Why feasibility studies fail

There is no international agreement on the terminology for each stage of feasibility study and there is no agreed standard for quality or accuracy. The AusIMM’s Monograph 27, Cost Estimation Handbook (second edition 2012) provides a set of standards that may become more widely used.

Surveys of many studies reported by RL Bullock in 2011 reveal that accuracy ranges are:

  • Scoping -50% to +30%
  • Prefeasibility -27% to +30%
  • Feasibility -20% to +27%
  • Detailed engineering -12% to +20%

These ranges are wider than generally understood but are constrained by what is practical. For example, many people expect a feasibility study accuracy to be +/- 10% but this is rarely achievable other than within the constrained boundary of the processing plant. Estimates for mining and infrastructure are much less reliable. It takes twice as much effort (and cost) to reach +/- 10% as it does to reach +/- 15%. Bullock also reported that the average capital overrun (over the last 50 years) was 26%, with no evidence that estimation accuracy has improved over that period despite the use of computers. The average overrun has been worse in recent years due to rapid cost escalation, but has probably now stabilized. There have been many studies over the years that reveal the generally poor performance of feasibility studies.

A feasibility study should be considered a failure if:

  • The capital cost is higher than expected
  • The operating cost is higher than expected
  • The recovered grade is lower than expected
  • Sales revenue is lower than expected
  • It takes longer to build and ramp up than expected
  • Initial performance cannot be sustained, though it may take several years for the failure to become evident.

AMC data suggests that around 25% of projects fail, a further 20% perform better than expected and the remaining 55% perform more or less as expected. There is no apparent difference in performance between junior and major companies, large and small projects, or locations around the world. Common causes of failure are:

  • Mine design and scheduling
    • Over-optimistic ramp-up schedules
    • Learning curve not considered
    • Over-optimistic production schedules
  • Geology, resources and reserves estimation
    • Inadequate attention to local variability
    • Statistics and modelling override common sense
  • Metallurgical testwork, sampling and scale-up
    • Metallurgical domains within the orebody not understood
    • Testing is done on unrepresentative composites
    • Failure to identify process contaminants
    • Inability to handle ore types as per mining schedule
    • Process water chemistry differs with lab

Often, the root cause of failure is an inadequate understanding of the geology of the deposit. In general, failure of a feasibility study can be attributed to inadequate resources or human factors.

  • Inadequate resources
    • time (and artificial deadlines) or skipping stages
    • budget
    • availability of skilled personnel for studies and for construction  management (or poor choices made)
  • Human factors
    • prescient CEO syndrome (already announced the answer)
    • the innate drive to make it work, when it doesn’t (corporate momentum)
    • pressure to make it work, when it doesn’t (stretch targets)
    • the consulting firm fee cycle (agree or we won’t pay for work already done)
    • study is a loss leader for an EPCM engineer (if feasible, we build)
    • structure and timing of bonuses to executives, project managers, consultants and bankers (long gone before the truth emerges)
    • confirmation bias (I only accept what fits my existing beliefs)
  • The average operating company has limited experience in developing projects, often has cut back or eliminated corporate engineering staff and usually does not involve experienced project managers in preparing the execution plan in the feasibility study. Cost overruns sometimes occur because substantial owner’s costs are overlooked in the study. These include cost for the owner’s employees, financial fees, interest charges, insurances, and legal and consulting fees. Contingency amounts are often inadequate. These are amounts that will be spent, it is just not possible to identify where they will be spent at the time the study is prepared. Based on many examples, the average contingency allowance across a feasibility study is 13%.To improve the performance of studies they should receive increased scrutiny through peer review and audit. Allocation of time and budget for studies must be adequate. There should be an independent audit of data gathering and analysis for each step in the study process. The formal process of risk assessment might include peer review by a specialist team that has no interest in the project outcome. More use should be made of benchmark data from existing operations. The AusIMM Cost Estimation Handbook is an excellent resource for anyone working on a study.The scope of work must be “is it feasible?” and not “make it feasible”, because sometimes the answer is “no”. “Not feasible” is a function of orebody, location and market conditions. It does not mean the study team are nincompoops. It does not mean the study budget was wasted. It is better learned from a study than from experience.