Organizational Behavior Insights from 50001 Ready Technical Assistance Cohorts

Understanding how individuals can lead an organization to lower energy consumption is key to addressing climate change at scale. In 2021, DOE and LBNL started a cohort-based technical assistance program open to any U.S. organization seeking to implement the DOE’s 50001 Ready energy management system (EnMS). This approach integrates continually improving energy performance into customary business practices. This presentation will highlight how participants and their energy teams adopt new practices and spread them throughout the organization relatively quickly to accelerate energy savings. LBNL is deploying 5 participant surveys over the course of the engagement, including pre- and post-program. Statistical and qualitative analysis (using NVivo) will be used to explore emergent themes in responses to open-ended questions, patterns between these and other variables, and potential response bias. By March 2022, this ongoing program had engaged >350 participants from 190 sites and >50 organizations, and 209 survey respondents. Participants are diverse in terms of geography, size, and sector, including manufacturing, commercial buildings, military, and government agencies. Interim results indicate 59% have worked for >5 years where managing energy or energy efficiency was important, while 25% had spent <2 years in this type of role. The top 5 motivations for implementing an EnMS were cost savings, environmental sustainability, increased productivity, corporate social responsibility, and utility incentives. 79% of respondents’ organizations had goals, targets, and/or commitments for energy, and 58% had them for carbon emissions. All respondents saw a 50001 Ready EnMS helping to address energy goals, with 63% seeing its applicability to emissions targets. Those most involved in making energy decisions were site management and site operations/facilities, while a broad range of stakeholders were primarily responsible for making decarbonization decisions. Major anticipated barriers were that other competing priorities would limit resources, data collection challenges, and implementation taking too long.