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Cold Weather is Good for Retail—But Only if Stores Plan Appropriately

“Brutal Cold Torments US” was a lead headline on CNN Tuesday. While the story probably sent a chill up the average person’s spine, it likely produced shivers of joy for retailers.

The nation is currently in the grip of “arctic cold” in the East, wind chill advisories as far south as Florida and record breaking cold thanks to “bitter, Canadian air” stretching from the Plains to the East, according to The Weather Channel.

As a result, today’s buy now, wear now consumer is scrambling to load up on hats, gloves, scarves and coats—anything to insulate themselves against hypothermia. It all adds up to a good start to the year for retailers.

But stores can’t live cold snap to cold snap. They have to make sales 365 days a year, a feat made more difficult by the predictably unpredictable nature of Old Man Winter.

This time last year, a Weather.com map showed the majority of the country was enjoying near or slightly above average temps, while the southwest was above average. Only the Northeast and Pacific Northwest felt what the news service called a “cold spell.”

Overlay the 2017 map with the 2018 map and they’d look nothing alike. But too often retailers, and the brands that supply them, use the prior year sales data to inform the following year’s buying and planning.

Jose Chan, vice president of business development for Celect, a predictive analytics company, says you only need to look at stock outs in key cold weather items online to see that retailers’ “backwards looking” approach to planning isn’t working.

“I don’t think anyone was expecting this. If anything, this was a blessing for them,” Chan said, referring to the uptick in sales that has resulted. “But the flip side is they lost out because they could have made the sales had they had [more of the right product].”

But who could have predicted this? Maybe no one, but AI coupled to a nimble supply chain could help. “AI can’t predict the weather, but what it can do is capture trends immediately. AI can factor in sales from yesterday to help you come up with a better prediction,” he said.

That data is useless, however, if retailers aren’t positioned to execute, which is why Chan said retailers must plan for the unexpected. In the case of freezing weather, that means having suppliers they can rely on for basics in an on-demand basis.

While under buying and leaving money on the table is bad, equally detrimental is the years that temps fail to dip and stores are left with a mountain of stock and an avalanche of markdowns.

Frieberg said using last year as a barometer for next year’s performance is an “unforced error” too many store execs commit time and again.

“The weather typically doesn’t repeat itself year after year so the impact might repeat roughly about 15 percent of the time,” said David Frieberg, vice president of marketing at Planalytics, a business weather intelligence firm.

Rather than trying to compare last year’s apples with this year’s oranges, Planalytics takes a much bigger picture approach to figuring out what the true impact of weather might be going forward.

“We take many years of a retailer’s sales histories on a week by week, market by market and category by category basis, match that with our weather data to uncover the correlations and relationships between when weather does this, they sell this much more or this much less. Then we’re able to quantify things on a go forward basis,” Frieberg said. “We can tell them how they should plan for the first week of next January and what that means in terms of units.”

Armed with this information, retailers remove the biases their personal experiences inject into their planning process.

“By removing the historical impacts of weather, retailers will build more accurate financial plans and demand forecasts,” Planalytics said via a report it produced with the National Retail Federation. “Removing weather’s volatility from historical sales creates a weather-neutral baseline.”

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