FOR CAPITAL OWNERS, BOARDS AND TRANSFORMATION SPONSORS
A full-potential programme can improve every cost centre and still reduce mine-wide value.
Composite benchmarks and department-by-department savings can produce an attractive EBITDA model while removing the protective capacity required to deliver stable saleable tonnes.
THE UNDERWRITING RISK
Does the target describe a mine that can actually operate?
A benchmark can show what one function achieved under particular conditions. It does not prove that the lowest costs or highest productivity figures from several different operations can all be achieved together in one operating system.
When that synthetic target is converted into resource reductions while the production commitment remains unchanged, the mine may lose the protective capacity required to absorb normal variability. The local saving appears immediately; the lost throughput arrives later and is often attributed elsewhere.
• Which real mine has demonstrated the complete target—not merely each component separately?
• What operating conditions and supporting resources enabled each benchmark result?
• Which people, equipment, spares, work fronts or buffers would be removed?
• How would the proposal affect constraint run time, starvation, blockage and production variability?
• What happens to saleable tonnes, cost per tonne and EBITDA if the proposed saving reduces throughput?
THE MINE THAT NEVER EXISTED
REAL NUMBERS. SYNTHETIC MINE.
A full-potential model may select the lowest mining cost from one operation, the smallest maintenance complement from another, the highest plant rate from a third and the lowest support cost from a fourth. Every number may have been achieved somewhere; no operation may have achieved them together.
The resulting target can look rigorous because every input has a source. But it describes a portfolio of attractive parts—not a production system that has demonstrated stable saleable tonnes.
Benchmarking remains useful as inquiry. The risk begins when decontextualised comparisons become simultaneous cost and resourcing targets without testing their effect on whole-mine flow.
Why a conventional MOS may not resolve the problem
1 — Essential governance
Separate the stable average, repeatable best performance, variability and budget. Do not treat one record day as capability.
2 — Local KPIs can fragment the mine
When departments are measured independently on cost, utilisation or activity, every function can report green while the system constraint is starved or blocked.
3 — Reviews often explain yesterday
Variance reviews support learning, but they may not coordinate the cross-functional decisions required to protect flow over the next 12 to 48 hours.
4 — The Flow Room adds the missing layer
Shared constraint data, buffer signals and decision rights allow departments to coordinate around mine-wide throughput. The Flow Room completes the MOS; it does not replace it.
How local savings can destroy mine-wide value
STEP 1 — Separate results become one target
The lowest costs and highest productivity figures from different mines, departments
or periods are assembled into one “full-potential” target without preserving the conditions that produced them.
STEP 2 — The gap becomes a resource reduction
People, contractor hours, equipment, spares, inventory, work fronts or buffer capacity are reduced while the mine’s production commitment remains unchanged.
STEP 3 — Variability reaches the constraint
Without sufficient recovery capacity and buffers, ordinary disruptions propagate through the production chain. The constraint is repeatedly starved or blocked and the operating plan must constantly be repaired.
STEP 4 — The saving reappears as lost value
Saleable tonnes become less predictable, fixed costs are spread over lower output and cost per tonne rises. The visible departmental saving can be overwhelmed by lost mine-wide contribution and EBITDA.
When capital owners should challenge the full-potential case
This approach is most useful when:
• an acquisition, turnaround or investment case depends on substantial operating improvement
• the financial model assumes lower operating costs and similar or higher production at the same time
• targets combine benchmarks drawn from different mines, departments or operating periods
• resource reductions are proposed without identifying the system constraint or required protective capacity
• departmental KPIs are green while saleable tonnes, cost per tonne or cash flow remain below expectation
• a previous transformation programme produced improvements that did not hold
EVIDENCE DISCIPLINE
Benchmarking and Management Operating Systems are not inherently harmful. The risk arises when decontextualised functional targets are converted into simultaneous resource reductions without testing their effect on the whole production system. Evidence strongly supports the importance of operating context, buffers, variability, starvation and blockage; the complete benchmarking-to-balanced-capacity pathway remains a testable hypothesis. Stratflow’s historical intervention record includes improvements in the 10–40% range, but this is context—not a forecast or guarantee for any individual asset.
START WITH ONE OPERATING ASSET
Bring the full-potential claim, the benchmark assumptions and a de-identified operating data series. We will test whether the proposed cost and resource configuration can deliver stable mine-wide flow under normal variability and whether a contained operating experiment is justified.