Store closures and demand decreases: Learning from the past to plan for the future
Learnings from the past crises are applied to help retailers facing store closures and demand decreases plan for the future after the pandemic.
Learnings from the past crises are applied to help retailers facing store closures and demand decreases plan for the future after the pandemic.
Our Italian country director shares his insights on how Italian customers faced the Coronavirus crisis and how RELEX helped them along the way.
While a sudden growth in online sales presents an opportunity to recoup lost in-store sales, it also poses a significant operational and logistical challenge.
RELEX’s best practices for managing demand for essential and nonessential items within a single environment during these unusual demand patterns.
Winsight Grocery Buisness interviewed our co-founder Michael about how a lean supply chain can recover from sudden demand increases.
Retailers must maintain transparent, proactive relationships with their suppliers if they hope to maintain availability during coronavirus demand increases.
No system, no matter how advanced, can accurately automate calculations when there’s no historical precedent on which to model forecasting.
Fresh items attract customers, yet grocers lose over 1,5 percent of revenue to food waste. Waste reduction is not just about sustainability, but it also contributes to a healthier balance sheet.
This study outlines how our four customers have led the charge toward environmentally responsible business practices while significantly improving both operations and cost-effectiveness.
Ultra-fresh products like fruits and vegetables have some unique challenges, but they also comprise one of the largest revenue streams and opportunity centers.
Stochastic planning has been presented as a result for tackling uncertainty in supply chains. Our whitepaper explains what it is and when and how to use it.
Retail is impacted by many factors, such as weather and cannibalization, that can be taken into account with the help of machine learning.
This white paper shows how accurately forecasting for short lifecycle products is possible through intelligent statistical modeling that uses data from previous product introductions.
16 % of large US grocery retailers still base their distribution center forecasts on historical data on outbound deliveries from these distribution centers. This is akin to driving a car while looking into the rearview mirror.
Accurate forecasting is at the core of increased operational efficiency as it is key to accurately match resources, such as stock and personnel, with demand.
During my almost seven years working with space planning, I’ve faced almost every question there is to ask around the topic. One, however, seems to come up constantly “Can we use forecast data when making the planograms?”
Predicting weather is not easy and rapid changes in weather can cause consumers to suddenly shop or cease to shop for specific products, which can quickly become costly for a retailer.
Sales promotion of one product impacts not only the sales of that product, but also products not in promotion.
“What would you consider a good level of forecast accuracy in our business?” is probably the single most frequent question we get from customers, consultants and other business experts alike.
This complete guide explains the facets of forecasting and why forecast accuracy is a good servant but a poor master.
Over the years almost every single retail initiative has had forecasting and replenishment at its core.
People are fickle, not wholly rational and make different decisions at different times. However, people are predictable in most of their buying decisions.
How does one create meaningful forecasts for new products when there is no sales history at all?
Demand forecasting for promotions is a major challenge for retailers, not least because of the impact it has on driving sales.