We’ve been using Lokad daily for over 2 years to calculate our sales prices. It’s a tailored solution, especially given that our combined catalogs take in to account the 20 countries where we operate. It has really helped us to take our ability to generate value via our pricing to a whole new level. As well as being very powerful, Lokad’s solution gives us speed and reactivity, two elements that have become essential for any e- commerce.
Now 70% of our turnover and all the growth is through ecommerce. I started to think about a purchase suggestion system to enhance/automate our purchase flows. I was planning to build it myself but realized that these guys made exactly what I was looking for - but way better! we use the service on a daily basis to optimize and make purchase decisions. Lokad is not replacing the purchase managers but enhances the capacity and provides most valuable insights to make their work efficient and accurate.
Lokad brings a new tool to the table, one that is both powerful and innovative. But on top of that, Lokad has shared with Air France Industries its expertise in inventory optimization and Supply Chain management, thus bringing not only a complimentary IT solution but also a real consulting expertise, which our teams can rely on.
If you can't measure it, you can't optimize it.
Your Supply Chain performance in 12 questions
The Quantitative Supply Chain represents a novel and disruptive perspective on the optimization of supply chains. It can be seen as a refoundation of many supply chain practices, in particular regarding inventory forecasting, and has been built to make the most of the latest statistical approaches and vast computing resources that are available nowadays.
This perspective has emerged at Lokad, a software company founded by Joannes Vermorel. Lokad mixes data analysis with machine learning, cloud computing and supply chain expertise in order to optimize supply chains in a rational and quantitative way, so that the business and financial impacts of every decision are properly quantified. His experience at Lokad has given Joannes Vermorel the opportunity to study and analyze the methods, challenges and performances of dozens of companies all over the world.
This book is intended for supply chain executives and managers who want their supply chains to perform more, faster and with less resources. It caters to those who, ultimately, want to be more in control of their supply chain, with a more precise idea of what their decisions entail. This book provides a comprehensive introduction to the insights, methodologies and tools that have been gathered under the Quantitative Supply Chain umbrella.
The first part of this book covers the general concepts associated with the Quantitative Supply Chain. It outlines how this perspective differs from the classic supply chain perspective, and sheds lights on the core insights. The second part of this book provides hands-on materials to implement a Quantitative Supply Chain initiative. It leverages Lokad as a programmatic platform tailored for Quantitative Supply Chain purposes.
A forecasting competition based on Walmart store data ended June 2020. Lokad ranked 6th out of 909 teams. In this episode, we have a closer look at this unusual sporting event, and what it takes to win such a competition. We are joined by Rafael de Rezende who was leading the Lokad team in this competition.
Arthur Conan Doyle’s iconic character Sherlock Holmes famously said ‘it is a capital mistake to theorize before one has data’. We certainly agree, as data is the foundation of any optimization process. Here, we discuss what companies that collect data can do and tackle the myth that data has to be “perfect” for a machine to be able to work with it.
In inventory control, there is a financial trade-off between purchasing more inventory and the cost of a potential stock-out. The more stock you have, the more working capital is needed and with too little stock on hand there are potential sales that can be missed, and even entire production processes that could be interrupted.