Is it possible to accurately predict future sales based on sales history? Past performance is just a single data point in all of the data being constantly collected, which on its own is not enough. In the case of a new product, retailers can’t rely on past performance to predict the future.
Increasing forecasting data accuracy is necessary to ensure retailers have accurate insight into consumer buying habits and ability to match that with bottom line results. Incorporating machine-learning technology allows retailers to recognize trends that otherwise escape the human eye.
Smart planning starts with your data. Increasing accuracy of data and leveraging a forecast and planning solution designed for retail can improve buying, promotion activity, inventory management and sales.
With a forecast and planning solution, retailers can analyze buying patterns of consumers and make more educated decisions in target group preferences. The system will also aid in determining different product lifecycles, and what factors play into these cycles. For example, is competition driving sales? Will the introduction of a new product cannibalize sales of existing merchandise? Statistical forecasting techniques can determine what factors influence sales, and what items will move at what pace, be it a seasonal or naturally slow or fast moving item. When you are buying the right products to fit customer needs, inventory will move faster and stock management will be minimized at the store.
Configure to your needs
Because retailers sell different items in varying outlets, every business has differing needs. A department store and a boutique have different customer preferences, selling patterns, and sales data. While it may be obvious why a forecasting and planning solution is necessary for big box stores, small retailers can also benefit. Unlike larger retailers, small retailers do not have much room for error, making it all the more important to get the right blend of colors, sizes and SKUs the first time if they want to compete in the market.
Improve business processes
When you are planning, ordering, and assorting stock smarter, it shows. A forecasting and planning solution drives smarter strategy and innovation in all processes of the business. A machine learning solution allows retailers to take charge of their inventory and align it with sales and future planning. This makes it possible to meet target goals without excessive overstock that often result in clearance markdowns.
It’s time for retailers to add sophistication to planning and forecasting. With increased competition, changing consumer demands and buying habits, as well as seasonal and other factors influencing retail results, getting inventory right is critical. Retailers who offer merchandise in the right quantity, blend of colors, styling details, and sizes at the right time and price will be able to plan ahead for success.
Andy Cariveau is vice president of Retail at Avaap, where he is responsible for enhancing the customer experience with Infor software including tools that can help you create a modern approach to retail forecasting and item planning. Andy will be at the National Retail Federation big show in booth #2854 January 16-17.