S1 Supporting Information for: Optimizing Eco-Efficiency Across the Procurement Portfolio Rylie E.O. Pelton 1 , Mo Li 1 , Timothy M. Smith 1 & Thomas P. Lyon 2 Rylie Pelton Olso4235@umn.edu Mo Li Lixx1407@umn.edu Timothy Smith Smith463@umn.edu Thomas Lyon tplyon@umich.edu 1 NorthStar Initiative for Sustainable Enterprise, Institute on the Environment, University Minnesota, 325 Learning and Environmental Sciences, 1954 Buford Ave, St. Paul, MN 55108 2 Erb Institute for Global Sustainable Enterprise, Ross School of Business, University of Michigan, 701 Tappan Street Ann Arbor, MI 48109 Summary This supporting information provides a list of the nomenclature, a detailed description of the method and its application to the breakfast cereal manufacturing industry, results of the various analytical steps including eco-efficiency results and sensitivity analyses, a description of environmental product attributes analyzed and life cycle inventory information for each of the eight product categories, accompanied by detailed written descriptions of model assumptions and sources. Pages S1-S52. Table of Contents Nomenclature S3 Methodological Steps and Application S4 Table S1. Hotspot Scenario Analysis - Procurement Portfolio Optimization methodological steps, including example applications from breakfast cereal industry case study. S4 Model Parameters and Results S5 Table S2. Variability in percent reductions and increments in total product option impact across all product attributes. S5 Table S3. Selected product options and corresponding product physical units in the three purchasing approaches: baseline, silo and portfolio, under the condition of minimizing GWP, water depletion and environmental index impacts subject to budget constraints. S5 Figure S1. Sensitivity analysis of different organizational procurement budget scenarios. S7 Table S4. Eco-efficiency comparison between silo and portfolio procurement approaches against baseline eco-efficiency values for different attribute pricing scenarios. S8 Table S5. Eco-Efficiency sensitivity analysis for alternative spend and alternative minimum and maximum hotspot percentage values. S9 Table S6. Hotspot Scenario Analysis results and characterization of baseline and attribute prices. S10 Table S7. Baseline and sensitivity analysis parameters for relative product category spend, impacts per million dollars spend, and the resulting total impacts for each product category. S11 Table S8. Total GWP impact characterization for each product category, methods and results. S11 Table S9. Shadow prices on budget constraints and sensitivity of shadow price estimates. S12 Table S10. Shadow prices on the physical unit constraints and sensitivity of shadow price estimates. S13 Attribute Definitions S14 Table S11. Containerboard (Corrugated Board and Paperboard) Environmental Attribute Definitions. S14