Skip to Content

Understanding Your Place of Business


Geospatial thinking gives us a deeper understanding of the communities where we live and work. A geographic approach also gives us a data-driven framework for recognizing how these places are changing and why. This is the clarity that business leaders and organizations need as they plan for the future, predict outcomes, and make decisions to support growth and resiliency.

As the global pandemic's cycle surges and ebbs, our need for accurate, local data multiplies. At the onset, few businesses were prepared for the scale of change this historic event would bring—and demand. Going forward, we are likely to see an accelerated speed of change, coupled with a need for new strategies for resilience to overcome disruption in its many forms. Industries and businesses that can see and measure new patterns quickly will have an advantage.

 

View of a retail shop window in an indoor shopping center

 

Location, broadly understood, has always been key to every business. We forgot that fact a generation ago, seduced by the fantasy that the internet had made brick-and-mortar sites obsolete. It wasn't true then, and it isn't now.

In other words, you need to understand your place of business. 

This starts with your most tangible place, your real estate facilities—the selection, construction, and management of which are being transformed by location analytics. Not only does location intelligence help determine where and how to build new facilities, but also smart 3D maps—digital twins—allow facilities, real estate, and business managers to plug into Internet of Things systems to understand where different assets are as well as their status and condition, from room temperature to the amount of carbon dioxide in the air.

As valuable as location intelligence is to real estate decisions, its greatest benefit may be in helping retailers get closer with their customers. Companies as varied as Fruit of the Loom, Chick-fil-A, and Starbucks are building loyalty programs with a tremendous amount of granularity and hyperlocal analysis, down to the block level. And retail winners are monitoring how the pandemic itself is changing consumers' attitudes and behaviors, which vary with location.

 

Map of San Francisco with red, blue and green dots

 

We saw that in 2020, with some businesses making inspiring gains after the onset of the pandemic. (Think curbside pickup with online ordering from restaurants and retail stores.) In these cases, local data identified customer behaviors and helped define new types of engagement that led to sales results.

Taking a step further, geospatial thinking and location intelligence (LI)—insights gained from data analytics available through geographic information system (GIS) technology—give us the means for quantifying discrete correlations between a place and business opportunities as well as the outcomes achieved. For example, the customer base in an urban hub will vary between the workweek and weekends. Simply looking at local neighborhoods around the store to understand potential customers will produce inaccurate results. Location intelligence can correlate customer commute patterns with store sales during business hours, providing a more accurate and complete assessment of a location's potential customer base. 

Map of Minneapolis and surrounding areas showing retail shopping habits

 

To find the opportunities ahead of us and measure the outcomes using a geographic approach, we must:

Apply sophisticated analysis. Combine a business's authoritative data with demographics and psychographics, such as human movement data; online customer behavior data; and information about local conditions around each store, restaurant, or shopping center—including patterns of COVID-19 recovery. 

Increase targeted consumer engagement. Companies as varied as Fruit of the Loom, Chick-fil-A, and Starbucks rely on loyalty programs to help them get to know their customers, as well as how buying habits are evolving by location. Hyperlocal analysis is possible, even block by block. What about localizing store offerings based on demographics, weather, etc.? At the same time, businesses can target new customers by combining proprietary customer data with consumer spending insights, demographics, and customer segmentation. 

Increase targeted consumer engagement. Companies as varied as Fruit of the Loom, Chick-fil-A, and Starbucks rely on loyalty programs to help them get to know their customers, as well as how buying habits are evolving by location. Hyperlocal analysis is possible, even block by block. What about localizing store offerings based on demographics, weather, etc.? At the same time, businesses can target new customers by combining proprietary customer data with consumer spending insights, demographics, and customer segmentation. 

Prioritize resiliency planning related to climate change. Leading corporations assess their vulnerability to extreme weather events through predictive modeling using GIS technology. This approach also helps decision-makers craft effective contingencies such as rerouting supply chains. Teams at AT&T and the City of Boulder, Colorado, used models that layer climate information, hazard data, and satellite imagery to guide them in deciding whether to reinforce or relocate coastal facilities in areas where storms will increase or allocate more funds for floodplain management. If a bridge or thoroughfare in a major European city temporarily closes, the appropriate supply chain manager can receive a real-time alert once a service is at risk. The manager also gets explicit insight into the issue without having to sort through volumes of information. With that pinpoint awareness from a virtual model, the company can shape its physical response, rerouting deliveries as quickly and efficiently as possible. This type of transparency ensures your business can continue to meet customer needs and maintain long-standing relationships with them.

Embrace transformation in the supply chain. Location intelligence is making the supply side of retail more visible in response to growing consumer interest in the traceability of products and services. Leaders at UPS and FedEx are among those providing transparency into the way they run the business—essential for brand health, legal compliance, and operational logistics. Location is the thread linking all elements across a supply chain—from component supplier to factory or farm to container to trucker to store. 

Adopt new forms of location-specific data and analysis. This includes artificial intelligence (AI)-based halo forecasting hosted in the geospatial cloud. Halo forecasting calculates how digital and brick-and-mortar stores intersect for consumers. How much did having a store in a market affect digital sales and vice versa? Analysts are finding that the halo effect can add as much as 20 to 30 percent to a physical store's sales. Retailers are combining artificial intelligence, big data analysis, and location intelligence to move beyond averages in quantifying how much revenue they can expect physical locations to drive to the digital channels. Analyzing digital and physical sales together creates a much more holistic forecast for a business in each market.

Geospatial thinking and location intelligence allow us to understand our communities and our customers better than we ever have. This means that even in uncertain times, we can grow our businesses and become more resilient, especially as we find new ways to apply the technology in the service of our customers. 

By Cindy Elliott, a thought leader in how geospatial information drives business transformation for Esri.

Stay updated


Sign up for The Esri Brief executive newsletter

The Esri Brief, a biweekly email newsletter, connects business leaders with thought-provoking perspectives on location intelligence and critical technology trends.