The high rate of failure of new mine developments to meet feasibility study expectations has been the subject of many fine technical papers. Yet failure rates remain stubbornly high._x000D_
Similarly, the common occurrence of disastrous acquisitions resulting from failed due diligence on projects is well known. Yet such mistakes continue to be made._x000D_
The authors argue that project and due diligence failure are caused at least partly by cognitive biases. These biases pervade decision-making throughout project evaluations._x000D_
A wider understanding of these biases (and their effects) is necessary. Only then can mitigating actions be taken._x000D_
The opportunity for this wider understanding exists. A number of best-selling books have been published on the topic in recent years. With wider understanding of key concepts and terms, cognitive biases can be recognised and discussed. They can also be challenged and mitigated._x000D_
The authors believe that these concepts should be entry-level, required knowledge for anyone evaluating, developing, reviewing or financing mining projects._x000D_
Perhaps the most prevalent biases in project evaluation failure are the over-optimism' biases. In particular, the planning fallacy and confirmation bias._x000D_
The anchoring effect is also pervasive. This bias propagates unrealistic assumptions from scoping and prefeasibility studies through to so-called definitive feasibility studies. Unrecognised anchoring biases also undermine the validity of many independent' due diligence reviews. They are also prevalent in corporate acquisitions._x000D_
The availability heuristic refers to a mental shortcut that can lead to a number of biases. One of these is the narrative fallacy. The mind constructs coherent narratives and opinions, regardless of the amount and quality of the information that support them. Narrative fallacy commonly occurs in the evaluation of social and political risk. Another is disaster neglect, which is especially common in the failure to assess risks associated with tailings management._x000D_
This paper outlines the relevance of these biases to mine project evaluations. It also provides examples where the authors have observed their effects._x000D_
CITATION: Love, S, Boland, M and Anderson, M, 2016. Influence of cognitive biases on project evaluation, in Proceedings Project Evaluation 2016, pp 226-235 (The Australasian Institute of Mining and Metallurgy: Melbourne).