Triple Bottom Line Metrics for Performance Analysis

The triple bottom line (TBL) framework, developed by Elkington (1994) is one of the most important performance metrics for operations managers because it goes “beyond the traditional measures of profits, return on investment, and shareholder value to include environmental and social dimensions” (Slaper, Hall, 2011, p. 4). By including environmental and social dimensions, the TBL metric allows operations managers to better understand how a company is performing across measures that include variables not typically considered by financial analysts but that yet have an impact on a company’s value. Indeed, with the rise of corporate social responsibility (CSR), firms have begun to see how a business’s footprint on a community in social and environmental terms also helps to diminish or strengthen the company’s value over time (Marquis, Lee, 2013).
When the company’s CSR is evident and impactful, the company’s performance can viewed in a more favorable light: a strong connection to the community and to causes that the community advocates can translate into valuable good will, consumer loyalty, and brand awareness. The TBL relates to the Customer Satisfaction Score (CSS)—another key metric in evaluating a business’s performance. Since a business is there to serve the needs of the consumer/client, rating the CSS can be pivotal in evaluating a firm’s performance. This is not to say that the TBL does not include financial measurements—not at all; in fact, the TBL can be measured by the three P’s—people, planet and profits.
While profits are measured in dollars and determined by factors such as cash flow, gross margins, income, balance sheets, and equity fluctuations, social and environmental capital are measured in different ways—for instance, by assessing the firm’s CSR policy. Various economic measures, social measures and environmental measures exist to support a TBL valuation: economic measures include establishment churn, establishment size, job growth, revenue by sector; social measures include the unemployment rate, relative poverty, median household income, violent crimes per capita, etc.; environmental measures include fossil fuel consumption, waste management, changes in land use and land cover, and so on (Slaper, Hall, 2011).
The data that would be used to support the profit side of the measurements would include a company’s finances—its balance sheets, earnings, forecasted earnings, credit risk (such as secured and unsecured lines of credit, assets, refinanced debt, revolving loans, covenants and so on) (Moslyn, 2010). These metrics support the overall financial performance of the organization by providing access to the variables that determine a company’s success.
To ensure that the data would be of sufficient quality, the appropriate data analytics would have to be employed. As Melnyk, Stewart and Swink (2004) note, “you get what you inspect, not what you expect” (p. 209). The relationship between metrics and performance is based on the need for routine inspections, which ensures that performance is on the right track. Without inspection, i.e. metric analysis, there is no sense of how the operations are running. Data analytics supports the metrics by creating “an index system [which] can link strategy, execution, and ultimate value creation” (Melnyk et al., 2004, p. 210). The quality of the index depends upon the quality of the data—and for the TBL, the data can be obtained by survey, by policy analysis, and by financial statement analysis. Consumer and employee surveys along with CSR data and balance sheet, cash flow, margins, etc. can all be used to obtain quality data for these metrics.

References
Elkington, J. (1994). Towards the Sustainable Corporation: Win-Win-Win Business
Strategies for Sustainable Development.  California Management Review, 36(2): 90–100.
Marquis, C., Lee, M. (2013). Who is governing whom? Executives, governance, and
the structure of generosity in large U.S. firms. Strategic Management Journal, 34: 483-497.
Melnyk, S., Stewart, D., Swink, M. (2004). Metrics and performance measurement in
operations management: dealing with the metrics maze. Journal of Operations Management, 22: 209-217.
Moslyn, G. (2010). Essentials of financial analysis. NY: W&J.
Slaper, T., Hall, T. (2011). The triple bottom line: What is it and how does it work?
Indiana Business Review, Spring: 4-8.