đź’Ą Learnings from FoodTech bankruptcies

Published on March 27, 2024

Recently, a significant number of startups have had troubles. Some survived the hardships, but many just went bust and filed for bankruptcy. Let’s look, with examples, at the five signs of distress in agrifood startups.

1 – Layoffs

Many tech companies have had layoffs over the past couple of years. This is not only observed in startups but also in large tech companies such as Microsoft or Meta. For startups, these layoffs are due to many factors, including the end of cheap money (and inflation), lower-than-expected growth, and a switch of focus. However, for most startups, this happens without the existence of a highly profitable core business activity.

Layoffs are generally the first externally visible sign of distress. It shows that the company can no longer convince investors to pour money into sustaining its initially planned growth trajectory announced (in terms of locations it wants to be active or in terms of projects it is developing). It is also simply a sign that revenue expectations (without mentioning profit) are unmet.

Nowhere is this more visible than for food delivery startups. As shown in the above graph (more details here, tens of thousands of people have been laid off in two years.

Also, as you can see, around half of the companies had to go into round after round of layoffs. I can’t imagine the atmosphere inside a startup which is announcing layoffs while its remaining employees are becoming aware that the shares they were thinking of selling during a further round of financing are now worthless.

2 – Downturns

Downturns happen when a startup raises money at a lower valuation than previously. This is supposed to be quite rare as it dilutes former investors (and as they have to announce to their own investors that they made a mistake by overvaluing a company). Even rarer are the cases where startups communicate on this topic.

The most striking example is certainly Indigo, which went from $3.5B to $200M in valuation.

3 – CEOs stepping down and brutal strategic moves

Due to this very public nature, removing a CEO can be a last resort option for a startup (mainly for its investors). The goal is often to demonstrate the startup’s commitment to switching to a new strategy (usually related to profitability). In many cases, it also goes alongside a downturn (where current investors commit some money) in order to attract new funds and follows one or multiple rounds of layoffs that have failed to put the company on track.

Many alternative proteins have recently announced such moves:

4 – Disappointing exits

If the above steps are revealed to be inefficient, selling the startup remains the only option to save face, first for investors and secondarily for founders. For employees, it will be a bad experience (forget about your precious shares; they will get extremely diluted and then acquired for pennies).

In a last-minute effort to avoid bankruptcy, timing is key, and there needs to be more time to negotiate the deal, which often lands on a disappointing valuation.

In recent months, the list is quite long, but here are some delivery examples:

5 – Bankruptcies

When all other possibilities have been exhausted, it’s time to declare bankruptcy and eventually shut down the company. This has at least one advantage: we get more information. Indeed, investors, founders, and employees often publicly settle scores.

In past months, it affected all categories:

  • Vertical Farms with Infarm: this article is a great read to understand how everything can go wrong inside and around a startup which had raised $500M
  • Plant-based products: the list would be very long here, but the best example may be Nowadays, a startup that was praised by commentators. It had fewer ingredients than others but was more expensive—not the best situation in an inflationary market.

Some learnings

First, the following pattern is quite consistent: layoff(s), then a hidden downturn quickly followed or associated with a CEO removal and a strategy change, and a failed exit or bankruptcy.

Secondly, there are some striking similarities between these failures, which we can group into  categories:

  • The “blind failure“: when a previously highly regarded startup had raised millions for something an obviously unscalable technology or no viable market. This happens repeatedly, and I can only wonder about the seriousness of the due diligence process made by otherwise reputable investors.
  • The “awful failure“: when startups fail due to fraud (which often consists of lying about the number of clients or the tech).

But most stories end with what we call a “good failure“: a startup that would have succeeded without an adverse event. Often it went too fast, invested in preparing growth that did not come due to a change in market conditions or bad luck. Here failure is only part of the “startup game”. At then end of the day, we don’t want cautious startups.

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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.