Combining life cycle assessment with data science to inform portfolio-level value-chain engineering: A Case Study at PepsiCo Inc.

Christoph J. Meinrenken, Beth C. Sauerhaft, Anthony N. Garvan, Klaus Lackner

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Life cycle assessment (LCA)-based analyses of company value chains can inspire profound modifications to products' design, material procurement, manufacturing, energy/water use, distribution, use, and disposal. However, such modifications often create trade-offs, improving some aspects while worsening others. How can firms decide whether or not to carry out such modifications? Or prioritize between different options to choose the one delivering the most competitive advantage? Typically, firms' metrics fall into two groups: (1) product-level metrics across the life cycle, including up- and downstream of facilities (e.g., product carbon footprints); and (2) facility-level metrics (e.g., plants' annual energy cost). Neither is sufficient for firm-wide cost-benefit analyses of modifications that affect multiple products and value-chain stages. Whereas facility-level metrics do not capture up- and downstream effects-where often most cost and environmental impacts originate-life cycle methodologies are currently not mature enough to be applied at the scale of entire product portfolios. We present a pilot system of key performance indicators (KPIs) that evaluate 3,337 products across 211 brands and five countries of PepsiCo, Inc. KPIs are firm-wide, annual figures (environmental, operational, and financial) across the value chain (cradle to grave) and can be determined at any level (single product, brands, or regions). Uncertainty analysis is included. In addition to KPIs for base cases, the system characterizes KPI impacts for any considered modifications (what-if scenarios). In a detailed case study, we present background about how and why PepsiCo used the system to evaluate all aspects of a strategic value-chain modification. For 7 of the 211 brands, this resulted in avoiding an 8% increase in greenhouse gas emissions and a 7% to 10% increase in procurement costs. It also saved PepsiCo an estimated ∼200 years full-time equivalent employee time (or alternatively ∼US$30 million in LCA consultant fees) had the LCAs of the 3,337 SKUs been carried out by traditional methods. This cost efficiency of the KPI system enables considering environmental impacts with more-traditional business metrics side by side. As a result, environmental impacts can be considered on a routine basis as part of integrated strategy and business planning. We discuss implementation considerations of the KPI methodology and future improvements.

Original languageEnglish (US)
Pages (from-to)641-651
Number of pages11
JournalJournal of Industrial Ecology
Volume18
Issue number5
DOIs
StatePublished - Oct 1 2014
Externally publishedYes

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life cycle assessment
value chain
life cycle
engineering
science
performance
firm
environmental impact
costs
cost
energy
product design
methodology
carbon footprint
annual plant
fee
uncertainty analysis
product
Value chain
Key performance indicators

Keywords

  • Enterprise resource planning (ERP)
  • Industrial ecology
  • Key performance indicator (KPI)
  • Life cycle assessment (LCA)
  • Product design
  • Supply chain management

ASJC Scopus subject areas

  • Environmental Science(all)
  • Economics and Econometrics
  • Social Sciences(all)

Cite this

Combining life cycle assessment with data science to inform portfolio-level value-chain engineering : A Case Study at PepsiCo Inc. / Meinrenken, Christoph J.; Sauerhaft, Beth C.; Garvan, Anthony N.; Lackner, Klaus.

In: Journal of Industrial Ecology, Vol. 18, No. 5, 01.10.2014, p. 641-651.

Research output: Contribution to journalArticle

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