Assumptions and effort/value mapping

Assumptions are beliefs your team holds but has not yet proven — about users, behaviour, feasibility, or value. Surfacing them early prevents costly builds on shaky ground. Mapping assumptions by effort and value helps teams decide what to validate, build, or defer.

Why it matters

NN/g emphasises that maps and plans built only from stakeholder assumptions carry risk: they may be incomplete, biased, or written off as anecdotal. Making assumptions explicit — then prioritising which to test — turns hidden beliefs into a manageable backlog of learning.

Key ideas

• Assumptions are not facts. Label them clearly until evidence confirms or refutes them.
• Effort estimates how costly it is to address or validate an assumption (low/high).
• Value estimates impact if the assumption proves true or false (low/high).
• Four buckets emerge from a 2×2 map:
  • Low effort / high value — do first
  • High effort / high value — plan and invest
  • Low effort / low value — maybe, quick wins only
  • High effort / low value — avoid
• Riskiest assumptions are high value and highly uncertain — test these before committing to build.

How it fits the pipeline

Assumption mapping builds on defined problems and helps teams decide what to validate before investing in solutions.

Common mistakes

• Treating assumptions as validated because "we've always done it this way"
• Mapping without rationale for effort or value judgements
• Skipping validation — assumption maps should feed research plans
• Confusing user assumptions with technical or organisational constraints without labelling them

Further reading (NN/g)

• Approaches to Journey Mapping — hypothesis-first vs research-first approaches
• How to Conduct Research for Customer Journey Mapping — why assumption-only maps need validation
• The 5 Steps of Successful Customer Journey Mapping — assumption formulation as an explicit phase