.
