“Location, location, location.” What has long been a truism in real estate now applies in more and more industries. Today, knowing precisely where your customers and your assets are at any given moment is equally as important as knowing who they are—and leveraging that data to predict what they’ll do next is the source of real disruption.
Take transportation, for example. Companies are using predictive analytics to do a kind of fleet- and routing optimization that simply wasn’t possible before. Amazon, meanwhile, holds a patent on “anticipatory” shipping and has started delivering packages straight to customers’ cars. Want an unbeatable edge in e-commerce? Deliver the right thing to the right place at the right time before customers know they want it.
Companies are beginning to unearth the “ground truth” in location data. In mapping circles “ground truth” refers to observations collected firsthand so, as this new granular information is combined with other data sets, once-hidden or obscure relationships can become visible and the predictive actions that once seemed impossible will become commonplace. Companies like Esri, the brains behind the industry standard location intelligence and mapping platform, ArcGIS, are poised to lead the location intelligence revolution, and give companies an edge through new predictive capabilities.
Here are five industries that could be transformed by this compelling technology.
Retailers have long relied on location intelligence for site selection, going back to the days of McDonalds’ pairing of detailed demographics and aerial photography. But with e-commerce eating the world, understanding customers’ “path to purchase” before they’re able to even articulate their desires is critical.
Some retailers use location intelligence to augment customer experience in their best-performing markets, whether through unique features or personalized service. Others use it to customize the product mix in a given store to reflect local trends.
But as their predictive powers have grown, the savviest retailers are moving from rapid reaction to prediction and anticipation. Walgreens, for example, publishes an annual “flu index” mapping antiviral prescription data to create a snapshot of flu season faster than the Centers for Disease Control. Influenza is far from the most lucrative viral phenomenon, of course, and this points toward one method for being faster than same-day shipping—by being there first.
“Amateurs talk strategy; professionals talk logistics,” General Omar Bradley once said, and manufacturers long ago took his advice to heart. Hyper-optimized supply chains circle the world, and location intelligence ensures there’s enough slack to reroute around disruptions.
But all of that begins to change with heightened powers of prediction. As Amazon’s patent and the rise of consumer subscription services such as Birchbox suggest, the future of manufacturing may be customized and anticipatory. Rather than replenish inventory, for example, manufacturers may opt to carry no inventory at all, relying on predictive models to produce and ship replacements ahead of demand. Other might try to turn their supply chains inside-out, specializing in predictive shipping (and returns) to hone their understanding of customers.
With more frequent and more powerful storms becoming a fact of 21st century life, predicting the path of hurricanes and their downstream effects has become critical for disaster recovery. With Hurricane Harvey bearing down on Houston last fall, Esri worked behind the scenes with the National Weather Service to calculate when, how, and where the storm’s accumulated rainfall would surge across the flood plain, and allowed them to predict flood heights days in advance. Working with these forecasts, the Red Cross was able to steer storm victims toward shelters on higher ground and close those that would soon be underwater.
In the future, similar predictions could be used to revise risk models and preemptively save assets, mitigating at least some of the $125 billion in property damage caused by Harvey.
Getting lost or stuck at a red light is expensive; UPS famously saves more than 100 million miles a year by routing its trucks around left-hand turns. Although Waze and Google Maps have been a similar boon for drivers, there’s nothing comparable for where people spend most of their time: inside buildings. Mapping indoor spaces with the same fidelity as city streets not only holds promise for way-finding (where’s that conference room, again?) but also for what might be called “human task routing”—turn-by-turn directions for work.
Combining task routing with predictive maintenance could optimize the efficiency of both people and machines. “Think about someplace as big as an airport, with 10,000 employees,” says Cross. “How do you optimize their work spatially? Step one, fix this duct…”
It’s one thing to predict the best route; it’s another thing to predict where the roads will be. In the oil-and-gas patches of Alaska and west Texas, the landscape is always shifting, whether due to climate (ice tracks that are no longer frozen) or the fact that someone drilled a new well in the road. Today, Esri is collecting traces of off-road vehicle traffic to calculate where the next roads should be, and to automatically route vehicles along them. For once, the map is the territory.
This story was created for and commissioned by Esri.