A New Solution to the Prime Costs Problem

On Monday, California State regulation went into effect mandating a $20 minimum wage for quick service restaurant workers. While this latest increase makes the cost of restaurant labor in California among the highest in the U.S., I think the debate about whether regulatory action was appropriate, or necessary, misses the larger point about the changing nature of the restaurant business.

Whether driven by regulatory change or just the shifting composition of the U.S. workforce and population, the days of cheap labor for restaurants are a thing of the past. And while inflation has slowed, food costs remain elevated for restaurants as well, and the price elasticity that consumers showed during Covid has vanished.

Restaurants find themselves in a prime costs vice, with few options.

The only sustainable way through this is for restaurants to fundamentally alter how they operate their business, leveraging data and automation to streamline management costs, amplify labor performance, reduce waste, and put their staff in a position to succeed so they can deliver the most possible value to the business.

Today, Fourtop is announcing its partnership with Nekter Juice Bar and Hart House, two brands with a California footprint that are taking an innovative approach to succeeding in the face of rising costs. They are investing in data infrastructure, advanced analytics, automation, and AI, all to support the fundamental principle that quality and service are still the cornerstones of restaurant performance.

Their vision is an inspiration to us. We started Fourtop to give restaurants the tools and capabilities to build towards a future of operations where automated systems and humans collaborate effectively to deliver great guest experience and sustainable business outcomes

We’re thrilled to be helping restaurants thrive in the face of ongoing market challenges, and we’re committed to sharing our collective journey as we chart a new path forward together. 


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Lessons from an Amplified Mistake

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Buy vs. Build: It’s Not Whether, but Where to Invest in Data