Inventory Management Takes a Digital Step Forward | Food Newsfeed
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Restaurants tend to keep their inventory lean, particularly with perishable items like produce.

Inventory Management Takes a Digital Step Forward

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Big data means big improvements for restaurants.
By Nicole Duncan February 2018 Technology

When it comes to P&L statements, inventory can sometimes be the redheaded stepchild, often overlooked in favor of labor costs and restaurant sales. For years, those oversights could be partially chalked up to an archaic system wherein amounts were recorded by pen and paper. Without a centralized system, multiple employees might count the same products twice. 

But new advances in digital inventory management are streamlining the process while also providing insights that were until recently out of reach.

"If you look at inventory as a business process, there hasn’t been a lot of change in the past 40 years in that process. The tools, however, have changed dramatically in just the past five years,” says CEO of Mirus Restaurant Solutions, Dave Bennett. Mirus, along with other management solutions like Delaget, Compeat, and Oracle, collects data from the point of sale, business software, and other sources, including external data points, to paint a more detailed picture of an operation’s inventory. 

According to the Environmental Protection Agency, in 2014 the U.S. generated more than 38 million tons of food waste; food is also estimated to be the single largest material to reach landfills and incinerators. While a good portion of these losses can be attributed to non-commercial use, the amount of food waste from restaurants still accounts for hundreds of millions of dollars in lost inventory. This is why, Bennett says, restaurants like to keep their stock of foods—especially perishable goods—lean. The problem arises when unforeseen foot traffic leads to a supply deficit. 

“Some events cannot be predicted, but many events are actually repetitive; the restaurant manager just didn’t know about it,” he says. “You probably don’t need to look at all of those sets of data, but some of them may correlate well with your customer traffic. The challenge is to find the external data that has that high correlation.”

So while it’s impossible to predict the weather, big data can show past correlations between rainy or cold weather and customer visits. Same goes for other seemingly insignificant factors like hotel occupancy, airport traffic, and local school events. Mirus says even cell tower activity could be factored into these projections to anticipate sales activity.

And as big data becomes more refined and widespread, an even bigger slice of the restaurant industry could soon be wielding its insights for inventory—and beyond.