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• The weather influences consumer buying behavior everyday – and it never stops changing; no other external variable shifts demand trends as immediately, frequently, and meaningfully.
• Retailers improve forecast accuracy when data-driven weather analytics are incorporated into planning, allocation, and replenishment processes and better align store-level inventories with consumer demand.
• Misaligned inventories lead to higher costs and reduced profits; inventory costs, markdowns, and shrink will be higher for retailers that ignore the impacts of weather-driven sales volatility.
Retailers have long looked at localization as a powerful way to improved conversions, total receipts, and customer satisfaction or loyalty. Localizing assortments and having the right amount of inventory available in stores when customers want to buy is a must if businesses want to realize localization’s promise and financial benefits.
Unfortunately, localization remains elusive for most retailers for a variety of reasons. Often, it is a lack of capabilities in a retailer’s existing software solutions. Or, finding a workable way to incorporate the “voice of the store” into processes has proven to be very difficult. And possibly the biggest hurdle to success has been the lack of access to critical market-level analytics.
On this final point, retailers may not realize that one very important piece of market-level intelligence is now accessible and applying it to the business has never been easier. The emergence of weather analytics that are precise, scalable, and presented in a business context (product volumes, not temperatures) is allowing retailers to optimize local inventories and improve both sales and margins.
What’s more “local” than the weather? When it comes to external variables, nothing is more consistently and directly impactful on sales than the weather. Integrating weather-driven demand metrics into core merchandising processes is not a long, drawn-out project and, once implemented, retailers can start capturing benefits in a matter of weeks.
By applying weather analytics across the business, retailers can add up to a 2% to total topline sales. Better availability leads to more sales and profit. But weather analytics also help on the expense side of the ledger. Inventory costs, markdowns and shrink are three primary examples.
Inventory costs: First off, retailers gain a one-time boost to their balance sheets by incorporating weather analytics. The benefit can be measured by looking at working capital improvement as a percent of cash and cash equivalents. For grocery, a 3-5% increase in working capital relative to cash is a common range. For DIY/home improvement and general merchandise chains, gains of 20% or more can often be achieved. Through a process called “deweatherization” retailers correct for the weather noise in historical sales and generate first-year savings as a result of initial inventory realignment or clean-up. This initial inventory reduction produces working capital by reducing the total inventory in the retailer’s system via improved forecast accuracy and optimized safety stocks.
Going forward, the improved planning accuracy produces annual costs savings by reducing excess stocks and inventory carrying costs. These savings enhance margins, with many retailers seeing 20 to 70 basis points in incremental profit as a result.
Markdowns: Clothing chains, sporting goods retailers, department stores, home centers, and other retailers can also utilize weather analytics can help limit margin-eroding markdowns.
There are opportunities to minimize markdowns with weather analytics during pre-season planning and allocation processes, as well as, during the selling season. First, when retailers plan the next season or year they must correct the weather bias or variability embedded in past sales performance. By deweatherizing last year’s sales a retailer has visibility into when favorable weather conditions exaggerated sales or unfavorable conditions deflated sales. In situations where prior sales are inflated and the positive weather environment doesn’t repeat the next year, retailers often end up with excess inventories that need to be marked down certain locations.
In-season, there is another opportunity to proactively manage markdowns when a retailer considers expected weather impacts to either delay markdowns for a period of time or reduce the depth of markdowns (e.g. 30% off instead of 50% off).
Perishable shrink: Given the amount of short shelf life perishable products on their shelves, food retailers face the challenge of balancing availability with shrink/waste costs. Erring too far on the side of on-shelf availability may ensure high service levels but it can significantly impact profit. On average, grocers lose about 5% of total sales in fresh categories due to products becoming unsaleable due to quality or expiration dates.
Using store-level, weather-informed replenishment, grocers typically decrease waste by 10-35% in fresh categories from produce to fresh meats. The large improvements are achievable since most replenishment processes and systems rely heavily on historical trends and/or the most recent sales volumes. Leveraging weather insights that adjust replenishment for the weather-based demand changes expected to happen in the coming days or week, grocers can do a better job reducing inventories where demand will be decreasing from recent peaks without risking lost sales due to stockouts.
The above inventory-related examples illustrate how a key market-level factor called the weather offers a proven way to tap into the potential of “localization” and the resulting financial benefits.
Other areas where weather analytics help retailers with expenses include labor (identify where hours can be trimmed), expedited freight/storage/handling costs (avoid costs of moving product), and digital advertising (don’t allocate spend where unfavorable weather makes conversions unlikely).