3 key challenges for food manufacturers to adopt a more sustainable business model

Published on 12 February 2024 Read 25 min

According to the latest IPCC figures, the food system as a whole accounts for almost 1/3 of global greenhouse gas emissions. If nothing is done, these emissions could reach 40% by 2050 due to population growth and dietary changes. For this reason, it is important that the food industry strives to reduce its environmental impact and its dependence on fossil fuels.

With this in mind, Alcimed has published a series of articles outlining the major challenges facing the food industry, with a view to turning sustainable development into an opportunity rather than a constraint. The aim is not to draw up an exhaustive list, but rather to stimulate discussion on the key issues.

In the fourth opus in this series, Alcimed tackles the question of how to create relevant indicators and manage data, with a view to guiding the industry towards more sustainable, value-creating business models.

Challenge n°1: Adopt common, credible indicators based on science

By developing the right decision-making tools…

Industrial players are striving to equip themselves with tools and indicators to assess the environmental footprint (particularly carbon) of their activities, so as to prioritize desirable solutions and evaluate their environmental benefits.

It is essential that these tools be based on a scientific consensus, to guarantee their objectivity and admissibility. The co-development of decision-making tools by researchers, companies and financial players can enhance the usefulness of these tools for practical application, such as assessing non-financial returns.

These tools can be designed in various ways at the interface between science and industry:

  • From science to industry: LCA is the current method for assessing the environmental footprint of different resources.
  • From business to science: Companies’ commitments and roadmaps can be confronted with scientific experts to ensure their relevance.
  • From science to industry: Multi-sector co-development of scientific indices, such as agrobiodiversity (ABDI).

… that reflect a holistic view of impacts

However, the various measurement tools available today have their limitations, starting with a common one: they still struggle to provide a holistic view of impacts, despite their intrinsic desire to do so.

  • LCA results are sometimes questionable, and do not always provide a complete picture of a product’s environmental impact. For example, they may indicate that conventionally farmed products have a lower environmental impact than organic products. However, they do not take into account the long-term effects of the use of pesticides and chemical fertilizers on soil and ecosystem health.
  • What’s more, the agri-food sector is unique in that it meets a fundamental human need: food for life. However, it is important to emphasize that this industry is often penalized by “one size fits all” indicators, such as GHG emissions, which can unfairly discriminate against certain sectors and players. Although GHG emissions are a major issue, it is necessary to take into account the criticality of the activity in order to carry out the analysis. In other words, this raises the question of whether GHG reduction objectives and strategies should be weighted according to the criticality of the activity.

Challenge n°2: Make better use of data management and sharing

In this context, better use and sharing of data are crucial, as they enable the generation of new scientific data for assessing environmental impact. This data includes, among other things, information on agricultural production and processed products, logistical and commercial exchanges, as well as product composition, quality and traceability.

Agri-food and agricultural production companies are faced with a growing challenge: collecting, producing, managing and analyzing ever more information at each production cycle. Indeed, to steer their environmental transitions, they need to be able to track the impact of their activities at every stage, from production to marketing, right through to recycling.

But data management is more than just a technical issue. It raises numerous challenges, each more complex than the last: standardization, exhaustiveness, interoperability, mutualization, reliability and certification, ownership and authenticity, governance and management, control and maintenance. These are all aspects that must be taken into account to ensure efficient data management and guarantee data quality and relevance over the long term.

Find out how we can help you deploy your data-driven strategy >

Challenge n°3: Collaborate with all stakeholders

The challenges of creating relevant indicators and managing data are interconnected, and require collaboration between all stakeholders if they are to be met. In addition to being a prerequisite for consensus on the indicators to be adopted (challenge 1), collaboration between stakeholders is essential, as it must also enable the circulation of data up and down their value chain, right through to recycling (challenge 2), in order to accelerate the transformation of players and industries. However, setting up effective and efficient collaboration is all the more complex given the large number of stakeholders involved: consumers, value chain players, academic players, startups and technology providers, other economic sectors, and the wider ecosystem.

In addition to the need to collaborate on measurement issues, the collaboration itself brings with it other challenges, which you can read about in this article on CSR value creation.

Indicators and data sharing enable the agri-food industry to measure value objectively, strengthening the relationship of trust with the brand and promoting environmental and ethical efforts.

However, there are a number of challenges to be met, starting with the need to take into account the specific characteristics of each sector and player when defining indicators, and to ensure good interoperability, reliability and governance of data, as well as good collaboration between stakeholders to reach a consensus on indicators and ensure data circulation. We can support your projects in these areas. Don’t hesitate to contact our team!

About the authors,

Mathieu, Project Manager in Alcimed’s Agrifood team in France

Sami, Senior Consultant in Alcimed’s Agrifood team in France

Ludivine, Consultant in Alcimed’s Agrifood team in France

Antoine, Consultant in Alcimed’s Agrifood team in France

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