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S-ROI Metric Enables Triple-Bottom-Line Decision-Making
September 18th, 2012
In many organizations, sustainability and finance professionals are struggling to reconcile the need for consistent financial returns with sustainability-related pressures from stakeholders both inside and outside the firm.
Sustainability Return on Investment, or S-ROI, bakes in the ability to measure the social, economic and environmental returns on sustainability initiatives. The S-ROI methodology, sometimes called Total Cost Assessment (TCA) for its ability to include external costs when calculating return on sustainability-related investments, allows for the enumeration of uncertain events with their concurrent costs and benefits.
The decision-maker obtains a financial picture of the future of a decision that includes best-case, worst-case, and most probable ranges of return on investment. The output takes into account both internal costs (those borne by the company) and external costs (those borne by society), allowing decision-makers to use both aspects as appropriate.
Although it comprises a new sustainability metric, S-ROI also relies on traditional communication — brainstorming and interaction between key stakeholders that maintain a vested interest in the decision.
By enabling expert stakeholders to engage in a decision-making process, the S-ROI methodology is designed to avoid the bias that comes from completing decision analysis in a vacuum or optimizing a decision around one type of cost or benefit. "In the US, we often want to avoid any metrics that have a lot of uncertainty or value judgments built in. Unfortunately that either leads to paralysis or all decisions being based on one metric,” says Lise Laurin, founder of sustainability consultancy EarthShift and one of the key minds behind the development of S-ROI.
The S-ROI output gives key decision makers across functions the actionable information they need to justify various forms of investment in socially and environmentally responsible activity, while avoiding “burden shifting,” where one harmful impact is simply traded for another.
In many cases, decision-makers use the S-ROI methodology to determine whether there is a business justification for initiatives that don’t show a positive ROI based on traditional costing methods.
For instance, Laurin points to a feasibility study that she conducted with the Japanese government’s National Food and Agriculture Organization to assess the long-term viability of building a biogas plant. The study assembled representative experts from four main stakeholder groups: crop farmers, the community, the broader economy, and the biogas facility itself.
During the assessment, the team of experts identified several risks and potential benefits, each associated with a potential dollar amount. Because each scenario has an uncertainty associated with it, the results of the study reflect the likelihood of each cost occurring.
The first risk was insufficient demand for liquid bio-fertilizer, which would require additional marketing investment. Other risks, such as clogging or other equipment damage, were also treated strictly as economic costs. Even social aspects, such as the community demanding odor control or limiting expansion, were treated in traditional economic terms, with a potential cost and probability.
Some scenarios identify potential benefits rather than costs. For instance, proposed regulations could potentially enable the sale of methane gas for power production at a higher profit than anticipated.
External intangible costs and benefits are more difficult to assess. By allowing wide ranges of probabilities and costs, these intangibles can be included and their impacts understood from a broad perspective.
In the case of the biogas plant, the project provided a positive return for all stakeholders. The graph that follows shows the results of the analysis after 20 years for each major stakeholder, with a range of probabilities included for sensitivity analysis.
S-ROI uses traditional cost accounting principles to fit within corporate and governmental financial planning systems. In the biogas plant study, Monte Carlo analysis was used to calculate the Net Present Value shown above.
In a Monte Carlo analysis, a computer simulates what is going to happen in the future. For each run, or each “future,” the probability of any scenario is calculated as “going to happen” or “not going to happen.” If the probability is high, the scenario will happen more often (in more of the runs). If the probability is low, it will happen less often. For instance, in the example above, the moderate possibility of clogging or other equipment damage would add additional costs of several million yen to approximately 40% of the runs, and 0 additional cost for the remaining runs.
The costs associated with each scenario are then calculated based on the uncertainty curve associated with them. Once all the capital and non-capital costs (and benefits) have been calculated for each “future,” after-tax net cash flow is calculated as follows:
Depreciable (capital) costs - (1-tax rate) * other costs + (tax rate * depreciation)
After-tax net cash flow with respect to baseline is calculated as follows:
After-tax net cash flow (costi , option j) - After tax net cash flow (cost i, baseline), where i is the cost of interest and j is the option being calculated.
Net Present Value is calculated as follows:
For years t=0-n, Sum [After-tax net cash flow with respect to baselinet/(1-discount rate)*t]
The graph is charted from the results of multiple futures (in this case, 1000 runs for each stakeholder). The full range is shown in pink, a 90% probability is shown in blue, 50% probability in orange and the mean and median result shown as dark blue and black lines. According to the analysis, even in the worst case, all stakeholders will be profitable. Thus, the decision was made to construct the biogas plant.
In another use of the S-ROI methodology, a company was considering an investment in a health-related program for the local community where they operate, which was struggling with a disease epidemic. Using traditional accounting methods, the investment would simply be a sunk cost with a 10-year NPV of around $4 million dollars. When the company’s experts sat down together, however, they identified many real risks to the company due to potential instability in the community (i.e. if the physical health of their workforce was threatened).
The results of the S-ROI analysis showed that those risks could cost the company more than $2 billion dollars after the 10 years. While putting in the investment wasn’t guaranteed to fix all of the community’s problems, it had a greater than 50% probability of creating a positive return for the company. The positive NPV in the below chart represents the benefits that accrue as a result of avoiding potential catastrophe. In other words, it represents the new scenario where the investment was made, versus the potential damage of doing business as usual.
Companies have long performed this type of analysis by hand or in Microsoft Excel, but using software that has the pre-loaded values and algorithms can make it faster and smoother, and you can invest more time in iterating potential solutions than crafting the model yourself.
The American Institute of Chemical Engineers (AIChE) has developed a number of spreadsheet tools that work with S-ROI, and EarthShift has developed a software tool called 3Pillars to simplify the process. The EarthShift tool uses Monte Carlo analysis to calculate Net Present Value for very complex scenarios so that brainstorming isn’t hindered by calculation capability.
A Web-based interface can control costs by allowing stakeholders to conduct the traditional workshop-based brainstorming and analysis through a social networking environment, not necessarily in the same room together. The use of these methodologies and software technologies helps to bring more rigorous data-driven analysis to complex decisions like the ones mentioned above, helping companies, governments, and other organizations minimize risk and maximize financial returns in today’s complex, interconnected world.