Oracle Retail Blog
By: Giuseppe Rapisarda, Oracle Retail Supply Chain Solution & Strategy Director
Did you know roughly 5% of a retailer’s total sales are driven by fluctuations in the weather? We are all affected by the weather. Every single day of the year, the weather has a material impact on us, especially in the winter. It affects our mood and it influences how we act. As Milli Vanilli once lip synched, blame it on the rain.
As seasons change, shopper behaviours change and retailers must tap into weather-driven demand patterns to help inform inventory decisions and demand forecasting to predict what shoppers want, where they want it, and when.
With the right tools and retail solutions, retailers can easily understand, interpret, and incorporate weather-driven demand as an integral part of business strategy and inventory planning. I teamed up with Planalytics, a global leader in business weather intelligence, to discuss how incorporating weather-driven demand can help improve forecast accuracy, increase inventory availability, and reduce out-of-stocks.
Weather data is not weather-driven demand
The fundamental truth is that weather data is not the same as weather-driven demand. While many companies have tried to integrate weather data into their demand forecasting operations, it hasn’t been effective. Why? Weather data is subjective, emotional, and complex, and in many cases, it requires expert translation. Unlike weather-driven demand, weather data doesn’t quantify weather’s impact and it can be challenging to scale, making it less effective.
Weather-driven demand, on the other hand, is quantifiable. At its core, weather-driven demand measures the impact of weather on consumer behaviour. It is undeniable that weather impacts what we do, and ultimately can affect consumer demand and buying behaviour. Not only can weather-driven demand help “de-emotionalize” business performance actions, but it is also easier to scale and understand.
Demand reigns supreme
Weather-driven demand data can easily be turned into business value when coupled with Oracle Retail’s solutions. Here’s how. Combine it with a modern attribute-based demand decomposition approach to drive a radical change to the predictive model using next-generation demand forecasting.
The key principle of demand decomposition is straightforward – look for patterns using the actual data of a single SKU at a single location and use the information of similar SKUs and similar locations grouped by attributes. The rate of sales, promotion and price effects, and seasonality all impact consumer demand, and each component is calculated at a different level of attribute aggregation. The embedded machine learning (ML) algorithms select the best attributes and exchange information to produce a statistically stable prediction that is seamlessly merged into the final forecast.
Replenishment is key
A key aspect of weather-driven demand shows up in the replenishment process. Leveraging weather information, we can automatically adopt placement, display, and replenishment parameters, further increasing the value of having a more precise forecast. The number of parameters needed to drive a replenishment system is enormous, and they are continually changing due to events such as the weather and more recently, the pandemic. With Oracle Retail Demand Forecasting, companies can define the strategies and write rules that manage each business scenario. The system will enforce the rules and automatically set the parameter values.
Research shows that 47% of respondents list out-of-stock merchandise at the top of their list for a bad shopping experience and 63% are unwilling to wait for an item to be back in stock before trying another brand. A lack of inventory is the fastest way for retailers to lose loyal customers, according to Oracle’s consumer survey.
By incorporating a weather-driven demand strategy into a business model, along with a modern demand forecasting solution, retailers can better manage inventory levels. When the right quantities of products are in the right locations at the right time consumers have a positive brand experience, sales increase, and a retailer’s overall service is improved.
Because at the end of the day, you want to say “girl, you know it’s true.”