A framework for increasing the availability of life cycle inventory data based on the role of multinational companies

Abstract

Purpose The aim of the paper is to assess the role and effectiveness of a proposed novel strategy for Life Cycle Inventory (LCI) data collection in the food sector and associated supply chains. The study represents one of the first of its type and provides answers to some of the key questions regarding the data collection process developed, managed and implemented by a multinational food company across the supply chain. Methods An integrated LCI data collection process for confectionery products was developed and implemented by Nestlé, a multinational food company. Some of the key features includes (1) management and implementation by a multinational food company; (2) types of roles to manage, provide and facilitate data exchange; (3) procedures to identify key products, suppliers and customers; (4) LCI questionnaire and cover letter and (5) data quality management based on the pedigree matrix. Overall, the combined features in an integrated framework provide a new way of thinking about the collection of LCI data from the perspective of a multinational food company. Results and discussion The integrated LCI collection framework spanned across 5 months and resulted in 87 new LCI datasets for confectionery products from raw material, primary resource use, emission and waste release data collected from suppliers across 19 countries. The data collected was found to be of medium to high quality compared with secondary data. However, for retailers and waste service companies, only partially completed questionnaires were returned. Some of the key challenges encountered during the collection and creation of data included lack of experience, identifying key actors, communication and technical language, commercial compromise, confidentiality protection and complexity of multi-tiered supplier systems. A range of recommendations are proposed to reconcile these challenges which include standardisation of environmental data from suppliers, concise and targeted LCI questionnaires and visualising complexity through drawings. Conclusions The integrated LCI data collection process and strategy has demonstrated the potential role of a multinational company to quickly engage and act as a strong enabler to unlock latent data for various aspects of the confectionery supply chain. Overall, it is recommended that the research findings serve as the foundations to transition towards a standardised procedure which can practically guide other multinational companies to considerably increase the availability of LCI data.

Environmental management of confectionery products: Life cycle impacts and improvement strategies

“…For datasets which were collected from suppliers (e.g. Miah et al, 2017), the data were converted to environmental impacts categories defined by EcodEX using Gabi LCA software V6.4 (Thinkstep, 2015), shown in Table 3.…”

“…For some of the chocolate products, the same technology and/or production lines were used. The LCI data for the confectionery factory is extracted from Miah et al (2017).…”

“…In comparison to other sugar confectionery ingredients, it was found from the data collected from suppliers, the processing sites for gelatine powder generated energy from different sources (e.g. natural gas, coal, fuel oil and wood) requiring high water consumption (Miah et al, 2017).…”

Novel macroalgae (seaweed) biorefinery systems for integrated chemical, protein, salt, nutrient and mineral extractions and environmental protection by green synthesis and life cycle sustainability assessments

“…The system boundary includes the direct, indirect and embedded inputs and outputs. For each biorefinery unit operation inventory given in Table 2 are the key ones control the decision making realised in the food and healthcare sector 94,95 .…”

How to Seize the Opportunities of New Technologies in Life Cycle Analysis Data Collection: A Case Study of the Dutch Dairy Farming Sector

“…A common problem in life cycle assessment (LCA) is the low availability of life cycle inventory (LCI) data [1][2][3]. Aproximately 70-80% of the time and cost of an LCA can be attributed to data gathering for the inventory phase [4]. New technologies such as distributed ledger technology (e.g., blockchain), the Internet of Things (IoT), big data (BD), and artificial intelligence (AI) provide opportunities to revolutionize the collection of LCI data.…”