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Come Rain or Shine

Come Rain or Shine

October 2, 2019

5 minute Read

After nearly 50 years in the car wash industry, Fred Frattaroli has learned to deal with the maddening reality that his business depends on something he can’t control – the weather.

As owner of Triangle Car Wash locations in several Pennsylvania cities and towns, Frattaroli has tracked the weather every day for 30 years. He jokes that he does it just to aggravate himself, but there’s more to it than that.

Frattaroli knows how rainy summer days keep the customers away in droves. That was the situation this summer as record rainfall doused areas of Pennsylvania. He also knows that nothing douses business for a small-town car wash like rain on the weekend.

“It rained Saturday, Sunday, Monday and Tuesday,” the colorful Frattaroli said recently. “I had to get a rubber stapler because I’m going to throw the damn thing through the television.”

Move the calendar ahead a few months and warm, dry weather kills business in the winter, while moderate snow brings in packs of customers to wash the salt off their vehicles.

“They come out of the woodwork,” Frattaroli said. “Give me two inches every 10 days and I’ll be happier than a pig in you-know-what.”

A New Technology Helps with an Old Problem

Car wash operators across the country can relate to Frattaroli’s frustrations. So much of their business hinges on Mother Nature and you can’t control the weather. But new technology has provided a better way to prepare for the age-old problem.

As more businesses rely on analytics and data to better inform decision making, predictive weather analytics is gaining a foothold. The field uses historical data on weather and customer traffic and weather forecasts to help companies plan for shipping and delivery, utilities, staffing, customer behavior and other key areas of business.

Retail, agriculture, golf, logistics, transportation, shipping and construction are among the industries that increasingly utilize predictive weather analytics. Property insurers also use it to better assess risk and plan for severe weather events.

Bethlehem, Penn.-based Weather Trends 360 entered the business in 2002, long before big data became a business buzzword. The company’s range of clients – a mix that includes Coca Cola, Walmart, Walgreens, Target, Microsoft, J.P. Morgan, Anheuser Busch and Sonic Drive In – reveals how major corporations are working to get ahead of the weather.

Company CEO and co-founder Bill Kirk said small businesses such as car washes can also prepare better in advance if they know the forecast calls for the driest, warmest March in a decade and a boost in sales or the heaviest snowfall in years, which keeps potential customers off the roads and out of the car washes.

“The tricky part is it’s one thing to analyze, it’s another thing to predict,” Kirk said. “It does you no good to know a really hot, dry winter is no good for a northeast car wash if you cannot forecast it.”

Kirk gave an example. A few months after his team of meteorologists and mathematicians used a detailed climate cycle model to accurately predict the second hottest winter in history – also a dry one – he met a car wash owner.

“The owner said, ‘I wish I had met you six months ago,’” Kirk said. “‘If you had told me that six months ago, I wouldn’t be stuck with half a million dollars of car wash chemicals. I would rather have the half a million dollars in my bank account than have it sitting in car wash chemicals.’”

For Frattaroli, the weather has a significant impact on staffing levels and schedules.

“The biggest bugaboo is maintaining a crew and trying to get them work,” he said. “You can have them sweep up and do busy work but that can only go on so long if there’s no income. It’s difficult maintaining personnel when the weather has been like it’s been this year.”

Because of slow business from the historically wet summer, Frattaroli reduced his staff to four full-time employees. When a week of clear skies arrived and the customers flocked to the car wash, his staff all worked overtime, pushing up personnel costs.

Beyond sales, staffing and purchasing, the ability to plan ahead for the weather helps budget for utilities. Kirk refers to “the power of one degree,” or how every degree colder increases the heating bill by five percent.

Predictive weather analytics is effective because it mixes an accurate long-term forecast- Weather Trends 360, for example, goes up to a year out- with business knowledge of an industry and insight into customer behavior.

So much of [car wash] business hinges on Mother Nature and you can’t control the weather. But new technology has provided a better way to prepare for the age-old problem.

From that customer behavior perspective, Kirk said weather’s impact on a car wash’s business may also vary based on the income-level of the neighborhood where it is located. “For lower-income consumers, a cold winter may not have them driving to the car wash to get the salt off their vehicles,” Kirk said. “They’re grappling with higher heating bills and have less disposable income. So much depends on geography.”

A Look at the Winter Forecast

What will winter 2018 hold?

The National Oceanic and Atmospheric Administration says it will be warmer than usual for much of the United States. The NOAA forecast for December through February called for above-average temperatures across the northern and western states, Alaska and Hawaii.

A soggy South and dry North may also be in store. NOAA says there is a 70 to 75 percent chance a weak El Nino system will form, bringing wet conditions to the South and Mid-Atlantic and warmer, drier conditions to areas of the North.

Alaska, the Pacific Northwest, and the Northern Plains are the areas with the greatest likelihood of above-average temperatures, the NOAA said. The Southeast, Tennessee Valley, Ohio Valley and Mid-Atlantic were all forecast to have equal chances of below-average, near-average or above-average temperatures. The forecast did not favor below-average temperatures for any area of the country.

Northern Florida and southern Georgia had the greatest chance for above-average precipitation, while drier-than-usual weather was forecast in parts of the northern Rockies and Northern Plains, the Great Lakes region and the northern Ohio Valley.

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