NEW YORK — Timothy used to be struggling at work. He’s a waiter at the Landmarc restaurant at the Time Warner Center, a classy-but-accessible eatery that serves bistro fare to Manhattan shoppers. By some measures Timothy has always been a great worker — he clocks in on time and never forgets an order. But his sales of beverages and side dishes were falling short last year.

In one month, Timothy (not his real name) served 426 customers, pulling in $17,991.50 in gross sales with a per-check average of $42.23. That’s $3.84 below the overall per-check average at the Landmarc. It turns out that while Timothy was beating the rest of the waitstaff in add-on sales like bacon or cheese on a burger, he was lagging 2 percent behind everybody else in red wine and liquor sales, and a whopping 14 percent behind his peers in sides like French fries and creamed spinach.

The bottom line was $1,636 of lost sales opportunity in a month — the money Timothy would have made if he’d hit the server average.

We know all this because every item sold at Landmarc — down to the last malbec, martini and red quinoa pilaf — is individually logged and enumerated by a sophisticated software package called Slingshot. The software slices, dices and crunches the data every night, and then serves it to managers with breakfast the next morning.

So when Timothy was up for a performance review last summer, the restaurant’s general manager knew everything about him — information she incorporated into a heart-to-heart talk about improving his average.

Some of the nation’s top eateries are quietly embracing data mining to eke out profit in a tough economy.

“It used to be that a manager would say, ‘That server’s great! He’s a nice guy, he shows up on time and keeps the salt shakers full,'” says Damian Mogavero, the entrepreneur behind Slingshot. “Now they can tell a server, ‘You sell 40 percent less red wine than your peers and you work in a steakhouse!'”

Welcome to the data-driven, number-crunching future of restauranteering. With the food business thriving again in the midst of America’s economic upswing – consistently claiming a whopping 4 percent of GDP — some of the nation’s top eateries are quietly embracing data mining to eke out profit in a tough economy. Software systems like Compeat, Hotschedules and Eatec help restaurants track complex metrics like sales trends, employee overtime, and food orders from suppliers.

The most ambitious software is Slingshot, which is tailor-made to bring restaurant waitstaff up to snuff with simple, human-scale tweaks. The web-based software system is the main product of Avero, LLC, Mogavero’s 12-year-old New York-based company. Avero tracks over $13 billion of food and beverage sales a year for 2,700 restaurants. In New York City, half of Zagat’s top-50 restaurants are clients, and on the Las Vegas strip, a whopping 94 percent of casino restaurants use its products.

That success didn’t come easily. The restaurant business has trailed just about every other big-money industry in wielding hard data to increase sales and boost efficiency. Even now, despite the high-tech point-of-sale machines and the daily specials displayed on iPads, restauranteering is still dominated by paper receipts, guesswork and hunches. Even if a waiter punches an order into a computer, little happens with that data after the customer walks out the door.

“When it comes to reporting, there are a lot of historic limitations to the ability to crunch your own data,” says Peter Hansen, director of operations at Landmarc, a group of four New York City restaurants with 550 employees, including the Time Warner Center restaurant where Timothy works.

Mogavero knows those limitations well. The 41-year-old entrepreneur started off as an investment banker on Wall Street, and then joined a restaurant group as CFO in the 1990s. That job put him in contact with some rising New York chefs who, he learned, were struggling to keep an eye on their bottom lines. Mogavero founded Avero in 2000 to mash up the data-crunching skills he’d mastered on Wall Street with the restaurant experience he’d developed later.

Something of a restaurant statistics quant, Mogavero approaches restaurant sales figures with a “Moneyball” mentality, breaking down the strengths and weaknesses of each server and bartender the same way a baseball GM would study the on-base and slugging percentages of his players.

Slingshot immediately found a home with a few big-name chefs like Tom Colicchio, Danny Meyer and Daniel Boulud, who then took the software with them as they as they leveraged their brands into spin-off restaurants around the world.

