Prototypes and Minimum Viable Products

Objective: Explain prototype and minimum viable product, distinguish their meanings, and apply them to a described case.

Prototype: A prototype is a test version used to examine selected features or assumptions. Minimum viable product: An MVP is a limited offering designed to test key assumptions with users. A business model connects value creation, delivery, revenue, and costs. A revenue stream is one component of that model, not a complete explanation of viability. Early experiments should test a specific uncertain assumption using an observable result. Define the decision rule before interpreting the test, examine alternative explanations, and improve the model when evidence conflicts with expectations. Application: A team builds a simplified booking screen. This most directly illustrates prototype. A pilot provides the core service without every planned feature. This most directly illustrates minimum viable product.

Objective: Explain experiment and success criterion, distinguish their meanings, and apply them to a described case.

Experiment: An experiment compares outcomes under defined conditions to test a question. Success criterion: A criterion states in advance what outcome will count as useful evidence. A business model connects value creation, delivery, revenue, and costs. A revenue stream is one component of that model, not a complete explanation of viability. Early experiments should test a specific uncertain assumption using an observable result. Define the decision rule before interpreting the test, examine alternative explanations, and improve the model when evidence conflicts with expectations. Application: A team tests two onboarding approaches with a stated method. This most directly illustrates experiment. A pilot specifies a completion-rate target. This most directly illustrates success criterion.

Objective: Explain pivot and validation limit, distinguish their meanings, and apply them to a described case.

Pivot: A pivot makes a substantive strategic change based on learning. Validation limit: A validation limit identifies what a test has not established. A business model connects value creation, delivery, revenue, and costs. A revenue stream is one component of that model, not a complete explanation of viability. Early experiments should test a specific uncertain assumption using an observable result. Define the decision rule before interpreting the test, examine alternative explanations, and improve the model when evidence conflicts with expectations. Application: Evidence leads a team to serve a different customer group. This most directly illustrates pivot. A small successful trial does not prove nationwide demand. This most directly illustrates validation limit.