📊 FoodTech in graphs: obesity and meat consumption

Published on July 19, 2023

One of the most fascinating elements of food is how it is deeply entrenched in our lifestyle. Then, it reveals many of our contradictions on topics as important as health, equality, or the environment. Notably, on this last topic, we may have long-term convictions. However, our short-term actions often go in the opposite direction (think about how meat consumption is still increasing even as consumers declare themselves more vegetarian or flexitarian). As often, it is better shown than explained with words, let’s look at some graphs that illustrate some of our food contradictions.

1 – Fighting obesity the wrong way?

Obesity is exploding all over the world. In the last World obesity report, we learn that half the world will be overweight in 2035. In some countries, half the population will actually be obese in 10 years. This has a huge human, economic and societal cost. The estimated yearly cost, for the US alone, is above a trillion dollars, or 4% of GDP.

Faced with this challenge, do we have a structured answer? Not really; it’s even the opposite. You may have heard about new “miraculous” diabetic drugs like Ozempic. They are used more and more for weight loss (the one Elon Musk talked about). Looking at the Google Trends graphs above, it seems these new drugs are the new “diet trend”. They are now more “trending” in terms of search than older fads such as intermittent fasting or keto diets.

Looking at these graphs, I see the need for innovation in at least 3 directions :

  1. better foods, with more nutrients and eventually fewer calories with alternative fats and sugars
  2. individual knowledge about our metabolisms to make educated choices on what we eat (from tests on the microbiome to glucose monitoring devices…)
  3. services to help consumers eat healthier diets, notably through ready-to-eat meals.

2 – How much should we cut meat consumption?

Below is a fascinating graph showing how much meat we are currently eating (in red) in each region and how much we’ll be eating in 2050 if we follow the current trends.

The dotted line shows the effort to make to reach an equitable (based on population) 52 calories of meat per day and per person. Reaching this level would mean:

  • closing the land gap or the additional land, we would need to produce the projected required amount of meat
  • solving 50% of the agriculture mitigation gap: the difference between what is projected and the greenhouse gas emissions level we need to reach to remain below 2°C.

52 calories of ruminant meat is about 1.5 hamburgers per week. Let’s say we are globally far from reaching this goal.

This graph is again a demonstration of the need for innovation to get around human behaviours. Here, alternative proteins, from plant-based burgers to cellular agriculture foie gras, will help reduce the gap between what we need to do and what we are really ready to do.

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Use case: project for a global F&B company looking to map its AgTech innovation ecosystem and the best startups to partner with

What we did:

  • Mapping of the AgTech ecosystem: startups, research regulators, and other leading companies.
  • Discussion to select areas to focus on.
  • Analysis of the information to reveal the trends and a model to analyse eventual partners.
  • A workshop to validate the opportunities based on our recommendations.
  • Scouting of relevant partners followed by introductions.

Results:

  • Mapping the different categories of innovations in AgTech that should be considered now to create long-term benefits for the business.
  • Identification of key partners (an incubator and a couple of startups).

Use case: project for a CPG company on the healthy ageing ecosystem

What we did:

  • Education of the board through a couple of workshops to define the perimeter
  • Identification of key opportunities and threats created by long-term evolutions (technologies, business models, behavioural changes).
  • Deep dives on each of the priority categories.
  • Co-construction of a vision on how the company should address these challenges.
  • Identification of partners (startups, incubators, funds) to move forward.

Results:

  • Creating a consensus on which categories to prioritise and how to address them.
  • Implementation of an open innovation strategy through the development of partnerships.

Use case: project for a global CPG company to develop a strategy on the healthy ageing ecosystem

What we do (ongoing mission on a subscription model):

  • Kick-off where we present an overview of the AgriFoodTech ecosystem to select with the client the categories to cover and for each, the level of information required.
  • Monthly newsletter: each month we send a newsletter with the articles that we have gathered ranked by relevance, their summaries, and a layer of analysis.
  • Database: we set up a personalised database that will be filled month after month with the information gathered on the companies identified for the watch.
  • Workshops: twice a year with the client’s innovation team and other “innovation curious” team members, we present an overview of the evolutions, key trends and a dashboard of the topics followed by the watch.

Results:

  • A clear, regular and evolutive tool to follow what is happening in terms of innovation on key topics.
  • A forum (through the workshops) to discuss innovation trends and new opportunities.

Use case: opportunity screening for an ingredient company

What we did:

  • Kick-off to define the perimeter of the ecosystem studied.
  • Mapping of the different trends shaping the innovation ecosystem of the client.
  • Analysis of the trends on DigitalFoodLab’s trend curve and other relevant frameworks.
  • Workshop to discuss DigitalFoodLab’s recommendations on key trends to prioritise

Results:

  • Shared view of the innovation ecosystem for the client with a view of the trends to prioritize.
  • Clear document (personalised trend curve) that can be easily shared internaly to explain the company’s innovation choices and which can be then updated each year.

Use case: scouting for an agriculture coop

What we did:

  • Kick-off to define the perimeter of the client, the goals of the scouting (partnerships) and the criteria on which startups should be evaluated.
  • Set-up scouting: we selected the first batch of 20+ key startups following the criteria of the client.
  • On-going scouting: then we set up a quarterly scouting of about ten startups.
  • For each scouted startup, we created an ID card with key information such as the business and technological maturity, funding, and corporate partnerships. We also added an explanation of why we selected this startup.

Results:

  • An ongoing and evolutive scouting are matching the client's criteria and its capabilities in terms of deal flow.

Use case: working on an acquisition process for a CPG company

What we did:

  • Kick-off to define what the client is seeking, notably in terms of maturity.
  • Workshop with the client based on a mapping of the different innovation ecosystems adjacent to its activities to select some priorities and discuss inspiring examples of startup acquisition stories.
  • Identification of 20+ targets.
  • Workshop to select the most relevant to engage with.
  • DigitalFoodLab worked as a sparing partner during the acquisition process, notably to help design how the acquired startup could be integrated into the overall company’s strategy.

Results:

  • Different results from traditional M&A processes with a focus on the client’s innovation strategy.
  • Identification of a good match for an acquisition.

Use case: market due diligence on sugar alternatives

What we did:

  • Kick-off with the client to discuss its interest on this category, its expectations and existing level of information (notably on the target company).
  • Mapping of the ecosystem to analyse the different existing alternatives and technologies to compare them.
  • Interview (calls) with relevant startups made by our internal biotechnology expert.
  • Recommendation on whether to invest or not.

Results:

  • Clear view of the ecosystem and of the reasons to believe (or not) in each sub-category.
  • Enforceable recommendations based on facts and expertise.