With Like-for-Like Weather Rare, Like-for-Like Surprises Are All Too Common
Quantifying sales impacts and planning from a weather-adjusted perspective puts retailers in a better position to manage the year-to-year shifts in consumer demand.
The weather was cited regularly in recent weeks as companies reported on and discussed their trading results over the spring period. And there was certainly cause for high street shops and others to point to less favourable conditions hurting sales, particularly in May and June when temperatures dropped below normal and, very importantly from a comping standpoint, well below the record readings from the prior year.
Planalytics’ Weather-Driven Demand (WDD) metrics clearly highlight how the changes in weather challenged many retailers this past spring. WDD values isolate and quantify the impact that the weather alone has on demand for specific products or, at higher levels, overall footfall or transactions.
In a situation where a half degree change in the UK’s monthly mean temperature is very significant, May 2019 was 1.4○C lower than May 2018. WDD impacts for the UK overall compared LY included: Garden Furniture (-16%), Grass Seed (-11%), Skirts (-10%), Sandals (-5%), and Bottled Water (-7%).
In June 2019 the UK’s monthly mean temperature was 2.2○C lower than June 2018, with significantly more rainfall as well. WDD impacts for the UK overall compared LY included: Shorts (-21%), BBQs & Accessories (-20%), Swimwear (-14%), Salads (-6%), and Ice Cream (-22%).
ADDRESSING THE WEATHER BLINDSPOT IN PLANNING
In retrospect, the negative impacts listed above should have been expected. The problem for many was that sales and merchandise plans did not adequately adjust for like-for-like headwinds on the horizon. After all, May 2018 was the warmest ever for the UK and June 2018 was the second warmest on record. Replicating these extremely warm temperatures and the very strong sales most seasonal categories saw as a result should not have been expected.
Conversely, the early part of spring was the only opportunity retailers had to capture comp gains. March warmer than normal and 3.7○C warmer than the prior year boosting overall clothing store transactions (+4% WDD v LY) with many seasonal apparel products seeing +5 to +15% and many lawn and garden products enjoying +20 to +50% WDD gains compared to LY.
This past spring was just the latest example of what has always been and always will be a challenge for retailers – the inherent variability of weather. Mother Nature simply does not stick to a set schedule. However, by default, many business plans and sales forecasts are not accounting for this reality. The positive or negative influence that weather had on sales is embedded in the prior year’s results which often serve as (or heavily influence) the baseline used to plan the next season or year. Unless these weather impacts are measured and removed, retailers adding significant error into their plans.
Detailed Weather-Driven Demand calculations (typically by product category, market/store, and week) improve planning accuracy when they are used to “deweatherise” or correct for the weather volatility that is “baked” into historical sales. Planning from a cleansed, weather-neutral baseline improves accuracy overall and often by 20% or more for specific products and times of year.
Looking back to the spring period one can see how a more accurate, weather-adjusted plan would have enabled a retailer to better manage internal and external expectations, identified how to best capitalise on more limited opportunities, and avoid the negative financial impacts that would arise from an overly optimistic plan. Broadly speaking, some of the benefits include:
• Increased early season sales by having inventory available when demand levels were projected to be higher than the year-ago period.
• Reduction in inventory costs, markdowns, or wastage by not over-planning later in the season.
• Optimising areas such as merchandise allocation/replenishment, pricing, promotions, staffing, and digital marketing by not “chasing last year’s weather” with a plan that assumes the weather and consumer reactions to it will be the same from one year to the next.
As the spring period exemplified, like-for-like weather is the exception rather than the norm. The surprises will continue for retailers that are not using weather analytics to illuminate (and precisely enumerate) how the landscape of weather-driven opportunities and risks are likely to shift going forward. Here are some weather impacts for retailers to consider during the final two months of the year.
From a year-over-year weather perspective, November and December could support strong comp performance as more favourable weather will support demand for winter items. Last year, both months landed in the top ten warmest over the past half century with December being nearly 2○C warmer than normal. As a result, sales of coats, knitwear, and other winter clothing suffered as well as hot foods and beverages and other seasonal categories.
WDD projections for November 2019 (versus the prior year) include Hats, Gloves & Scarves (+8%) and Heaters (+14%). WDD projections for December 2019 (versus the prior year) include Soup (+3%) and Winter Coats (+10%).
Weather-based sales volatility will never disappear. Retailers that can “put a number” on the impacts and then integrate these analytics into their planning processes can put themselves in a better position to effectively manage the sales swings, serve their customers, and improve performance and profitability.