Customers & Industries: Slovak Rail Company

European Investment Bank Recommends @RISK to Determine Feasibility of Railway Capital Investments

  • Industry: Transport
  • Product(s): @RISK
  • Application: Capital Investment

Summary

Palisade’s risk analysis software, @RISK, was recommended by the European Investment Bank for the task of modelling potential train travel over the next 30 years for the Slovak Rail Company.

@RISK was recommended as a result of its excellent track record with a wide variety of other projects. Flexible and fast, it was also the only decision support tool that enabled the complex modelling and depth of risk analysis that was required to provide an informed view of the overall risk presented by SRC’s investment proposals.
Jozef Dančo, Consultant, Eurotarget

In 2005, Rail Slovakia, which had been operating for more than 160 years, was split into the Slovak Rail Company (SRC) and Slovak Cargo. SRC, which is the country’s only state-owned public transport organisation, is responsible for national, regional and suburban passenger rail transport.

In order to continue to provide a viable rail transport system, SRC’s rolling stock required modernisation, with end-of-life vehicles being replaced by double-deck electric or diesel units. However, a key risk in undertaking this task was that the dwindling passenger numbers opting for rail travel would result in revenues not being high enough to warrant the investment in new carriages. The Slovakian Ministry of Transport, Ministry for Finance and the SRC, all of whom were to co-finance the project with the EU regional finance fund, required a risk-based methodology to be used before it committed to going ahead with the project.

Palisade’s risk analysis software, @RISK, was recommended by the European Investment Bank for the task of modelling potential train travel over the next 30 years. The EU Commission also confirmed that the SRC could use this method of decision support to determine whether investing in new rolling stock was feasible.

@RISK Used to Determine Revenues

The first task was to use @RISK to ascertain whether buying new rolling stock would have a positive or negative outcome on SRC’s revenues. Revenue-related inputs to the @RISK model centred round rail fares (with expected increases taken into account), state subsidies and trends in passenger numbers. Historical data was used to help predict future train use, along with the effects of revised timetables (aimed at making trains more frequent and convenient in order to encourage people to make journeys by train), and the outcome of introducing the new carriages. This was balanced with inputs relating to operational costs such as materials, energy, salaries, rail track charges and repair and maintenance cost.

In addition, inputs to @RISK included the results of the experience of Slovakia’s neighbours. The Czech Republic, Hungary and Austria, all of whom had seen passenger numbers increase somewhat as a result of updating their rolling stock.

@RISK Calculates Socio-Economic Impact of Increased Rail Use

In addition to modelling the financial feasibility of investing in new carriages, SRC needed to look at the socio-economic impact of people taking more journeys by train.

The main competitor to rail transport is travel by car, which is seeing a seven to eight percent increase per year in terms of journeys taken and the number of vehicles on the road in Slovakia. (As indicated, a key factor influencing this growth is that train timetables are often inconvenient and result in long waits during rail journeys).

SRC’s revised strategy of new carriages and upgraded timetables was predicted to result in several positive benefits. The increased number of trains would reduce both waiting times and the number of changes required during one trip, making train travel more attractive. In addition, there was evidence that some travellers would be prepared to pay more for the comfort afforded by the modern carriages. These factors all served as inputs to the @RISK model.

The ‘damage’ caused by car journeys was also modelled by @RISK. Historical road statistics were used to calculate the reduction in traffic accidents as a result of more people using the safer option of the train. In addition, the environmental impact of fewer car journeys, such as a reduction in pollution, was factored into the @RISK model, along with the decrease of operational costs as a result of less road use reducing the necessity of repairs.

Socio-Economic Benefits of Train Travel Justify Investment

The financial modelling set out to determine whether the investment in new rolling stock could be justified in terms of increased revenues for the SRC. Despite some uptake in passenger journeys, it showed that the rail company would not be profitable and the system would therefore need subsidies.

However, when investigating the socio-economic impact of the investment, the outcome was always positive. In other words, investing in the rail upgrade was worthwhile because it resulted in obvious advantages in terms of better quality journeys, fewer car accidents and less pollution.

As a result of SRC using @RISK to enable informed decision-making, the European Union and Slovakian Ministry of Transport approved the investment in its new rolling stock. Some carriages are now in operation, and all 32 new units will be in use by 2013.

@RISK Presents the Overall ‘Risk Picture’

Working for Eurotarget, a business consultancy that advises SRC and the Slovakian Ministry of Transport, Jozef Dančo was a consultant on SRC’s project. He explains: “@RISK was recommended as a result of its excellent track record with a wide variety of other projects. Flexible and fast, it was also the only decision support tool that enabled the complex modelling and depth of risk analysis that was required to provide an informed view of the overall risk presented by SRC’s investment proposals.”

Additional Information

Distribution used: Normal distribution. Both the probability of number of passengers and the cost/price probability could be represented by the ‘bell’ curve, so normal distribution was used.

Illustrations: Total revenues are calculated from the number of passengers and the fare, but the fare is considering to change in intervals only.

@RISK output report for FNPV (Financial Net Present Value):

Have Questions? Talk with us.

Contact Us