Picture this: You walk into a restaurant; the host greets you by name and seats you at your favorite table in the corner. You’ve hardly had time to put your napkin on your lap, and the server is pouring the off-menu wine that you loved on your last visit. When telling you about the day’s specials, the server mentions how close one of them is to a dish you enjoyed recently. There’s no need to wait for the check at the end of the meal or hassle with splitting the bill; they already have your credit card details on file.
If this sounds like VIP treatment at your favorite neighborhood haunt, it’s not — it’s what the restaurant of the future could look like. Anyone who has visited a restaurant recently, though, might be inclined to think that this kind of dining experience is light years away.
The state of restaurant industry technology today
Technology has disrupted — for better or worse — every type of industry, including restaurants. But, in spite of nearly $2.5 billion in global restaurant tech investment since 2012, many restaurants remain reluctant to adopt new products. Our industry is the second largest employer (after health care) in the U.S., but many restaurants remain tethered to outdated technology, pen and paper, or even just hoping that they’re getting things right. I frequently see restaurant operators running point of sale and other systems on Windows XP; they spend hours collecting and concatenating data from various systems, creating complex spreadsheets to complete jobs like payroll, ledger updates, and even sales tracking.
This despite a veritable explosion of inexpensive, cloud-based solutions that can speed data delivery, improve accuracy, and integrate with accounting and labor solutions, as well as food distributors. It reminds me of my friend who drives a broken-down Volvo with a manual choke. “It gets me there,” she says. Sure, it’s a car, but it’s surprisingly expensive to maintain, and it really doesn’t always get her to where she needs to be.
The meal of the future
That said, I can’t really knock the reluctance of restaurants to adopt new tech. They understand that sound data will lead to greater efficiencies and profits, but they also see that there is a huge amount of fragmentation in restaurant tech. The $2.5 billion in investment has been made in more than 600 different companies, most of which offer vertical solutions. You still need one system for scheduling and staff communications; another for ordering and invoice management; another for reservations; and still another for point-of-sale. And that only represents the most basic technical needs of a restaurant.
Think about online ordering. It drives a huge amount of incremental revenue, but every single aggregator wants the restaurant to have a dedicated iPad just to receive their orders. It’s no wonder that making confident decisions about technical updates is hard for the restaurateur.
So where to begin? More best-in-class companies are providing solutions that unify data from various sources, either by normalizing data through partnerships and APIs or by providing the platform that brings disparate data together. These solutions have the potential to take the restaurant beyond operational efficiency; they create insights that also drive hospitality. These providers deliver valuable intel like:
- Which entree brings people back the most
- Which bartender is giving away too many free drinks
- Whether it’s ultimately more profitable to spend ad dollars on brunch or on a wine tasting
- Sales analytics, imported from the POS system, that lets owners compare results over time on categories like repeat customers and new sales
And this is only the beginning. As the technology matures — and more restaurant owners take the leap to adoption — we can expect deeper analytics around menu pricing and ingredient intelligence, and forecasting that helps with staff scheduling.
For restaurant owners, this kind of information is valuable in making operational decisions — pulling low-performing menu items or putting Brian the server on the slowest night because he’s great at upselling wine — but that value is ultimately passed along to the customer as well in the form of more appealing dining options and better service. And the more data gets logged into these systems, the more advanced the insights they offer can be. With a platform that understands a customer from end to end, you can deliver that VIP scenario consistently: As soon a guest is seated, the server can see important information about that guests (visit history, order history, food preferences, and more) and use this insight to deliver a VIP experience. With that level of sophisticated data, the point of sale becomes the point of service.
In most industries, the endgame for data and analytics is automation driven by artificial intelligence (AI) and machine learning, but the restaurant industry may buck the trend. Hospitality is a perfect example of a science-driven art. The people who open and work in restaurants have a love for people and hospitality that would be difficult to reproduce with AI. A machine can probably suggest an entree and wine pairing based on a guest’s dining history, but only a person is going to be able to understand when a guest needs more privacy after a bad day, or a warm towel after coming inside from a driving rainstorm. Those kinds of touches are so important in the restaurant business: They’re the reason that people choose to celebrate in restaurants; they’re why people turn to restaurants during tough times. It’s that sense of belonging and community.
For this reason, it’s likely that data-driven automation in restaurants will initially be focused on operations: things like using sophisticated forecasting to automate scheduling, and to optimize inventory and menu design. There are already a number of players in the market that are delivering hospitality via (mostly) machines. Take a look at what Eatsa is doing, offering fresh, personalized meals via an app, no cashiers needed; or GrubHub, which has some very intriguing ideas about recommendations. I believe we’ll see many more begin to take advantage of technology in the back of the house.
There is a lot of talk in AI and machine learning circles about “human-in-the-loop intelligence” — that is, using humans to augment the long tail of work that machines can’t complete. The machine comes first, and the human in the loop cleans up the details. In restaurants, we’ll see something more like machine-in-the-loop, where the human is at the fore and the machine augments service with the activities that are less central to the guest experience.
Ultimately, the trick for success in the restaurant industry will be how to access and use data-driven insights to improve those uniquely human connections that define hospitality — not to replace service with machines.
Rosie Atkins is the vice president of product at Upserve, a restaurant management platform.