If given the choice, my eight-year-old son would eat the same thing for every meal: kid’s bean-n-cheese burrito with black beans (no rice) and sour cream and guacamole. Every. Time. As a parent, I’m fine with this, because it means he’s at least eating. As an adult, however, I crave more variety in my meals and want subtle differences from dish to dish.
But I fear those subtleties and nuances in food will get lost as hardware and software innovations push restaurants towards greater data-driven insights. These insights will translate into actions that will increase predictability. This predictability can mean more profits for business, but more meal monotony for customers.
I got to thinking about this when I wrote about Nectar this week. That company uses high-tech bottle caps to monitor pours and provide real-time analysis of how much booze bartenders are using on any given drink. On its face, it’s a way for bars, already working on thin margins, to better manage their alcohol inventory and spending. But painstakingly monitoring every ounce of every pour could also limit a bartender’s ability and willingness to get creative with their cocktails. Why experiment on the mango-tini if you’re just going to get called out for wasting booze or, in the case of owners, watch every extra drop put in a drink become data that tells you how much money you’re wasting?
And it’s not just impacting what happening behind the bar. Earlier this month at Google I/O, the internet giant launched a new Google Lens feature that combines machine learning, computer vision and a whole bunch of data to let people know what’s popular at a restaurant at that moment. From the Google blog post announcement:
Say you’re at a restaurant, figuring out what to order. Lens can automatically highlight which dishes are popular–right on the physical menu. When you tap on a dish, you can see what it actually looks like and what people are saying about it, thanks to photos and reviews from Google Maps.
This, too, however, seems to be a good news/bad news scenario, as my colleague Jenn Marston wrote at the time:
On the one hand, it could provide valuable information for restaurants when it comes to figuring out what is and isn’t selling on the menu, so chefs and operators could better adjust their planning and inventory (potentially helping them avoid food waste and keep costs down).
But what this will do to the adventure of going out to eat? Part of the fun of the restaurant experience is the guesswork, which would be gone were we to rely too heavily on data-driven recommendations. This seems unlikely at higher-end restaurants and places designed for adventurous foodies, with robust appetites for the unknown. For all the places in between, though, too much knowledge might make the restaurant experience just a little too predictable.
Obviously, when presented with all this new data, restaurants will want to act on it, and what better way to combine precisely monitored food creation with consistency than with a robot?
We cover robots a lot here at The Spoon. (Heck, we dedicated an entire conference to food robots.) A big theme we’ve found again and again when it comes to restaurants and robots is that a robotic workforce can do repetitive tasks far more precisely and consistently than any human, which means little to no variation in the end product. The machine will make the meal the same way, every time.
Again, this isn’t necessarily a bad thing in and of itself. The robot-created cheeseburger at Creator is delicious, and if I go back to San Francisco, I know it will be delicious in all the same ways if I order another one.
But if restaurants have the tools to know exactly what food sells and when, and they have a machine that will successfully replicate those popular meals over and over, then what we’ll get is… the same meals over and over and over. The ability for cooks (or customers) to experiment will be limited at best, eradicated at worst. The restaurant experience becomes more like a pre-determined assembly line constructing widgets, rather than a real meal.
The question of data insight versus art certainly isn’t a new one, just ask baseball. The difference for the restaurant industry, though, is scale. Everyone eats (even at baseball games), and restaurants, in an effort to drive more sales and eke out more profits, will optimize their businesses around data. The end result will probably taste good, but in a way that feels more mandated from management.
As long as they serve bean-n-cheese burritos, I know at least one person who will be happy.
Join us to talk restaurant tech at the Smart Kitchen Summit, our flagship foodtech conference on Oct 7-8th in Seattle.