Opportunities for greater energy efficiency in government facilities by aligning decision structures with advances in behavioral science

In 2007, Executive Order 13423 mandated 30% energy and emission reductions for all government facilities by 2015. Unfortunately, the government fell short of their goal by 9%. Their approach through mandates and federal legislation focused predominantly on new construction and major retrofits to existing facilities. To meet future energy and emission reduction goals, more emphasis on facility management is needed. The government manages over 370 million square feet of facilities each year. The daily decision process for government facility managers is full of competing interests, such as maintenance needs (preventative and corrective), limited operating budgets, time constraints to make decisions, and bounded rationality about energy consumption and savings. By understanding how these decisions are made and the cognitive bias that may occur, advances in facility management decision making can reduce energy consumption. Cognitive biases to the decision making process such as loss aversion, anchoring, and status quo bias are explored and an approach to overcome them is offered, a tactic called choice architecture, meaning restructuring decision environments to align with behavioral decision theory. Examples of choice architecture, such as, enabling procurement systems to query green products, changing default settings in mechanical systems, and requiring the use of pay back period calculators to account for cognitive limitations of the decision maker, are suggested and supported by behavioral science research to help direct facility managers towards energy efficient choices. This approach, through choice architecture, holds potential to yield relatively low-cost solutions (they do not require new mandates or laws) to support greater energy reduction in government facility management. This merging of literature from behavioral science to facility management is meant to open new avenues of interdisciplinary research.