IBM’s Latest AI-Powered Solution Allows Retailers to Harness Weather Changes to Drive Performance
IBM and its subsidiary The Weather Company announced IBM Weather Signals, an AI-based tool to help companies predict how fluctuations in weather will impact business performance, even months in advance. With this insight, businesses can proactively adjust supply chains to ensure accurate inventory, staffing and promotional activities aligned with anticipated changes in local weather conditions.
IBM Weather Signals uses Watson AI to merge weather data with a company’s operational data to create a model that predicts how anticipated seasonal weather conditions, or even minor fluctuations in temperature, wind chill or humidity, are expected to impact business performance, right down to sales of individual product categories at specific locations.
Integrating this insight into supply chains, companies can then redirect inventory to meet anticipated changes in demand ― for example a fashion retailer can time the introduction of seasonal clothing lines to the start of the seasonal weather or a tourist attraction can anticipate how humidity might impact visitors’ willingness to stand in line and adjust staffing or pricing. These insights increase productivity and reduce waste to potentially add millions to the bottom line.
To help companies better integrate weather into their business planning process, IBM Weather Signals will be integrated with popular analytics platforms like Tableau. This provides interactive capabilities to model the correlation between weather and business performance within the context of overall business forecast planning, and within an intuitive dashboard environment, without having to migrate data to a new platform.
IBM Weather Signals has applications across a broad range of industries and is particularly relevant to industries that are sensitive to changes in daily or seasonal weather conditions such as retail, consumer packaged goods, services, hospitality, entertainment and travel, and transportation.