Understand the problem before generating solutions

There is one mistake that can make an entire ideation session useless: generating solutions for a problem that was never properly understood.

If a product is not selling, for example, we may immediately suggest discounts, new features, advertising campaigns, or pricing changes. But perhaps the real issue is somewhere else. The product may be targeting the wrong audience, the checkout process may be confusing, the value proposition may not be strong enough, or the product may simply not solve a problem that users consider important.

Before generating solutions, I try to understand the cause of the problem. Tools such as the Fishbone Diagram and the 5 Whys can help considerably with this investigation. I explain this process in: Fishbone Diagram: What It Is, How to Create One, and Find the Root Cause of a Problem .

Depending on the decision, we may also need to understand the market, competition, demand, and financial feasibility before investing in a solution. In that case, I also recommend: Market Analysis and Business Case: How to Assess Product Feasibility .

Only after the problem is sufficiently clear do I consider it a good moment to start generating alternatives.

What is idea generation?

Idea generation is the process of creating different possible ways to solve a problem, respond to an opportunity, improve a product, or change an existing situation. The objective at this stage is not to immediately discover the perfect answer. It is to create enough alternatives so that we are not forced to execute the first solution someone suggests.

This is closely related to ideation. In product development, design thinking, innovation, and problem solving, ideation is the phase in which we deliberately expand the space of possible solutions before narrowing it again.

This distinction is important because idea generation and decision-making require different behaviors. During idea generation, we want variety, exploration, and even unrealistic possibilities. During prioritization, we need criteria, evidence, constraints, and trade-offs.

Brainstorming: how to generate more ideas

Brainstorming is probably one of the best-known idea generation techniques. The basic concept is simple: a group generates as many ideas as possible around a clearly defined problem without judging those ideas too early.

There is an important difference between brainstorming and simply putting several people in a meeting to discuss a problem. In a normal discussion, someone proposes an idea and another person immediately explains why it will not work. When that happens too early, potentially useful ideas disappear before they have a chance to evolve.

In brainstorming, I prefer to separate two different moments: divergence and convergence. First, we expand the number and variety of possibilities. Later, we reduce them by evaluating which alternatives actually make sense.

This is very similar to the logic behind the Double Diamond: expand the problem or solution space, then converge toward the most promising alternatives.

How to brainstorm effectively

The first thing I do is define a sufficiently clear problem. The more generic the question is, the more difficult it becomes to generate useful ideas.

For example:

“We need to double the sales of our website.”

From that point, the idea generation phase begins. At this stage, almost anything can be suggested:

- Offer a 10% discount.
- Call every customer and offer a product.
- Create a referral program.
- Redesign the checkout process.
- Put a monkey dancing tango with one of our products on the website.
- Ask Bruce Springsteen to write a song about the company.

Obviously, some of these ideas are unrealistic. That is not necessarily a problem. An absurd idea may lead to another, less absurd idea, which may eventually generate something genuinely useful.

I usually follow a few simple rules: do not judge ideas while they are being generated, prioritize quantity before quality, allow participants to build on other people's ideas, and record everything. When the generation phase is over, the behavior changes completely and we start evaluating the alternatives.

That is when questions such as these become useful: How much would this cost? How long would it take? What impact do we expect? What risks are involved? Do we have enough capacity? Can we test the idea without building the complete solution?

Idea generation and problem solving

There is a major difference between generating many ideas and actually solving a problem. Brainstorming expands the number of alternatives, but effective problem solving also requires understanding causes, evaluating constraints, comparing trade-offs, and verifying whether the chosen solution works in practice.

This is why I do not treat brainstorming as an isolated activity. I see it as part of a sequence: first we understand the problem, then we generate alternatives, then we prioritize them, and finally we test the most promising ones.

If we jump directly from a problem to the first available idea, we may end up executing the wrong solution extremely well.

Ideation and brainstorming: what is the difference?

Brainstorming is one technique that can be used during a broader ideation process. Ideation is the broader activity of exploring different ways to solve a problem or satisfy a need.

This means brainstorming does not have to be our only technique. We can combine workshops with customer interviews, research, competitor analysis, prototypes, Crazy 8s, user observation, or other forms of idea generation.

The important distinction is that ideation is about creating possibilities, while prioritization is about making choices.

Crazy 8s: a fast idea generation technique

One technique I like for accelerating idea generation is Crazy 8s. The exercise is simple: take a sheet of paper, fold it three times, and unfold it. You will have eight different sections.

The facilitator then introduces a problem. Let us use a different example:

“Customers are adding products to the cart but leaving before completing the purchase.”

Each participant starts drawing possible solutions. It does not matter whether you can draw well. The objective is not to create a beautiful interface; it is to represent an idea quickly.

The exercise should move fast. Participants should not spend several minutes trying to create the perfect solution. Time pressure exists precisely to reduce overthinking and encourage people to generate possibilities.

Impossible ideas are also allowed. You can improve your previous idea in the next drawing or take an idea from another participant and transform it into something different.

