Measuring green risk

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LONDON – As the business world tunes into the benefits of being environmentally friendly, business intelligence firm SAS has launched a product to help organisations accurately measure and manage their environmental impact. SAS for Sustainability Management is a decision-support software platform that allows firms to identify innovative strategies that effectively address complex environmental, social and economic situations, while also achieving stakeholder objectives.

"Lessening our impact on the environment and mitigating the future risk of depleting our planet's natural resources is becoming a priority in shaping every organisation's strategy," says Jim Goodnight, chief executive officer of SAS. "With SAS, organisations can optimise business strategies for minimising risks and costs, developing new lines of business, and improving resource use, environmental or otherwise."

The new system has been piloted by Cisco, which has being using SAS to support its sustainability efforts. "Cisco believes new innovative technologies and the power of collaboration are keys to achieving our sustainability goals and minimising our impact on the environment," says Laura Ipsen, co-chair of Cisco's ecoboard and senior vice-president of Cisco global policy and government affairs. “By partnering with SAS and using SAS for Sustainability Management, Cisco can better prioritise projects and resources that create a positive return for the environment, shareholders and our employees. The SAS solution will enable us to simulate the impact on carbon footprint, waste reduction targets, greenhouse gas emissions and other goals so we can more effectively predict and manage the impact of our operations on the environment.”

SAS for Sustainability Management is based on the SAS Enterprise Intelligence Platform and uses the Global Reporting Initiative framework to report on triple bottom line indicators: environmental, social, and economic. The system also uses SAS's predictive abilities to validate strategies, identify causal relationships, forecast improvement scenarios and drive innovation.