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A Q&A with Euro and Jack of Guac
Have you ever wondered how grocery stores stay ahead of demand and avoid shelves of expired food? It’s not easy. Everything from weather, to supply shocks, to events can have a dramatic effect on how much inventory they can and should carry. Not to mention, every grocer is unique and has a completely different set of suppliers and shoppers to best support.
Euro Wang and Jack Solomon founded Guac to provide a solution for grocers to help them cut their food waste, reduce ordering mistakes, and provide a better consumer experience for folks hoping to browse shelves stocked full of their favorite grocery items. Guac combines cutting-edge ML technology with hundreds of external data points tailored to specific grocery stores: weather, sports events, tourism spikes, health indicators, local demographics, store layout, and much more.
Fresh off the heels of their $2.3M seed round funding announcement in TechCrunch, we sat down with Euro and Jack to chat more about Guac’s climate impact, their innovative software solution, and why they personally became so interested in decarbonizing the grocery industry.
Beyond grocery stores’ high energy consumption and emissions from leaked refrigerants, how does food waste stack up from an emissions perspective?
Food waste accounts for about 8% of all greenhouse gas emissions globally — if it was a country, it would be the third largest GHG emitter behind the US and China. Specifically, when food decomposes in landfills, it generates methane, a greenhouse gas that is at least 27x more potent than carbon dioxide. In addition, any food that is thrown out means that the resources (water, land, energy) used to produce, transport, and handle that food is also wasted. By addressing food waste at the production/ordering level with demand forecasting, we can solve food waste at its root.
Grocers and department managers have been in charge of forecasting for their stores for decades. Can you share more about why and how more tools are needed to help support them make better decisions?
Traditionally, grocers rely on the intuition of experienced department managers, who over time identify patterns in things like weather or public holidays. But the challenge is that grocery demand is influenced by hundreds of variables that are intertwined — hot weather might generally increase apple sales, but hot weather when combined with school vacation and an NFL playoff game day might lower apple sales. It’s impossible for one department manager to keep track of all of these different variables and to process the complex ways these variables interact with demand. We make this possible with machine learning, and we also empower department managers with more information by telling them things like “this 20% increase is because there’s a conference happening nearby”.
How and why did you become so passionate about decarbonizing the grocery industry?
The scale of food waste’s impact on the climate and food security is just enormous. And what’s exciting is that every bit of food waste we save directly results in less methane being emitted and resources being conserved. In addition, solving it from the demand forecasting angle gives us a unique opportunity where we can align profit growth and decarbonization for these massive retailers — which we can leverage to make an outsized impact on the climate.