
Case study: One Stop
With RELEX's machine learning forecast, One Stop has enhanced its daily forecast despite the complex weather-driven demands and increased in-store availability without spoilage corresponding.
With RELEX's machine learning forecast, One Stop has enhanced its daily forecast despite the complex weather-driven demands and increased in-store availability without spoilage corresponding.
Atria significantly improved their forecast accuracy and stability after implementing RELEX machine learning-based forecasting capabilities.
This guide demonstrates best practices for building a business case for supply chain technology investment and puts perspective on primary considerations when working with ROI calculations.
DOUGLAS, the leading beauty platform in Europe, has significantly improved its forecast accuracy and product availability with RELEX's AI-driven forecasting and replenishment solutions.
By investing in modern supply chain planning and optimization technology, grocery retailers can improve their profitability and their sustainability at the same time.
In this video, our expert Josh Mann gives a view into the RELEX product offering and explains how we help retailers plan better, sell more, and waste less.
It is more important than ever that retailers collect data from all channels and use it to manage the flow of goods through the supply chain to the point of customer interaction.
By relying on AI and machine learning to create highly accurate forecasts, grocery retailers can successfully reduce food waste and spoilage.
Incorporating AI into demand forecasting and inventory optimization can improve product availability, reduce waste, smooth the flow of goods and improve operational efficiency in distribution and in stores.
By now, everyone knows that “Silos” is the new bad word in business as it creates critical weaknesses. Find out how to break out from silos to empower greater transparency, collaboration, and information sharing.
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.
Welcome to RELEX Labs, our research engine at the core of our company working closely with our customers to develop the future of retail optimization.
A leading Finnish retailer piloted RELEX’s AI-based main delivery day optimization functionality to take replenishment to the next level.
Running a grocery business has changed fundamentally: The days of working on intuition have passed, and the days of data analytics and frictionless retail are here.
Retail is impacted by many factors, such as weather and cannibalization, that can be taken into account with the help of machine learning.
With AI hype going on, many forget that AI doesn't matter, but the results do. We now use pragmatic AI when describing how we use data for better decisions.
Most retailers are rich in data, but access to data does not automatically enable retailers to make better decisions faster. This is where decision science steps in.
Retailers are no longer interested in major system replacements. Instead, there's a trend toward implementing in parts rather than as a whole.
Choosing a supply chain planning system isn’t easy. That's why we've listed some things to consider if you’re going to transform your supply chain planning.
The industry has been talking about RFID for 20 years, but it still hasn’t come into common use or delivered significant value to retailers.
Supply chain planning is particularly challenging for mid-market retailers encountering all the same complexities as big retailers.
With spending on IT coming under more pressure, not necessarily because of reduction in budgets but more from the increasing number of projects a CTO is faced with, where should a company focus its attention?
Big Data isn’t a magic bullet but there are some impressive gains to be made in traditional operations, such as supply chain management.