The Most Expensive Product Mistake Is Building the Wrong Thing

Define the business problem in observable terms

A useful problem statement names the user, the difficult task, the current workaround and the consequence of leaving it unresolved. “We need an AI dashboard” describes a solution. “Operations managers cannot identify which orders need intervention” describes a problem that can be investigated.

Separate evidence from enthusiasm

Interviews are a starting point, not automatic proof of demand. Ask people to describe the last time the problem occurred, show the tools they used and explain what they did next. Compare what they say they want with what they already spend time or money doing.

The person using a product may not be the person authorising its purchase. Understand both. A useful feature can still fail commercially if procurement, security review or adoption costs make the change unattractive. Keep these constraints alongside the product requirements.

Test the riskiest assumption first

For a hypothetical reporting product, the uncertainty may be whether anyone acts on the report, not whether the team can build a chart. A manually prepared report can test that decision before a complete data platform is commissioned. This is an illustrative approach, not a client outcome.

Choose an experiment that could genuinely change the plan. Define what evidence would support proceeding, revising the scope or stopping. Avoid tests whose only possible conclusion is that the original idea was right. A prototype is useful when it reduces a specific uncertainty.

Make scope a decision, not a wish list

Distinguish the minimum workflow that produces value from the features that make it comfortable. Identity, permissions and recovery may be essential even when they are invisible in a sales demonstration. Conversely, several attractive interface features may be unnecessary for the first release.

Give each planned feature a reason to exist: the decision it supports, the user affected and the evidence behind its priority. When every feature is labelled critical, the team has not yet made a product decision.

Use delivery to learn, not just to finish

Review the product against its intended business behaviour after each useful increment. Do people complete the workflow? Do they return? Can the team support it without hidden manual work? These questions are more informative than the number of tickets closed.

Changing direction when evidence changes is not failed execution. The point of early product engineering is to make uncertainty cheaper. Agree the next learning milestone before agreeing the next large build commitment.