Project scoping and estimation is the structured process of turning a client's goals for a learning video platform into a defined scope — a list of features with their complexity and interdependencies — and then deriving a time and cost estimate from that scope. In practice, scoping for a learning video project starts from a reference architecture: the team maps the client's requirements onto a known blueprint, identifies which components are standard (video player, LMS integration, basic tracking) and which are custom (adaptive learning engine, custom proctoring, bespoke analytics), and sizes the custom work. A key discipline in scoping is separating must-have from nice-to-have features: scope creep on learning platforms is common because stakeholders tend to add interactive and AI features without understanding the engineering cost. Estimation techniques range from analogous estimation (comparing to past similar projects) to bottom-up estimation (sizing each component independently) to three-point estimation (optimistic, most likely, pessimistic per component). For learning video specifically, underestimated areas include WCAG accessibility compliance, SCORM/xAPI integration edge cases, video player customisation, and multi-tenant data architecture. Scoping is also the stage where build-vs-buy trade-offs are resolved: if a commercial LMS covers 80 % of requirements, the scoping output may be a custom video layer built as an LTI tool rather than a full platform. A well-executed scoping engagement produces a written scope document, a work-breakdown structure, and a confidence-ranged estimate that the client can use to make a go/no-go decision.
