3 Lessons Food Start-ups can Teach the 'Big Guys'

Lauren Raouf
May 24, 2016
Food technology is one of the hottest sectors for venture capitalists in recent years. According to research from CB Insights, in 2015 alone, more than $5B was invested globally in tech-enabled food-focused companies. That number doesn’t include significant investments in typical food companies, like the nearly $100M invested in the coffee chain Blue Bottle since 2014. Is it an overheated investment market? Possibly. But established food providers do have something to learn from these up-and-comers.

Fail fast. But also fail small.

Drilled into the head of a start-up founder is the mantra to “fail fast.” There certainly are merits to this strategy – get a reasonable version of a product or recipe out into the marketplace to see how consumers respond. This is especially important because what consumers say they’ll do in interviews, surveys, or focus groups is often quite different to what they actually do when faced with a real product. The important corollary to this is also to fail small. They start with small-scale tests in limited distribution areas. Now valued at $2B, Blue Apron started with small-scale tests in a small delivery area in Manhattan in the summer of 2012. From these tests – and continued experiments – they’ve learned what meals people liked and when likely subscription drop-offs would happen. UberEATS took three months from concept to design, but before being rolled out to all of Uber’s customers, the app was tested in Toronto. They found they needed to reduce the number of restaurants, make restaurant food brands more prominent, and improve the photography of the menu options. Only once those changes were made was the app then sent back for more testing, and then rolled out to more cities over time. And sometimes, major changes are required. In one example, start-ups Kitchit and Kitchensurfing came into being promising to deliver chefs into homes on demand. Through large-scale city tests, both companies learned that the “chef on demand” model was both too expensive and required too many choices from consumers. Both have shifted to offering more streamlined and cheaper options. Copying this fail fast mentality, well-designed tests are one of the most powerful ways for enterprise food companies to understand the true drivers of their customers’ behavior and preferences.

Follow the data.

How do you follow the data? Well, first, you need to have it – which can be a struggle given antiquated point-of-sale technology and reporting systems that can exist at many enterprise food retailers. Second, and often undervalued at established companies, is the ability to truly dig into the data. Scan the job boards at start-ups like Munchery, Blue Apron, Plated, and Postmates, and you’ll see multiple roles focused on data analytics and statistics. Many established companies in this space lack these capabilities, and therefore lack the information to understand if their activities are actually driving changes in customer behavior. For example, analysis that fails to correct for the seasonality of the food business – soups will sell well in the winter while salads are the focus of summer – may teach the company the wrong lessons about where to focus menu innovation and promotional activities. Better demand planning based on a deeper understanding of data can save critical profit points in a notoriously low-margin business. Data investment can be under-resourced, but present a significant opportunity for established food retailers.

Remember the power of doing one thing well.

Starbucks – once a lone coffee shop in Seattle – is just one example of the power of doing one thing really well for a very long time. While they’ve increased their menu options over the years, they’ve never lost focus on what drives people into their cafes: the coffee. As resources and fiefdoms within large companies multiply, it can be hard to stop menu item proliferation and operational complexity can mushroom beyond expectations. Not only can this be hard to manage effectively, but consumer research has also shown that when consumers have too many options (say, twenty-four types of jam) they are less likely to purchase anything at all. Start-ups don’t typically have the luxury of presenting too many options to their consumers. By keeping consumer options limited and simple, they reduce the costs of complexity. Meal delivery companies like Sprig, Munchery, and Maple, all present a handful of rotating options to consumers each day. The options change but they stay focused on the goal of getting a great meal quickly to their customers at a reasonable price. While the supply chains of established companies may not move as quickly, these start-ups show the importance of focusing on the one thing – be it an ethos like fast delivery, or a product like coffee – that makes your company stand out, and not becoming confused in your message to consumers over time as capabilities multiply.


The food start-up landscape provides many instructive examples for established food retailers. By taking the ideas of failing fast and failing small, following the data, and doing one thing well, established companies should take the best lessons from food start-ups and apply them to their businesses.

About the Author

Lauren Raouf

Lauren Raouf is a consultant focused on the retail and consumer goods industries, with a particular interest in food and beverage companies. After spending five years working at the Boston Consulting Group in Washington DC and London, she’s made her way to Chicago and helps companies understand consumer behavior and the organizational requirements needed to deliver growth and change.

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