Retail forward: Turning “adapting to cope” into “adapting to win”
2020 required retailers to prioritize demand over profitability. To successfully move forward, retailers need to find a way back to efficiency and turn “coping” into “winning."
2020 required retailers to prioritize demand over profitability. To successfully move forward, retailers need to find a way back to efficiency and turn “coping” into “winning."
The BWS category poses several challenges for retailers, including promotional planning, capacity management, and omnichannel replenishment, leading to poor results if not planned for carefully.
In this webinar, we discuss what DIY supply chain challenges HELLWEG has faced and how they have managed to optimize stock levels while reducing inventory and freeing up capital.
In this Customer voice blog, Antti Kurhela, Supply Chain Manager at Wihuri, talks about how this foodservice operator was able to rapidly adjust to changing conditions while still reducing food waste in 2020.
In this 12-minute video, Johan Hoover from Big Lots, explains how RELEX’s demand and supply planning has enabled them to become more efficient and adaptive in a highly turbulent retail market.
An effective S&OE process ensures retailers meet their sales plans without suffering from poor product availability or costly operational firefighting.
Grocery retailers who are implementing an omnichannel strategy should use a transparent supply chain management solution that provides trustworthy, automated forecasts.
Weather-based forecasting is challenging, but those retailers who can accurately forecast when the weather will affect sales can capitalize on increased sales opportunities and prevent excess stock and costly spoilage.
Our expert Josh Mann explains what machine learning is, what kind of challenges it solves, and why many leading retailers are starting their transition toward machine learning-based demand forecasting.
It is nearly impossible to fully automate processes for exceptional demand periods like those caused by hurricanes. Instead, planners must take a hands-on, localized approach to hurricane management.
In this webinar, our our data scientists and retail planning experts explain what machine learning is, what kind of challenges it solves, and why so many retailers today are transitioning toward machine learning-based demand forecasting.
During the coronavirus crisis many businesses saw an increase in online ordering. This trend won't go away once the crisis has passed - people are discovering the convenience of online ordering.
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.
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.
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.