The early diners are dawdling, so your 7:30 p.m. reservation looks more like 8. While you wait, the last order of the duck you wanted passes by. Tonight, you’ll be eating something else — without a second bottle of wine, because you can’t find your server in the busy dining room. This is not your favorite night out.

The right data could have fixed it, according to the tech wizards who are determined to jolt the restaurant industry out of its current slump. Information culled and crunched from a wide array of sources can identify customers who like to linger, based on data about their dining histories, so the manager can anticipate your wait, buy you a drink and make the delay less painful.

It can track the restaurant’s duck sales by day, week and season, and flag you as a regular who likes duck. It can identify a server whose customers have spent a less-than-average amount on alcohol, to see if he needs to sharpen his second-round skills.

So Big Data is staging an intervention.

Both startups and established companies are scrambling to deliver up-to-the-minute data on sales, customers, staff performance or competitors by merging the information that restaurants already have with all sorts of data from outside sources: social media, tracking apps, reservation systems, review sites, even weather reports.

They have an eager audience. The NPD Group, a market research company, is predicting “flat” growth in 2017 restaurant traffic, with a 2 percent decline among full-service restaurants and no growth for quick-service restaurants. A 2016 National Restaurant Association survey reported that 4 out of 5 restaurateurs believed that business would improve if they embraced technology, and a third worried that they were lagging in those efforts.

“Silicon Valley looks at inefficiencies in the world, and they aim to disrupt the food space,” said Erik Oberholtzer, a founder and the chief executive of Tender Greens, a quick-service chain based in Los Angeles that is using data to guide its East Coast expansion. “I mean that in a good way.”

In the old days, restaurateurs used ledgers to track sales, and scribbled notes about their customers’ preferences or idiosyncrasies. Then along came point-of-sale software and reservation services that provided more sophisticated records and analysis, but created a tech tower of Babel, with most systems speaking their own dialect.

Avero, a New York City-based company founded in 1999, defined the next generation of analytics: It translated data into a common language, added external data and generated an easy-access overview of inventory, food costs and sales, accounting, scheduling and customer behavior. “Not 40 systems with 40 passwords,” said Avero’s founder, Damian Mogavero.

Newer companies now aspire to eliminate the need for translation, to create an analytics program that integrates all aspects of a restaurant’s operations into one system, with one password, in real time with mobile access, said Shu Chowdhury, the chief executive of a startup called Salido. One of its initial investors is the chef Tom Colicchio, who is using it as he revamps and expands his chain of ‘Wichcraft sandwich shops.

These new tools make a paradoxical promise: that they can take restaurants back to the good old days, before the business grew so big.

“The goal,” Oberholtzer said, “is to leverage the technology to do what we would do if we had one little restaurant and we were there all the time and knew every customer by name.”

Oberholtzer and his two partners opened the first of two dozen cafeteria-style restaurants in Culver City, California, in 2006, and plan to open an equal number in the Northeast by 2020. Every new Tender Greens will rely on what he calls “a whole rebuild of technology,” because the 11-year-old system it uses is about as up-to-date as a beeper.

He has decided on a combination of three systems that “play well with others,” he said, so there’s no communications problem: Brink POS software, a point-of-sale system that Oberholtzer says “is robust enough to handle volume and simple enough for our teams to use easily,” an essential combination for an expanding company; Olo, to coordinate online ordering and delivery; and the Punchh mobile app, which logs each customer’s name, email address and purchase history.

“It gives us ways to recognize people who’ve been in regularly, or haven’t been in for a while or have specific preferences,” Oberholtzer said.

A regular diner who always orders the niçoise salad will get a message on the app about the halibut special. A diner who always orders vegetarian options will not get the message about the summer hog roast. “We want to accommodate everyone’s needs,” Oberholtzer said, “sometimes before they even mention them.”

In Chicago, at the Michelin-starred Oriole, where 28 diners sit down each night to a $190 tasting menu, the owners, Noah and Cara Sandoval, rely on data from the Upserve system to identify their top 100 guests in terms of numbers of visits and amount spent, but that’s just the start. The system also creates a profile with every first-time reservation.

“You can’t know that someone’s going to become a regular, so you don’t necessarily keep track of those people,” Sandoval said. “But the system does.” It also tracks the top 100’s dining companions when they split the check. Upserve sends a list of credit card numbers, dates of visits and items bought; the restaurant matches each number to a name, and a search on Google, Facebook and LinkedIn provides a face to go with it.

“We’re sure to recognize them” the next time they come in, so the staff can welcome them back by name, Sandoval said. “It surprises people, in a nice way, when they didn’t make the reservation themselves.”

