The dataset presents the duration in days for seven stages in a typical lifecycle from concept to delivery for a courtyard rubber flooring project. Each bar reflects how long a stage lasts before the product moves to the next phase. The production stage dominates the total cycle time, accounting for a substantial portion of the overall duration, which indicates throughput constraints in manufacturing, tooling setup, or material readiness. Shorter early stages such as Concept and Design suggest scoping and planning are relatively quick, yet even small delays here can cascade downstream when capacity is constrained. The Prototype and Testing stages show moderate variability, reflecting iterative refinement and quality validation that can be sensitive to design changes or supplier lead times. The Tooling stage, while shorter than Production, can be a critical catalyst for ramp-up, as tooling readiness affects batch size and start date for mainstream production. Delivery, though relatively brief, depends on logistics, packaging, and coordination with distributors; delays here can erode customer satisfaction even if manufacturing is on track. The data suggests several levers for improvement: parallelizing non-dependent validation tasks, pre-staging raw materials, and investing in automation or faster tooling setups to reduce setup times. A 10–20% improvement in non-production stages could reduce overall cycle time by several days, while a larger gain in Production could yield more pronounced reductions in lead time. Regularly reviewing stage-level performance allows a factory to detect emerging bottlenecks, forecast impacts under different demand scenarios, and align resources with production schedules. This lifecycle view supports data-driven decision making, better supplier coordination, and a clearer roadmap from concept to delivery in a competitive manufacturing environment. Data quality matters: ensure timestamps are recorded consistently, differentiate planned vs actual durations, and annotate deviations with root-cause notes. The visualization complements narrative analysis by providing an at-a-glance comparison across stages and facilitating collaborative problem solving.