Using Historical Weather Data To Lock In A Profitable Winter Season

As snow and ice professionals gear up to tackle another winter season, one of the biggest challenges they face is how to price their snow removal contracts. Weather can be one of the greatest wild cards for snow removal companies looking to make a profit each winter. However, understanding and analyzing your job location and its historical weather data may be one of the greatest assets in determining relationships between contract pricing and overall risk versus reward. So the big question becomes which source weather data is right for your company? That answer is not always easy and depends on various factors like the geographic region, the client’s needs and whether you are pricing the contract per inch, per push, time and materials or seasonal.

Inside this story, I have provided a thorough analysis of the different types of useful winter statistics for pricing out snow removal contracts (averages, extremes, median snowfall and event count). Diversifying your portfolio as you would in the stock market is one step to success, but understanding how to incorporate an extensive network of historical weather data will also allow you to professionally educate your clients and prospective clients during the process.

Boston’s rolling 30-year average is significantly lower than its average from recent years. The more long-term data you analyze, the more realistic your predictions will be for the upcoming year. Photo: Kevin Hopler, WeatherWorks LLC

Know Your Location

The first step in determining your contract price point involves comprehensive research of your actual proposed work location. The nearest airport providing weather data may in fact be very reliable but it may not always be representative for your exact “work” location once you factor in distance, topography, altitude and seasonal extremes. One example illustrating this case was during the 2013-14 winter season in the Detroit metro area. The distance between Detroit Metro Airport (KDTW) and Dearborn, Michigan was only 11 miles but represented a seasonal snowfall difference of 32.3 inches. Other factors like rising altitude over a short distance can often yield a 10-percent to 15-percent difference in 5-year and 10-year average snowfall.

Philadelphia’s rolling 30-year average is 15 inches less than its 5-year average. Photo: Kevin Hopler, WeatherWorks LLC

Average Snowfall

Some of the most common requests during the contract preparation period include 5-, 10- and 30-year averages for a particular location or zip code. Although a 5-year average will provide insight into the latest trends of snowfall data at a particular location, relying solely on this statistic can appear erratic and prove detrimental to a snow removal contract. A 10-year average, one of the more popular requests, will still contain some fluctuation but at least provides you with more data points to make a more educated decision. Thirty-year averages are also very common and often less influenced by recent trends but also typically have a lower bias than a 5- or 10-year average. There is no wrong answer to which average is best for your company, but one solution would be to use a moving average shown in the graphic above for the greater Philadelphia area. Keep in mind, if you were to use the 5-year moving average in 2013-14, you would be utilizing a total nearly 15 inches higher than the rolling 30-year average.

Median Snowfall

Only a small percentage of companies rely on this simple metric. The median snowfall is simply the middle point in the data set. This statistic can be very useful to snow and ice professionals in the planning stage of developing a new geographic market, especially when the average snowfall at a particular location is skewed by extreme snowfall seasons on either side of the spectrum. Median snowfall may offer a more realistic characterization of what is normal at locations that are often inundated with numerous smaller events in addition to some seasons with a few historic, large snowfall events.

The monthly seasonal event count can help you determine your number of plow events versus deicing events. Photo: Kevin Hopler, WeatherWorks LLC

Event Count Statistics

Finally, determine the type, frequency and amount of snow at a given location over a number of years (10 years is most common). This involves obtaining the highest resolution data possible and breaking down each season into your proposed billing increments so that you have an idea of frequency of plow versus deicer events and the risk for extreme snowfall events. Is the location susceptible to sleet or ice storms? If so, you may approach the bid differently and account for time and material.

So, before you jump into another season or new geographic region, make sure that your company is equipped with the most reliable and accurate weather data for your proposed work location. Avoid the pitfalls of relying on historical data too far from your job site and use more than just the nearest airport. Most meteorological consulting firms can prepare a detailed, site-specific snow climatology to assist with your preseason bid preparation process. The snow climatology report should then be used to test your pricing model. The outcome should provide the confidence needed to service your client in the most efficient manner and maximize your potential for a profitable snow season.

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