What Do Football Teams and Winning Retailers Have in Common? Data-Driven Agility

machine learning

As a particularly exciting NFL season is about to culminate in Arizona in February, one thing I’ve noticed recently is the emerging role that real-time data now plays in pro football. Beyond preparing an advance game plan, most teams now leverage data and technology to make improvements mid-game

Many of us can remember a time when the most valuable equipment on the sidelines of a game was probably a hefty cooler of Gatorade. Not so today — coaches and players now rely on mid-game data to quickly make adjustments that directly translate to the scoreboard. Even pro football veteran Tom Brady can be seen diligently studying a mobile tablet on the bench, gaining insights toward running the next series of plays better — as well as capitalize on his opponent’s weaknesses. Waiting to review game films the following week just isn’t enough anymore.

“Game-changer” is a buzzword that’s probably been thrown around a bit too much. But as with professional baseball, NFL teams are uncovering new layers of next-generation analytics that are literally redefining their sport — from tracking an individual player’s speed on the field to their physical recovery rates after practices, games, and injuries. 

Witnessing this new age of “data-driven” football, it’s easy to draw parallels with retailing. In both worlds, old playbooks revolved around chasing yesterday’s numbers, but today’s retail winners are turning to advanced data science — specifically AI and machine learning — to determine critical mid-season adjustments and tally additional points to their scoreboard.

It begins with pairing the right data, including seasonality, pricing, promotions, and projected product lifecycles with AI modeling for accurate, hyper-localized demand forecasting and planning, effectively anticipating and “tackling” rapid consumer shifts — more important than ever in this volatile post-pandemic economy.

Data-driven allocation and replenishment ensures that retailers continually stock the right products across both stores and DC locations — agilely maneuvering around sudden supply chain disruptions — to avoid costly immobile excess inventory, or that ultimate retail “fumble” — the frustrated shopper who tires of perpetual out-of-stocks and takes their business to a competitor.

AI-powered lifecycle pricing empowers retailers to get a step ahead of traditional seasonality and outmoded ad hoc markdown processes to deliver optimized sell-through at maximum margins across every SKU — from reliable star performers to those underachieving “second-stringers.” AI/ML pricing solutions have proven essential for determining every product’s elusive sweet spot — fastest sales volume at highest net profit.

Gridiron metaphors aside, there clearly are similarities between the data revolution in football and the data-driven innovations retailers are adopting around every aspect of their operations. Step one is accessing the relative value of a specific data set, the next is to actually leverage that data into an actionable game plan. At antuit.ai, we hope you’ll be pleased with the outcome of your favorite NFL team this season — and we’ll continue to root for your retail team, now and into the future.

— Sivakumar Lakshmanan, CEO, antuit.ai, now part of Zebra Technologies

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