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Case Study (excerpt)
Managing long-term risks: what is the probability of economic
success for major infrastructure projects?
1.
The situation
Capacity constraints in air travel and significant latent demand for service
between two major cities triggered the plans of a major transportation authority to
conduct a pre-feasibility study on a High Speed Rail (HSR) connection between
those two cities. The High Speed Rail link is envisioned to significantly improve
the regional transportation infrastructure and to transform the economic and
social development of the region.
The focus of the assessment did not center on strategic options and the
FlexValue – the main strategic options like route alignment, potential stop options
and investment timing had been pre-determined based on overall socioeconomic and political considerations. An assessment focused on the project’s
risk, and the client ultimately wanted to know the project’s most likely financial
outcome.
2.
Calculating the project’s NPV
After the preliminary decisions regarding route alignment, terminals and
intermediate stops had been made, a comprehensive assessment of demand
was conducted based on extensive market surveys, industry benchmarks and
expert interviews. The demand assessment was one of the key variables in the
pre-feasibility study, as it would reveal which segment of the population would
derive a benefit from the project and, accordingly, would be a major driver of the
financial business case.
Based on the demand assessment and assumptions about future ticket prices, a
revenue projection spanning the next 50 years was derived. Based on this
projection as well as further industry benchmarks, fixed and variable operating
costs were forecasted for the same period. An extensive evaluation of the route
and technical factors then led to the estimation of the total CAPEX for the
construction, renewal and replacement of the High Speed Rail link.
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The financials were then summarized in a free cash flow projection (see figure
1.1).
Figure 1.1: Free cash flow projection
3.
Summary
The starting point of our analysis was to build a traditional financial model based
on revenue, OPEX and CAPEX estimates. On top of that, we then carried out an
in-depth analysis of the various corresponding risks. By including those data in
our analysis, we calculated the RiskValue and derived a probability distribution
for all potential financial project outcomes. Therefore, we were able to assign a
probability to our long-term bet on the financial outcome of the infrastructure
project.
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4.
Our results contrasted with the DCF method
Figure 1.2: Scenario Analysis
In addition to the RiskValue calculation, we also carried out a traditional scenario
analysis calculating a Worst Case, Expected Case and Best Case. While the
Worst Case showed a negative NPV, the Best Case exceeded the Expected
Case’s value by over 20%. Based on qualitative discussions, lump-sum
probabilities were then assigned to the three cases. While this analysis produced
some valuable insights, the probability of each case was purely based on gut
feeling. This was of particular concern since the team expected major risks in
terms of revenue, OPEX and CAPEX which could change the entire dynamics of
the business case. Also, the traditional scenario analysis gave us only three
potential outcomes – ignoring many other potential results that we were able to
evaluate using the RiskValue approach.
Ultimately, the RiskValue approach gave us a clear indication of what the most
likely outcome of the investment case would be. It therefore increased decision
making quality substantially, helping the client to make a well-substantiated
decision – and not a reckless bet on a highly uncertain future.
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