Demand Forecasting for the 21st Century Consumer
By Tom O'Reilly / November 2016Insights
Retailers must put aside antiquated mass marketing practices. Relying on single assortment, standard pricing and a single “average location” forecast will not satisfy the 21st century consumer.
With so many factors impacting shopping behavior and increased pressure on profit margins, retailers must focus on better understanding the demand for merchandise throughout the buyer’s journey. Forecasting predicts and meets consumer demands while controlling pricing and inventory. This is critical because warehousing excess inventory adds overhead costs while under-stocking leads to loss in revenue.
Anticipating future consumer actions can be done by evaluating past revenue, deciphering sales patterns and analyzing buying behavior. The objective is to better manage order quantities, stock and shipment allocation at the store and SKU levels. By improving demand forecasting, retailers will experience fewer stock-outs, improved margins and more solid overall business results.
Retailers Use of Demand Forecasting Technology
Experts say many retailers still use manual ordering and even resort to relying on their “gut” or intuition when replenishing stock and preparing for promotions.
According to Teradata, “most retailers continue to rely on last year’s shipment-withdrawal data or rolled up t-log data in tools like Excel to help plan their activities for distribution and buying.”
A recent Progressive Grocer article describes the business context for demand forecasting, stating the technology should go beyond inventory replenishment to include planning and collaborative elements. Team members across retail organizations – from category managers, buyers, store managers and vendors – should be able to reconcile their forecasts using the same system.
“The technology should be flexible enough to provide insight to the forecast and the ability to manage the impact of changes made by any stakeholder in the system,” says Alan Lipson, global retail/CPG industry marketing manager for SAS. “Ideally, the forecasting technology would be linked to inventory optimization technology so the retailer and the manufacturer can work together to make sure consumers get their favorite holiday menus on the table without any hiccups.”
The good news is that retailers can begin integrating demand forecasting technology with a modest budget and team. A small staff with detailed data acquisition practices, in addition to some industry-leading tools can reduce stock-outs, improve sell-through, inventory turns and customer satisfaction.
Here are some of the ways retailers are using demand forecasting:
Promotion event-planning: A more granular demand forecast of promotion events at store-item week and day level. This process connects future store needs to the distribution center, while also estimating customer needs at store level to improve automation, reducing out-of-stocks and costly overstocks.
Buying function: Improve the supply chain by aligning the demand and inventory forecast from the lowest level of item-store days and weeks over a variety of future time horizons.
Computer-assisted automated ordering: Granular forecasts developed at item-location-day to automate the order calculation based on expected consumer demand. This reduces manual effort and enhances order quality.
Machine Learning Technology
Machine learning technology is modernizing retail demand forecasting by linking attributes such as assortment, space, price and fulfillment for greater accuracy. Retailers can align merchandise financial plans and connect location with assortment, category, space and price plans.
dunnhumby’s Retail Heartbeat Availability Suite combines real-time, fine-grain prediction engine with machine learning techniques to create demand forecasts for improved inventory planning. The ultimate goal is to speed the decision making process and spotlight growth opportunities, while mitigating costly risks for retailers.
With new technologies becoming more easily available and affordable, retailers can integrate demand forecasting in their planning cycles to achieve business objectives. The latest advancements will free up retailers to better focus on shoppers and improving the customer journey for the 21st century consumer.