“Avero’s analytical tools are a platform for maintaining consistent management goals and standards across our brands,” says Boulud, a French chef who started using Slingshot in New York City at his Michelin three-star rated Daniel, and then added it at his trendy DBGB and his new restaurants in London and Beijing.

Data mining found a particularly welcome home on the Las Vegas strip. Spurred by the opening of Wolfgang Puck’s Spago restaurant in 1992, Vegas has transitioned from the land of buffets and steak and eggs to a high-end dining destination, and casino owners wooed chefs from the coasts into opening top-shelf dining brands out in the desert.

Avero’s software, it turns out, is particularly attuned to Sin City’s ethic. Casinos had already mastered data mining in every other part of their business — they could see how much money their croupiers were raking in and which tables, and which video poker machines were generating the most money. Now they could finally get that kind of granular data from their restaurants.

“It’s corporate out there. You need numbers for your ROI,” says Mogavero.

It isn’t just the leaders in the fine-dining stratosphere who desire a better understanding of their statistics. The technology is now spilling into casual dining, with chains like Romano’s Macaroni Grill and Margaritaville picking it up.

In some ways, it seems a little incongruous. Food, after all, is nominally a craft; at its best, an art. And patrons generally don’t rate a restaurant experience based on the server’s alacrity in talking them into a more expensive bottle of wine. But Landmarc’s Peter Hansen says successful restaurateurs have always been mindful of the bottom line, and data-mining tools just give them a way to monitor the details without turning them into accountants.

‘No chef gets in the business to use Excel.’

“If you can give somebody something that doesn’t look like an old school, ’70s-style report that you’re going to toss out the window, that’s what the manager wants,” Hansen says. “That’s what the chef wants. That’s the information that’s the most valuable to the brand.”

“They’re spending all of their time in the office, sifting through administrative bullshit,” says Mogavero, “when they should be in the kitchen and out with their staff and customers. No chef gets in the business to use Excel.”

But what of the future? In theory, there’s no reason why Slingshot’s techniques for monitoring waitstaff couldn’t be adapted to track customers. A restaurant might remember, for example, whether a particular patron is a wine snob, and make a point of sending over the sommelier as soon as the diner is comfortably seated. A customer who ordered the tasting menu with wine pairings at her last visit, could wind up with a great table in the back of the house, while the frugal diner who habitually skips the cheese course goes straight to the cheap seats by the kitchen.

If that’s the logical next step in restaurant data mining, Mogavero isn’t talking about it. His focus remains squarely on the server. Avero recently introduced a new program called Single Server Mentoring, which, in contrast to Slingshot’s wall of detail, identifies the Timothys of the staff in a chef-friendly click. It finds the servers consistently performing in the bottom 10 to 20 percent and shows their boss the keys to bring them up to the restaurant’s sales average.

“Do that with your whole staff and your revenue goes up by about a percentage point,” Mogavero boasts, noting that such a number could be the difference between life and death in an industry that functions on razor-thin margins.

Avero has grown by 20 percent a year for the last three years, and has accumulated $50 billion of sales data. This depth enables it to read trends, predict the ups and downs in the business, and help restaurants compare themselves to other similar outlets, says Mogavero.

For him, training servers doesn’t just mean getting them to ask if customers want fries with their meal. It’s getting the beer guy to learn how to sell a bottle of wine, it’s getting the vegan to sell steak frites and it’s getting the would-be wine expert to stop jabbering about the Côte de Beaune already and sell a side of broccoli rabe with ricotta.

As for Timothy, the server who was selling the pastas and burgers like a pro, but fumbling the Brussels sprouts and Bourgogne rouge — his data-driven intervention last year has helped his personal bottom line. Landmarc’s most recent data shows his total sales now at the waitstaff average. The “lost sales opportunity” is gone, and an extra $1,636 in sales for the restaurant means another $321 in tips.

Joe Ray is a food and travel writer and photographer based in New York City.