# **_4.2 Demonstration of Robust Decision Making_**

Robust Decision Making can help us more fully understand the strengths and weaknesses of our options and make a sound decision, without relying on accurate predictions of the unpredictable future. It helps us answer several useful questions:

1. How do our options perform across a wide range of potential future conditions?

2. Under what specific conditions does the _rehabilitating the existing plant_ fail to meet our goals?

3. Are those conditions sufficiently likely that we should choose a different _energy investment_ option?

In practice, these questions are addressed in a close collaboration between decision makers, stakeholders, and analysts. A series of structured workshops help participants frame the analysis, deliberate over interim findings and direct subsequent analyses, and reach decisions. Because we are re-creating an earlier project analysis, we focus in this section on the analytical steps and draw on the outcomes of stakeholder engagement in the original project.

## **Structuring the Problem**

To conduct the RDM analysis, we first structure our analysis to more fully identify the uncertainties we face. In this study, we used the same uncertainties as in the original analysis, but in nearly all cases, we have expanded the range of possible values as shown in column D of Table 1. Figure 1 shows this visually for the option of rehabilitating the existing plant. The values’ ranges were drawn from the literature and historical data, and from consultations with energy experts. For example, literature on investment planning biases suggests that on average, capital costs are underestimated by 28% (Siemiatycki, 2010). World Bank energy experts confirmed that for a comprehensive thermal rehabilitation project, cost overruns of 50% are possible. Hence, we considered a range of capital costs from a lower bound of just below each option’s stated cost, to an upper bound of 150% of the stated cost.

We also added two new uncertainties: the length of construction time and discount rate. The length of construction time is an uncertain and important parameter. Most projects experience delays in implementation (Ahsan and Gunawan, 2010). Indeed, the original analysis identified possible delays in rehabilitation and construction as plausible risks. Moreover, decision makers were concerned with how quickly each option could be implemented and would begin producing electricity.

<mark>The discount rate is also deeply uncertain. It is a political choice and often highlycontested (Arrow et al., 2013). It shapes how we allocate resources between the present and the future (Gollier, 2011). A higher discount rate signifies an urgency to satisfy present needs, whereas a lower discount rate expresses concerns for the long-term impacts of an investment. Although the World Bank typically uses discount rates of 10% to 12%, no single discount rate is appropriate for all projects and it may be difficult for stakeholders to come to consensus (Hoekstra, 1985; Oxera, 2011). After consultation with World Bank experts, we use a range from 1 to 20% to explore both the longer-term considerations of contributing to the country's growth and the short-term objectives of avoiding an energy crisis.</mark> 10