Dick's Sporting Goods and Wayfair don't have a lot in common. They have different product assortments. They have different physical footprints. They have different e-commerce fulfillment strategies.

But during the pandemic, their tech teams found a similar truth: They could better serve consumers by giving them a more detailed picture of their supply chain, specifically real-time inventory. To do that, they needed operational and technological agility to deliver accurate information to the customer in real time.

As gyms closed and consumers started working out more at home, fitness equipment demand rose and scarcity set in as supply chains struggled to keep up. But at the same time, shoppers began to show a new willingness to travel farther to get that equipment as soon as possible.

"Because we didn't have maybe a 35-pound dumbbell [at the closest store], they would drive an extra 10 minutes to go to the store down the road to pick it up on the same day," Jay Piskorik, director of platform engineering for Dick's, said at the National Retail Federation's Chapter One virtual conference Thursday.

The tech team at Dick's noticed as the pandemic went on, shoppers were less inclined to wait for two-day shipping and more inclined to drive a longer distance to pick up an item from another Dick's location.

"We were seeing a lot of these changes. So, we had to adjust, kind of, how we were presenting inventory," Piskorik said.

Dick's has been shipping some online orders from stores since 2013, so it had the data ready to go. But the pandemic upped the scope and the stakes for the accuracy of inventory data and the velocity and volume at which that data needed to move to be presented to the consumer. The team needed to build the data processing capacity to present more data to each visitor to the site, every time they visit, without fail — at a time already bringing record site traffic.

Piskorik described months of backend work to seamlessly connect the company's warehouses and stores to its website. The Dick's team was adjusting data capacity right up to the days before Black Friday and Cyber Monday 2020, leaning on data structure provided by Redis. The site had seen cyber weekend level traffic at various points through the pandemic, so scaling for the real thing meant dialing up capacity even further.

Fulfillment makes the sale

Without physical stores, Wayfair found another way to satisfy changing consumer needs during the pandemic. More time at home sent shoppers online looking to upgrade decor and furniture, presenting an opportunity to Wayfair. But production backlogs and delivery delays have plagued furniture retailers during the pandemic.

NRF moderator Phil Hall, pre-sales data analyst for Looker, a data analytics platform acquired by Google in 2019, mentioned that Wayfair's ability to clearly reveal in-stock status and delivery timing sold him on a furniture purchase from the site recently. Matthew Hartwig, associate director of product management for data infrastructure at Wayfair, confirmed sharing supply chain data with consumers became a high priority.

"Early in the pandemic, the supply chain was one of the most acute pain points. How do you forecast demand, supply, trucks, staffing, in an entirely unprecedented period of time?" asked Hartwig. He chalked the company's success in wielding and sharing supply chain data with the customer up to a culture of quick decisions at the company.

"If you need to go and talk to five different teams and get on all of their different backlogs to be able to get an answer, you're not going to seize the opportunity as it's presented," Hartwig said.

Wayfair has spent years building its supply chain, warehouse and logistics capacity to be ready for the growth it saw during the pandemic, though it was perhaps not expected quite so fast. The capacity-building required to contend with the increase in digital sales spurred by the pandemic was on the tech side. Before the pandemic, the company worked with on-premise technologies and planned future capacity needs once or twice a year.

The company shifted to Google Cloud just before the pandemic in the normal course of planning for growth. And Hartwig said, without that decision, "Wayfair would have been sunk." When the pandemic sent data volume up 150% YoY, explained Hartwig, Wayfair's machine learning models would have slowed their training frequency.

Real-time inventory location and a realistic time-frame for delivery are just two supply chain data points that gained importance with shoppers in the pandemic. Customers' priorities changed, and so did the way online retailers could best serve them, as long as they had a digitized supply chain and the data storage and processing capacity to deliver.