CPG companies need to leverage retailer data in demand planning and collaborate effectively with their retail partners to attain high forecast accuracy and meet demand.
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.
The Vitamin Shoppe improved their inventory optimization and got more accurate forecasting after implementing RELEX.
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.
The Swiss online-only supermarket saw significant improvements in their forecast accuracy and promotional campaign outcomes.
RELEX features enabled Rossmann to increase efficiency, cut back on in-store shelving work, and relieve some of the pressure on logistics while reducing inventory and out-of-stocks.
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.
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.
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.
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.
Norway’s largest discount variety retailer achieved over 17% cut in DC inventory in just 18 weeks.
Finland’s leading bookseller uses RELEX's Markdown solution to optimize stock levels and largely automate the markdown process.
By linking shift planning to demand forecasts and the incoming delivery schedule, the Swedish grocer has been able to reduce personnel costs by 6-8 %.
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.
RELEX has played a key role in supporting the evolution of Arena’s supply chain processes towards a more holistic control of its entire customer-fulfilment chain.