Using Spatial Analytics & GIS in Retail Supply Chains to Respond to COVID-19

Introducing Spatial Analytics and GIS into the Conversation

A couple weeks ago, I was talking with a neighbor whom I hadn’t spoken with in some time. I had seen him, of course. But because of the COVID-19 pandemic, this was the first time we were interacting face to face. 

 As our kids played together, we started catching up and the coronavirus inevitably worked its way into the conversation. I asked him how he was adjusting, and vice versa. And, because he works in retail supply chain, I asked if his company was using spatial analytics to help manage its inventory.

 “No,” he said, “we aren’t.”

The topic was fresh on my mind because of a recent Zoom interview I had with Cindy Elliot, the head of the commercial industry team at Esri. Because Esri builds mapping and spatial analytics software, also known as geographic information systems (GIS), we discussed the importance of spatial analytics, specifically in retail supply chains. 

This type of technology offers substantial benefits in managing supply chains to be more responsive AND efficient, which is particularly important given the current economic and social conditions. I wondered why the opportunities presented by spatial analytics aren’t more widely known, and I used the opportunity to share some of what I’d learned about how retailers are dealing with COVID-19 using these tools. 

What Are Spatial Analytics and GIS?

Spatial analytics and GIS allow us to dive into human interactions more closely by looking for insights on geographically-connected data. This analysis is based on location, anywhere from a community perspective to a neighborhood perspective. The key is that it’s a specific, narrow point-of-view. This somewhat counters traditional thinking, which emphasizes the “big picture.” While the big picture is important, supply chains definitely can benefit from looking at the nitty gritty details – localized analysis. 

 Elliott explained that this allows for better understanding of what’s actually happening with supply chains in general but especially as they relate to COVID-19. Different locations around the world are different based on their demographics. For example, an area with an older demographic is likely more vulnerable and impacted than an area of a younger demographic. Getting in the weeds of those differences provides insights for better decision-making. There is no single answer to what’s happening and why it’s happening for all communities, so spatial analytics allows us to look at things from a different (closer) perspective and discover trends and connections that inform supply chain management decisions.

An Example of a Prepared Company

Elliott illustrated this point with an example from the unprecedented disruption in the retail supply chain industry. At its core, retail supply chain is about getting products from manufacturers to customers through a retailer, and some organizations are more prepared for disruptions in that process than others. For instance, HEB, a grocery store chain based in San Antonio, Texas, used insights from spatial analytics to adapt quickly to the pandemic. 

 HEB sources its products across the globe, and following the H5N1 crisis, they established an Influenza and Pandemic Task Force. In early January 2020, they immediately started having daily calls with their suppliers in China, and then, over the following weeks, they started establishing that same daily cadence with their European partners and providers, as well.

Elliot explained that they did this for a few reasons:

1) to understand what was going to disrupt their supply chain,

2) to start looking at what was happening in those communities, and

3) to establish the customer demands in their different Texas locations and how they were changing. 

HEB used spatial analysis to pinpoint their store locations, which then led to depicting what those particular communities looked like in terms of customer demographics. How was the virus spreading depending on the location? The people? The geography? 

Once the data from spatial analysis was gathered, the next step was finding necessary resources. That is, finding supplies to match the demand at a community level. 

“HEB knew that as a first responder, they needed to provide those services and support to their communities as much as they could and as quickly as they could,” Elliott said. “In addition to responding to customer demand, a key aspect of this is looking at new vendors that they wouldn’t have found otherwise.”

Once again, we’re looking for those small details rather than painting one big picture.

So, Why Spatial Analytics and GIS in Retail Supply Chains?

Being as prepared as possible is a great first step when countering a global pandemic, of course, but being able to adapt to the constant change is just as important. 

Some businesses are responding proactively rather than reactively in certain areas, appealing to the needs of those living there. At the same time, other businesses are declining in resources, action, and prosperity. According to Elliot, people are asking questions such as:

1.) Do I have the workforce that I need?

2.) Do I have the equipment that I need?

3.) Do I have the supplies I need in the right locations to serve the customer at the right time? 

Retail supply chains use analytics to configure the allocation of resources, but as conditions change, uncertainty increases. For example, a business that was open yesterday might be closed today due to a localized flare up of the virus. 

Spatial analytics is helping normalize the COVID-19 disruption and provide insight into specific demographics rather than finding a single national or even regional solution. Using spatial analytics, we can predict that community flare up and have at least a few days to adjust supply to meet new demand patterns.  

After having such an insightful conversation with Elliott, I think back to my neighbor and how this type of information could really help his business make better decisions. If our retail supply chains can harness the power of spatial analytics to our advantage, the information we gain could prove extremely valuable to how we counter COVID-19 moving forward as the nation re-establishes the economy.

Acknowledgement: An enormous thank you to Cindy Elliott, Maddi Heise, Stephen Caldwell, the Sam M. Walton College of Business and the SCM Research Center at the University of Arkansas for their support in developing this article.