This is a new section of the PPPLRC website and is currently in draft form.  Your feedback is welcome: If you would like to comment on the content of this section of the website or if you have suggestions for links or materials that could be included please contact us at ppp@worldbank.org.

Poor Planning and Project Selection

Photo Credit: Image by Pixabay

Scarce resources are too often spent on poorly-selected projects that fail to achieve benefits commensurate with their cost. The result can be under-used assets and poor service delivery at a higher cost than necessary. These systematic problems result from:

  • Poor planning and coordination—good sector and cross-sector planning and coordination are needed to ensure that the best projects—those that represent good value for money, enable integrated regional development, and provide customers with the services they desire—are consistently selected. Without sound plans, responsible agencies will not have the full view of potential projects that could be implemented, will not know the sequence in which to implement the projects to achieve the best value for money, and cross-sector coordination will be weak. Mumbai Water—Example of Poor Planning in Infrastructure provides an example of how weak infrastructure planning can mean projects fail to achieve value for money. The 2016 McKinsey report on infrastructure investment (Woetzel et al. 2016) identifies $49 trillion required globally between 2016 and 2030 to approach fulfilling infrastructure needs. The 2013 McKinsey Report on infrastructure productivity (Dobbs et al. 2013) notes that scaling up best practice could save an average of $1 trillion a year in infrastructure costs during that period.
  • Flawed analysis—the analysis underpinning project selection is often flawed, so projects that appeared to be cost-benefit justified turn out not to be so in practice. Benefits are often overestimated, resulting in projects that are larger or more complex than is justified by demand for services, while costs are often under-estimated. The United Kingdom Government's Green Book on project assessment (UK 2011a, 29–30) acknowledges this as a systematic problem and highlights the need to correct for optimism bias in project analysis. UK Treasury supplementary guidance on optimism bias (UK 2015a) presented evidence on the extent of optimism bias dating from the early 2000s. A global series of studies of large transport projects by Flyvbjerg—(Flyvbjerg et al. 2002); (Flyvbjerg et al. 2003); (Flyvbjerg 2005); (Flyvbjerg et al. 2005)—found that costs are systematically underestimated, and benefits often overestimated:
    • A study of 258 transport projects found that actual costs were on average 28 percent higher than planned costs—and 65 percent higher on average for projects outside Europe and North America.
    • A study of 25 rail projects found traffic was heavily overestimated, at over twice actual traffic, on average. The accuracy of traffic forecasts for 183 road projects was also found to be highly variable, but without a tendency to overestimate.

Additional evidence and analysis on estimation bias is presented in Australia’s report on overbidding for toll roads (AU 2012).

  • Politics or personal gain interfering with the project selection process; increasing costs, or diverting funds to less beneficial projects. An IMF analysis of corruption in public investment in infrastructure (Tanzi and Davoodi 1998) found corruption tends to create a bias towards capital spending projects, and increase their size and complexity—reducing the productivity of that investment.

The IMF report on infrastructure efficiency (IMF 2015a), focusing on the quality of investment, instead of its volume, identified average inefficiencies in public investment processes of around 30 percent across countries, according to their estimates, better public investment management could increase investment expenditure by as much as two-thirds of the estimated additional needs.

These factors often feed into each other. For example, weak analysis or poor planning can enable badly-chosen projects to be pushed through for political or personal gain, as described in the World Bank's sourcebook on deterring corruption in the water sector (WB 2008, Chapter 6). Flyvbjerg's studies (Flyvbjerg 2005) also emphasize, with examples, that costs and benefits can be deliberately misrepresented, to push through projects for political or organizational reasons.

Mumbai Water—Example of Poor Planning in Infrastructure

The experience of the Municipal Corporation of Greater Mumbai provides an example of weak planning in the water sector. The Corporation was looking for ways to improve the efficiency of its operations. Mumbai is short of water, with supply rationed to around four to six hours a day in most parts of the city. Corporation planners were working on new schemes to transport water from hundreds of kilometers outside the city. Consultants engaged through the World Bank analyzed the cost of achieving a 24-hour water supply in one ward (K-East) entirely with new supply, and compared this with the cost of achieving 24-hour water supply through improving the distribution system to reduce leakage and theft. The consultants estimated that the cost of distribution improvements would be one sixth or less of the cost of bulk supply increments, for the same level of service improvements. The size of the discrepancy suggests that the Municipal Corporations’ planning had been biased toward large projects.

Source: (Kulkarni 2008)

How PPPs can help—project assessment and design

Under the right circumstances, PPPs can help improve infrastructure project selection, by harnessing the analysis and ideas of private sector investors, whose financial returns depend on getting cost and revenue forecasts right.