Even the type of credit card contributes to the dossier. If a customer pays with an airline card, a server might mention travel. If a customer is a sports fan, he will most likely get a server who is as well.

The food gets similar scrutiny. Upserve offers a “magic quadrant” feature that divides dishes into four categories — “greatest hits,” “underperformers,” “one-hit wonders” that are popular with first-timers but not with repeat visitors, and “hidden gems,” which regulars like and first-timers don’t — to help the Sandovals understand which are popular, and which prompt diners to return.

Customers who find the mining of personal data invasive can opt out, up to a point, but it requires effort: To avoid detection, they have to pay cash and not make reservations. Those who participate actively in the process get more information in return.

In June 2015, the online reservation service OpenTable, which represents 43,000 restaurants worldwide, started to provide customized recommendations, just as Netflix and Amazon suggest programs or products based on a customer’s history.

If users sign up for the company’s app and allow OpenTable access to their GPS, they receive recommendations for restaurants in the United States and several foreign countries,said Scott Jampol, the company’s senior vice president for marketing.

And if data can help a customer find a restaurant, it can also help a restaurant find its customers. To pinpoint potential locations in the Northeast that best reach what Oberholtzer calls Tender Greens’ “psychographic” — the college-educated diner who cares about health and locally produced food — he starts with data from a customer analytics firm that specializes in site selection.

He refines that list with Google searches like “plant-forward lifestyle,” he said, and looks at where delivery systems like Uber and DoorDash do a lot of business.

“You overlay and look for redundancy,” he said, “and that begins to tell the story of where you want to be.”

But successful growth makes it hard to keep a sharp eye on operations. Charlee Williamson has been with the New Orleans-based Ralph Brennan Restaurant Group for 24 years, and keeps track of six managers and 78 servers at the Jazz Kitchen, thousands of miles away at Disneyland in California. She relies on the Server Scorecard, a feature offered by Avero.

The score card ranks servers on multiple criteria, which makes it easier for Williamson to identify the right waiter, for example, for a large party with children. She might not pick the server who sells the most. The more appropriate match could be a server who ranks higher in tip percentage than in sales, thanks to grateful families who tend to order less alcohol.

The message to restaurateurs is simple: Ignore data at your peril, said Mogavero, the author of a recent book, “The Underground Culinary Tour,” about how data has transformed the restaurant industry.

Startups aspire to create even more streamlined software, but it isn’t easy. “We’re making a moon shot here,” said Chowdhury of Salido, which originally set an August deadline for “a fully operational stack” of features but is only about three-quarters of the way there. The company has extended its deadline to early 2018, as development work continues with 64 existing clients.

The basic point-of-sale part of the program is already in use in New York at Made Nice, the new fast-casual restaurant from the chef Daniel Humm and Will Guidara, owners of Eleven Madison Park and the NoMad, and at Jean-George Vongerichten’s ABC Kitchen.

Still, some early adopters approach the new systems warily. Guidara, who also uses Avero at Eleven Madison Park, thinks technology is great for a fast-casual operation that emphasizes volume and delivery, and for the business side at a fine-dining operation. It has no place, he said, when it comes to service at Eleven Madison Park or the NoMad, where he and Humm rely on traditional methods of high-end hospitality: expertise, eye contact and a hair-trigger response to a diner’s every need.

“When I worked as a controller, in accounting capacities, we used it quite often,” Guidara said. “But from an experiential, guest-facing point of view, we don’t use it. That’s never been how we approach things.”

The chef David Kinch owns Manresa in Northern California, which won its third Michelin star in 2016. His reservationist does a Google search on every guest to ferret out basic information like occupation or interests, and then he relies on a highly trained staff, including a concierge and two master sommeliers, to work the room and ensure everyone is happy.

“I’m pushed constantly about these new systems,” Kinch said. “People say it’s all about the guest? I think that couldn’t be further from the truth. I place a tremendous value on direct eye contact and a genuine smile.”

At Oriole, the Sandovals have left sake on the menu despite data showing that it doesn’t sell well. “We go by our gut,” Sandoval said. “It pairs well with a lot of the courses, it’s very versatile, and it speaks to how we’re willing not to go the traditional route.”

The sheer glut of new restaurant data systems can be overwhelming, even to those who embrace them.

“At least once a week, I get something about a new startup with a new gadget that’s going to make our lives so much better,” said Sisha Ortuzar, Colicchio’s partner at ‘Wichcraft. “They’re distractions. We just want to get back to making sandwiches.”

© 2017 The New York Times Company