Industrial Electric Productivity: Myths, Barriers & Solutions
Summary
The report identifies a 300,000 GWh annual electricity saving potential in the U.S. industrial sector by closing the productivity gap between the lowest and highest performing states. It argues that while exogenous factors like electricity prices play a role, the primary constraints are endogenous barriers such as poor understanding of efficiency potential, fossilized design paradigms, and capital constraints. Through case studies in high technology, oil and gas, and food production, the authors demonstrate that holistic design and overcoming these barriers can significantly reduce energy use and costs. The document concludes that policymakers should provide low-cost capital and education to incentivize efficiency measures that benefit society but may be NPV neutral for individual firms.
Key insights
- There is a significant disparity in industrial electric productivity across the United States; if the country matched the productivity of the top ten performing states, it would save 300,000 GWh annually, representing 8% of all electric retail sales.
- A majority of the industrial electric productivity opportunity (62%) can be addressed by improving efficiency in three specific end uses: facility HVAC, process heating, and machine drives, which together account for over 7% of total U.S. electricity use.
- Exogenous factors such as the number of energy efficiency programs, the presence of energy-intensive industries, and electricity prices do not fully explain the productivity gap, as high-performing states often have intensive industries and varying price points.
- Industrial efficiency in new (greenfield) sites is hindered by internal barriers including a lack of clear targets, a tendency to use 'fossilized design paradigms' rather than innovative approaches, and 'split incentives' where equipment suppliers prioritize their own costs over the lowest levelized costs for the user.
- Retrofitting existing facilities faces additional challenges, such as the potential need to scrap equipment that still has useful operating life and the risk that major retrofits could temporarily reduce facility productivity and margins.
- Case studies demonstrate substantial savings across sectors: data centers can reduce costs and emissions through virtualization and cooling optimization; oil and gas facilities can reduce pumping energy by addressing frictional losses in piping; and food production facilities can achieve 35-40% energy reductions in existing facilities and 40-50% in new ones.
- To accelerate market transformation, policymakers should provide access to low-cost capital for NPV neutral efficiency measures and offer education and training to address the lack of holistic design skills within companies and among external contractors.
Cite the original document
- APA
- Doig, S., Bell, M., & Mims, N. (n.d.). Industrial Electric Productivity: Myths, Barriers & Solutions. RMI. https://rmi.org/app/uploads/2017/05/RMI_Document_Repository_Public-Reprts_2009-18Industrial-Electric-Productivity-090529.pdf
- Chicago
- Doig, Stephen, Mathias Bell, and Natalie Mims. Industrial Electric Productivity: Myths, Barriers & Solutions. RMI, n.d. https://rmi.org/app/uploads/2017/05/RMI_Document_Repository_Public-Reprts_2009-18Industrial-Electric-Productivity-090529.pdf.
- Wikipedia
- {{cite report |last1=Doig |first1=Stephen |last2=Bell |first2=Mathias |last3=Mims |first3=Natalie |title=Industrial Electric Productivity: Myths, Barriers & Solutions |publisher=RMI |url=https://rmi.org/app/uploads/2017/05/RMI_Document_Repository_Public-Reprts_2009-18Industrial-Electric-Productivity-090529.pdf |access-date=17 August 2026 |via=Climate Insights Directory}}
- BibTeX
- @techreport{doigndindustrial, author = {Doig, Stephen and Bell, Mathias and Mims, Natalie}, title = {{Industrial Electric Productivity: Myths, Barriers \& Solutions}}, institution = {RMI}, url = {https://rmi.org/app/uploads/2017/05/RMI_Document_Repository_Public-Reprts_2009-18Industrial-Electric-Productivity-090529.pdf}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }
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