📉 The great slowing of innovation

Published on November 13, 2024

We often comment on the decline in funding in FoodTech startups, as in our latest report on global investments, which shows a 72% decrease since 2021. It is not something that only impacts food, though: we should stress more that it’s also something affecting other “tech sectors”. This is well reflected on the right-hand-side graphs below.

Food is probably slightly more impacted:

  • in terms of capital invested, with a “new normal”, which is somewhat at 2017/2018 levels rather than 2020. But that’s largely due to its low exposition to the few remaining “hype areas” in tech, notably artificial intelligence.
  • in terms of deals, with a very severe dip in the number of deals. This translates into the depletion of the pool of early-stage ventures, which may be the point we are the most worried about.

These graphs coming from the Global Innovation Index (which ranks Switzerland as number #1), show something else: innovation is slowing beyond startups and venture funding. After years where the growth in the number of patents was stalling, it went down in 2023 with almost 2% less patents. In the same time, the number of scientific publications is going down by 5.3%.

While there is not yet a definitive explanation of what is happening, we can put forward multiple hypotheses:

  • Rising costs: the cost of disruptive innovation has increased significantly due to the inflation and to the global contest for talents.
  • Disillusion: recent investments in disruptive innovations have proven deceptive and have provided little returns for companies.
  • Short-term focus: in the current, highly uncertain economy which creates financial constraints, investment in long-term projects and innovation may be less of a priority compared to short-term gains in productivity or incremental innovation. For venture capital, this translates into a preference for startups with a clearer path to profitability.
  • Rationalisation: it has also been shown that the increase in the number of patents, or in scientific publication wasn’t necessarily linked to a rise in quality. As for startups and investments, a form of rationalisation was required.

In the short term, this isn’t too worrying and could be only an adjustment. But I think it reflects something more profound and that it should be taken in consideration very seriously, especially in food where we have a deep need of innovation.

  1. First, there are growing doubts on the cost and the output of research with the idea that there are diminishing returns in many areas. As underlined in the report on the Global Innovation Index with the example of ageing, the gains of lifespan and health-span have become marginal in the past decades, even if investments in research have kept increasing.
  2. Then, for food (but it could be the same for many other areas), there is an also growing discussion on whether the venture capital model is the best one for disruptive innovations. Investors expects returns (an exit through an acquisition, which is the preferred path in agriculture or food) in a window of seven to ten years. But we are seeing that many startups working on disruptive technologies (such as alternative proteins, new inputs or materials) need more time to reach a relevant level of maturity.

Now, what do we do next? We could just stay there and complain about the state of things, but let’s see that as a challenge that creates opportunities. If others are disengaging, it’s maybe the best time to consider putting more effort into innovation with a fresh look. Here are a few ideas for agrifood companies:

  1. Set up strategic partnerships to solve the scale up challenge of disruptive technologies: rather than relying solely on VC-backed startups, companies can consider forming coalitions (ideally between players at different stages of the value chain to avoid direct competition) to boost research, investments, and scale in key areas, such as the broad spaces of alternative proteins, healthy ageing and decarbonation.
  2. Focus on collaboration, increase R&D spending and open Innovation: with declining patents and publications, collaboration is becoming essential. Companies can increase their own R&D capabilities both by increasing their spending, but also by partnering with universities and. A key of success is probably to be extremely clear on the goals while not being too focused on the short-term.
  3. Create internal innovation ecosystems, first to seek where innovation is really needed and which level of disruption is required, then to either engage with startups, or to develop innovation internally. This is highly challenging (as it needs to build the right structure with the right metrics that don’t put too much pressure on the need to reach immediate profitability) but it can highly rewarding if done well.

If that’s an important topic for you, and if you also want to make food innovation great again, maybe we should have a chat. Contact us here.

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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.