Private investors and lenders undertake their own project analysis based on their experience and strong, profit-driven incentive to assess benefits and costs. Lenders to project finance transactions, in particular, carry out extensive project due diligence, as described in How PPPs Are Financed. A 2002 Standard and Poor's study (Bain and Wilkins 2002) found that traffic forecasts for toll roads commissioned by banks tended to be less optimistic than those commissioned by other agencies, including developers and governments, although still biased on average. Guarantees on the debt of the private party, or lax termination payments, may reduce lenders’ due diligence efforts, therefore reducing this relevant source of value for the public sector.

The PPP tender process can therefore act as a filter for non-viable projects. As described by Engel, Fischer, and Galetovic (Engel et al. 2009), if the private sector sponsor and lenders are asked to shoulder revenue and cost risks under a PPP, a non-viable project may simply not attract private interest. For example, a McKinsey report on infrastructure challenges in India (Gupta et al. 2009, 25–27) notes that several of the National Highways Authority of India (NHAI)'s toll road projects did not attract bidders—in some cases demand forecasts were too high; in others, bidders found NHAI's cost estimates to be low, and the project not viable on more conservative cost assumptions. Conversely, Engel, Fischer and Galetovic (Engel et al. 2009) note that if the government is bearing a risk—for example, by providing a demand guarantee—then a non-viable project could still be profitable for the private partner, reducing the filtering ability of PPPs.

Experienced private companies can also be well-placed to identify infrastructure needs, and come up with innovative ideas to meet them. Accepting unsolicited proposals for PPP projects from private companies can be a way to capitalize on these ideas. While unsolicited proposals can be a useful source of ideas to improve project selection, they need to be subject to the same analysis and competitive procurement as other major government investments. Dealing with Unsolicited Proposals describes how some governments have introduced policies to encourage unsolicited proposals, while subjecting them to rigorous analysis and competition.

PPP limitations and pitfalls—poor planning and project selection

While the PPP process can provide more information and additional analysis to inform project selection, the government remains responsible for choosing which projects to implement and which procurement method to use. This limits the extent to which PPPs can help improve project selection. Indeed, PPPs may even distort investment priorities—low priority projects may go ahead simply because they are easier to do.

Foremost, PPPs do little to improve planning. Where PPP projects initiate from government, private companies can only respond by avoiding projects that do not appear viable, as described above. By then, considerable time and resources have already been invested in the planning phase. Where PPP ideas are generated by private investors, the projects may not be aligned with the government’s investment priorities and the unsolicited proposal may exacerbate weaknesses in planning and coordination between sectors or across regional boundaries. Also, in generating project ideas, private firms focus in those that are financially viable, but may not propose economically beneficial projects that would require government contributions.

If a PPP program is not well designed, the inflexibility of resulting PPP contracts may create sector planning challenges. As described in the United Kingdom House of Lords' review of the PPP program (UK 2009, 28–29), PPP projects constitute a long-term commitment, which can be expensive to change if needs change (or were misunderstood in the first place). Although changes in traditional public procurement also imply added costs, these are typically lower than under a PPP, since the absence of long-term contractual commitments allows easier recourse to the market and competitive pressure.

There are limitations on the extent to which PPPs can improve project analysis. First, the private sector is not immune to optimism bias. The Standard & Poor’s (S&P’s) (Bain and Wilkins 2002) analysis mentioned above shows lenders make more realistic assumptions than public agencies—nonetheless they still overestimate traffic forecasts. The more conservative traffic forecasts commissioned by banks still overestimate traffic by almost 20 percent—see (Bain and Polakovic 2005). In Spain (Vassallo et al. 2012), traffic estimates by concessionaires that were awarded several PPP toll road contracts have proven to be even more optimistic—revenue generated by the companies could barely cover the interest of the outstanding debt.

Secondly, where the private party to a PPP is not bearing traffic risk, or other project risks, the incentive for rigorous analysis is weaker. PPP structures can even weaken government incentives for rigorous analysis, by obscuring the costs and risks the government bears (see the pitfalls described under Insufficient Funds).

Finally, PPPs can provide an opportunity for corruption, which may bias project selection. Where project selection is not based on analysis but rather influenced by corruption or pursuit of political gain, PPPs are also likely to be affected. Guidance on assessing corruption risk, and mitigating it, is provided in a series of World Bank sourcebooks on governance in the water (WB 2008), electricity (WB 2009b), and roads (WB 2009c) sectors. Lack of a proper Public Investment Management system, as well as the existence of a parallel selection process exclusively for PPPs, create additional opportunities for mismanagement and corruption—Anand Rajaram et al’s book on the power of Public Investment Management (Rajaram et al. 2014) presents good practices in this field, and includes a chapter on PPPs (Chapter 7).

The policies and processes presented in Establishing the PPP Framework and PPP Cycle of this Reference Guide, and in the references listed, can help governments avoid the planning and project selection challenges that can undermine the effectiveness of PPP projects.

Note(s):

Find in pdf at PPP Reference Guide - PPP Basics or visit the PPP Online Reference Guide section to find out more. 

Download Page as PDF


Updated: June 23, 2022