By the end of the exercise, the team will have several visual alternatives. These ideas can then be grouped, combined, discussed, and reduced until only a few options remain for deeper investigation.

How to turn ideas into potential solutions

Once a brainstorming or Crazy 8s session is complete, a new problem appears: we now have too many ideas.

At this point, quantity is no longer the objective. We start asking harder questions. Which alternative has the greatest potential to solve the problem? Which one is technically feasible? Which requires fewer dependencies? Which costs less? Which can be tested faster? Which could generate more value?

We also need to consider the people affected by the decision. A solution may look excellent from a product perspective while creating a serious problem for technology, operations, sales, finance, or customer service.

When a change affects different areas or people with significant influence, stakeholder analysis can also become important. I discuss this in: Stakeholder Mapping: How to Identify, Analyze, and Manage Project Stakeholders .

How to prioritize ideas

Prioritization is where idea generation becomes decision-making. Instead of asking only whether an idea is interesting, we need to compare alternatives using explicit criteria.

Depending on the context, those criteria may include value, cost, effort, risk, strategic alignment, technical complexity, dependencies, time to market, customer impact, or learning potential.

The objective is not to discover a mathematically perfect answer. It is to make the reasoning behind the decision visible enough that the team understands why one idea is being selected over another.

How to use an Impact × Effort Matrix

One simple way to support idea prioritization is an Impact × Effort Matrix. Instead of comparing alternatives only through opinions, we place them on a matrix using two questions:

• How much effort will this idea require?
• What impact do we expect if it works?

These two dimensions create four groups:

• High impact and low effort: usually the opportunities we should investigate first.
• High impact and high effort: potentially strategic initiatives that require planning, capacity, and investment.
• Low impact and low effort: possible quick wins, as long as they do not distract the team from more important priorities.
• Low impact and high effort: usually the first candidates to be eliminated.

Effort and impact are still estimates, of course. The matrix does not make the decision for us. What it does is make the criteria behind the discussion more explicit.

What about the Eisenhower Matrix?

In an earlier version of this article, I called a matrix based on urgency and importance an “MVP Matrix.” That name was incorrect. The model is actually known as the Eisenhower Matrix.

The Eisenhower Matrix categorizes activities according to whether they are important, not important, urgent, or not urgent. From there, we typically decide whether to do, schedule, delegate, or eliminate an activity.

It is a useful prioritization tool, especially for tasks and time management. But when we are comparing possible solutions to a product problem, I prefer the Impact × Effort Matrix because it directly compares the expected benefit with the relative cost of implementation.

In other words, the fact that something feels urgent does not necessarily mean it is the best solution.

How to validate an idea with a Minimum Viable Product

After prioritizing ideas, we still should not assume that the complete solution needs to be built immediately. When uncertainty is high, I prefer to first understand the smallest thing we can do to validate the hypothesis.

This is where the concept of a Minimum Viable Product, or MVP, becomes useful. The question changes from simply:

“What should we build?”

to:

“What is the smallest version of this solution that can tell us whether our hypothesis makes sense?”

This matters because an idea can look excellent during a brainstorming session and still fail once it reaches the market. The less time and money we need to invest to discover that, the better.

Market analysis, hypotheses, feasibility, and business cases are directly connected to this decision. For a deeper discussion, I recommend: Market Analysis and Business Case: How to Assess Product Feasibility .

How to use project data to decide what to build

There is one part of this process that is often forgotten: after choosing an idea, someone still has to execute it.

A solution that looked simple during ideation may start consuming much more money than expected. An MVP may grow until it is no longer minimal. Tasks may be poorly defined, estimates may start failing, dependencies may appear, and new risks can emerge during execution.

This is where Saint Jude Project Intelligence can support the decision-making process. By using the data already generated in platforms such as Jira, Azure DevOps, Asana, Monday.com, and ClickUp, teams can analyze costs, schedules, estimates, task quality, capacity, performance, and risks related to implementation.

Imagine two solutions that appear to generate similar impact. The first requires only a few changes and can be delivered quickly. The second begins consuming several sprints, depends heavily on specific professionals, and uses much more budget than expected.

That information may completely change the decision. Prioritization should not end when an idea is placed inside a quadrant. We need to keep evaluating whether something that looked like a good idea still represents a good decision while it is being executed.

The goal is not to find one perfect idea

Perhaps this is the most important point in the article. The goal of idea generation is not to gather people until someone magically discovers “the right idea.”

The goal is to create enough alternatives so that we are not forced to execute the first solution someone thinks of. From there, we use evidence, context, experience, prioritization, and experimentation to gradually reduce the number of possibilities.

Brainstorming expands the solution space. Crazy 8s accelerates ideation. The Impact × Effort Matrix helps us prioritize alternatives. An MVP helps us validate a solution before investing too much. And execution data helps us understand whether the decision still makes sense once work begins.

In the end, finding better solutions is not only a matter of creativity. It is a decision-making process.

And a good decision usually starts with two questions:

“Are we solving the right problem?”
“Which alternatives have we not considered yet?”

See you soon!

Erik Scaranello