Items where Keyword is "cost overruns" (Publications and Working Papers)

In this paper we characterise the propensity of big capital investments to systematically deliver poor outcomes as "fragility," a notion suggested by Nassim Taleb. A thing or system that is easily harmed by randomness is fragile. We argue that, contrary to their appearance, big capital investments break easily — i.e. deliver negative net present value — due to various sources of uncertainty that impact them during their long gestation, implementation, and operation periods. We do not refute the existence of economies of scale and scope. Instead we argue that big capital investments have a disproportionate (non-linear) exposure to uncertainties that deliver poor or negative returns above and beyond their economies of scale and scope. We further argue that to succeed, leaders of capital projects need to carefully consider where scaling pays off and where it does not. To automatically assume that "bigger is better," which is common in megaproject management, is a recipe for failure.

The academic literature and popular press has chronicled large IT project failures for the last 40 years. Two points of contention surround this debate. First, quantitative studies found mixed support of a wide-spread crisis, questioning the representativeness of failure cases. Second, organizational theories disagreed on underlying assumptions about the nature of uncertainty, in particular about stability, locus of control, and controllability of the causes of IT project disasters. To advance the understanding of these two gaps four hypotheses were tested with a sample of 4,227 IT projects. The findings showed that outliers are stable phenomena following power laws, occurrence and impact of outliers differs between public and private sector, benefits management is associated with thinner tails and lower risk, and agile delivery methods do not statistically significantly influence the thickness of the tails. In sum, outliers are stable and non-random phenomena. They matter more than medians or means when it comes to IT project risk. Second, the notion of outliers bridges the gap between qualitative and quantitative studies. The findings also show that causes of outliers are, at least to some extent, internal and controllable by organizations. Lastly, the paper draws implications for organizational decision-making, learning, and risk management.

This paper examines three independent explanatory variables and their relation with cost overrun in order to decide whether this is different for Dutch infrastructure projects compared to worldwide findings. The three independent variables are project type (road, rail, and fixed link projects), project size (measured in terms of estimated costs) and the length of the project implementation phase. For Dutch projects, average cost overrun is 10.6% for rail, 18.6% for roads and 21.7% for fixed links. For project size, small Dutch projects have the largest average percentage cost overruns but in terms of total overrun, large projects have a larger share. The length of the implementation phase and especially the length of the pre-construction phase are important determinants of cost overruns in the Netherlands. With each additional year of pre-construction, percentage cost overrun increases by five percentage points. In contrast, the length of the construction phase has hardly any influence on cost overruns. This is an important contribution to current knowledge about cost overruns, because the period in which projects are most prone to cost overruns is narrowed down considerably, at least in the Netherlands. This means that to determine the causes and cures of overruns one should focus on the period.

The article first describes characteristics of major infrastructure projects. Second, it documents a much neglected topic in economics: that ex ante estimates of costs and benefits are often very different from actual ex post costs and benefits. For large infrastructure projects the consequences are cost overruns, benefit shortfalls, and the systematic underestimation of risks. Third, implications for cost–benefit analysis are described, including that such analysis is not to be trusted for major infrastructure projects. Fourth, the article uncovers the causes of this state of affairs in terms of perverse incentives that encourage promoters to underestimate costs and overestimate benefits in the business cases for their projects. But the projects that are made to look best on paper are the projects that amass the highest cost overruns and benefit shortfalls in reality. The article depicts this situation as ‘survival of the unfittest’. Fifth, the article sets out to explain how the problem may be solved, with a view to arriving at more efficient and more democratic projects, and avoiding the scandals that often accompany major infrastructure investments. Finally, the article identifies current trends in major infrastructure development. It is argued that a rapid increase in stimulus spending, combined with more investments in emerging economies, combined with more spending on information technology is catapulting infrastructure investment from the frying pan into the fire.

Despite the hundreds of billions of dollars being spent on infrastructure development — from roads, rail and airports to energy extraction and power networks to the Internet — surprisingly little reliable knowledge exists about the performance of these investments in terms of actual costs, benefits and risks. This paper presents results from the first statistically significant study of cost performance in transport infrastructure projects. The sample used is the largest of its kind, covering 258 projects in 20 nations worth approximately US$90 billion (constant 1995 prices). The paper shows with overwhelming statistical significance that in terms of costs transport infrastructure projects do not perform as promised. The conclusion is tested for different project types, different geographical regions and different historical periods. Substantial cost escalation is the rule rather than the exception. For rail, average cost escalation is 45% (SD=38), for fixed links (tunnels and bridges) it is 34% (62) and for roads 20% (30). Cost escalation appears a global phenomenon, existing across 20 nations on five continents. Cost estimates have not improved and cost escalation not decreased over the past 70 years. Cost estimates used in decision-making for transport infrastructure development are highly, systematically and significantly misleading. Large cost escalations combined with large standard deviations translate into large financial risks. However, such risks are typically ignored or underplayed in decision-making, to the detriment of social and economic welfare.