At RELEX we are in a unique position to get the most out of machine learning in forecasting retail demand. And there are three reasons for this.
In this whitepaper we’ll take a look at the different forecasting approaches that can be used to achieve an unprecedented degree of accuracy in diverse situations.
This whitepaper compares the costs of procurement in relation to long and short delivery times, and presents an opportunity.
In this whitepaper we take a look at how to Christmas and draw lessons for year-round seasonal management.
This article takes a look at the impacts weather can have on demand and how to take different scenarios into account.
As sales fluctuate significantly day to day, precision with fresh food is only possible through accurate daily forecasting and daily replenishment.
In the food sector the longest holiday forecast period is that for Christmas and New Year, where successive holidays make maintaining supply chain efficiency quite challenging.
Supply chain integration has been talked about for so long, and has had so much promised on its behalf that, frankly, it’s easy to tune out.
This article explains how data systems affect the execution of S&OP processes.
To borrow a phrase from the famous baseball player Yogi Berra “It’s like déjà vu all over again.”
There are plenty of companies who have managed to turn seasonality into an opportunity.
Less work, better forecasts: More efficient and accurate demand forecasting with quantitative forecasting tools!
Doing demand forecasting with quantitative tools can make your operations more efficient.
In grocery retail, approximately 3.9% of revenue is lost due to stock-outs and it is estimated that the situation is even worse in specialty retail.
This article focuses on stock replenishment from the perspective of department store operations.
Forecasting is not rocket science, and a wide range of effective and easy-to-use tools are available to support it.
In many cases, it’s possible to increase the efficiency of spare parts management quite dramatically.