Miners seeking sustainable growth face a dual challenge: proving near-term operability while credibly extending value through additional capital investments. This case study presents a structured pathway to develop a strategic mining schedule for a three-pit copper–nickel system. The goal is to align funding decisions with realistic timelines and constrained operations. This work presents an alternative to conventional pit-shell workflow using an integrated direct block scheduling (DBS) approach leveraging the Bienenstock–Zuckerberg (BZ) algorithm. DBS incorporates time-dependent constraints such as limited sink rates, mining boundaries, earliest start dates, material blending, and staged capital expenditures. The advantage of DBS lies in its ability to embed these constraints early in the optimisation process and preserve the time value of money. The result is a schedule that is based on dynamic rather than static cut-off grades. The DBS optimised extraction sequence is then translated into operational phases using clustering based phase generation (PGN), with outputs that vary depending on phase targets—for example, smoothing mine production or stabilising ore feed to the plant. These operational phases (pushbacks) are converted into an executable strategic schedule using phase bench scheduling (PBS). The PBS model converts the optimised extraction sequence (block based) into operational mining units, benches within each phase. In addition to the DBS constraints, limitations on annual CAPEX expenditure, precedence between purchases, and the replenishment of capital items are included in the optimised operational schedule. The contribution is a practical, capital planning ready workflow: start with DBS (BZ accelerated), derive clustered phases, enforce PBS under realistic sink rates and blend constraints, and evaluate incremental plant investments and logistics options. For mine operators seeking funding for expansion, this workflow connects optimisation to execution and demonstrates credible value uplift with defensible assumptions.