Nobody likes to wait. And that’s especially true of today’s connected consumers.

Three-quarters (77%) say they would use a checkout optimization function to access estimated wait times, according to a white paper from Cisco Consulting Services, and 60% would rather scan items themselves and pay at a self-service kiosk than wait in line.

That’s why some technology companies are helping retailers streamline checkout using the Internet of Everything (IoE). Adding data and analytics to the connected “things” in the Internet of Things (IoT), retailers can predict rushes, optimize staffing and reduce lines—and perhaps one day, eliminate registers completely.

Retail Dive recently talked to Shaun Kirby, CTO of Cisco Consulting Services, about IoE and how it can be used to streamline purchases, get more information about customers and their habits, and increase loyalty and sales.

RD: How can the Internet of Everything help end checkout hassles?  

Kirby: Checkout optimization is an area where it’s about data—being able to analyze it in new ways and predict further into the future what the demand for checkout will be. Retailers often need to reorganize their workforces to respond to changes in demand. Data analytics helps them do that.

One of the keys is to predict further into the future and more accurately than ever before. We do this by lighting up what we call the “dark assets” with sensors—even very early indicators, like when your parking lot is starting to fill up.

RD: How does IoE reveal such information?

Kirby: There are sensors that can tell when a car enters a parking space. Video is important, too—a camera mounted on a light pole, for example, can not only count vehicles, but also match a license plate to determine if a customer is a repeat visitor, allowing the retailer to give them a personalized experience.

Infrastructure that helps enable IoE will impact multiple areas of the business, [such as] understanding the flow of shoppers. When we combine data from different sensors and apply techniques such as machine learning, we are able to predict as much as 30 minutes in advance what demand at the front checkout will be.

One of the things that we found is an indicator of imminent checkout is the frozen-foods section. These are things people are most likely to put in their carts at the end of a shopping trip. When a sensor shows that milk is leaving the shelf at an accelerated rate, it’s a sure indicator that checkout is going to pick up in about five minutes.

RD: How does this help in allocating staff resources?

Kirby: The intelligence gained by real-time data analysis gives the retailer advance warning, so even if they are shortstaffed because someone has called in sick, store managers can predict traffic and rearrange staff so there is more coverage at the checkout. It works both ways: If we can predict when traffic is going to drop off, you can repurpose cashiers to do other things such as interact with customers or restock shelves.

Today’s queue-management systems look for lines building up, but from the shopper’s point of view, it’s already too late. Just the sight of a few people ahead of you makes you think you’ll be spending 10 to 15 minutes in line, and that can be very discouraging.

With IoE, we are able to completely eliminate lines before they even have a chance to build up. This helps retailers build loyalty and attack the problem of abandonment.

RD: What does IoE offer consumers who want to control the shopping experience?

Kirby: We’ve seen varying degrees of success with mobile checkout—scanning items with a mobile phone and placing them in the cart. The technology is already there with bar codes or QR codes and even near-field communication (NFC).

But what’s really key is that the process needs to be simple in order for shoppers to adopt it. We thought anything a shopper could do to short-circuit the line would be adopted overwhelmingly, but what we found is that the process has to be simple to be adopted.

The other factor that’s key is providing additional sources of value-add. One great example of this is Wal-Mart’s Savings Catcher. It’s popular because it gives people the confidence that they are getting the best deal.

RD: Are consumers willing to provide that information?

Kirby: If retailers can prove the value to the shopper, not only will the shopper buy more and be more loyal, they will be willing to provide more information about themselves. Then, you can understand their paths throughout the store, for example, and how they make their buying decisions.

IoE is going to bring us to the point of symbiosis between the retailer and the shopper, where in exchange for good advice and helpful service, the shopper is going to be willing to provide the information retailers need to provide that help. If value is there, shoppers will give up information in exchange for convenience, discounts, insight, and entertainment.

RD: Will we ever eliminate the checkout altogether?

Kirby: I could foresee a future where there are no banks of registers as we know them today, and checkout takes place throughout the store. Some boutiques are already doing that with clienteleing or a personal concierge—a high-touch approach, if you will.

IoE technologies are going to make the cost of providing a high-touch experience so affordable that many brands that are perceived as lower-end are going to offer a high-touch experience. I don’t think retail associates will ever go away, but they will be playing more relationship-building roles—talking to customers in the aisles or helping with the purchase decision.