Lokad Forecasting SDK

With the advent of cloud computing, a little more than a decade ago, it has become straightforward to acquire computing resources on-demand (storage, compute, network) pretty much at any scale as long as one is willing to pay for it. Yet, while it is ... [More] straightforward to perform large scale calculations over the cloud computing platform of your choice, it does not imply that it will be worth the cost. At Lokad, we do not charge our clients per GB of storage or per CPU per hour. Instead, the primary driver for our pricing, when opting for our professional services is the complexity of the supply chain challenge to be addressed in the first place. Naturally, we do factor into our prices the computing resources that we need to serve our clients, but ultimately, every euro that we spend on Microsoft Azure - spending-wise, we did become a “true” enterprise client - is a euro that we cannot spend on R&D or on the Supply Chain Scientist who is taking care of the account. [Less]

With the advent of cloud computing, a little more than a decade ago, it has become straightforward to acquire computing resources on-demand (storage, compute, network) pretty much at any scale as long as one is willing to pay for it. Yet, while it is ... [More] straightforward to perform large scale calculations over the cloud computing platform of your choice, it does not imply that it will be worth the cost. At Lokad, we do not charge our clients per GB of storage or per CPU per hour. Instead, the primary driver for our pricing, when opting for our professional services is the complexity of the supply chain challenge to be addressed in the first place. Naturally, we do factor into our prices the computing resources that we need to serve our clients, but ultimately, every euro that we spend on Microsoft Azure - spending-wise, we did become a “true” enterprise client - is a euro that we cannot spend on R&D or on the Supply Chain Scientist who is taking care of the account. [Less]

Supply chains are complex and as a result our clients frequently end up with a dozen bespoke dashboards, each dashboard being designed as an entry point to address a key business challenge. As the modelization of the supply chain gets refined over ... [More] time, the complexity of the Lokad account tends to grow as well, merely reflecting the incremental improvements that have been brought so far. Recently, we realized that while Lokad is tremendously capable of orchestrating a complex quantitative modelization of a world-spanning supply chain, the user experience could be somewhat overwhelming when logging into an account that contains dozens of advanced dashboards. [Less]

Supply chains are complex and as a result our clients frequently end up with a dozen bespoke dashboards, each dashboard being designed as an entry point to address a key business challenge. As the modelization of the supply chain gets refined over ... [More] time, the complexity of the Lokad account tends to grow as well, merely reflecting the incremental improvements that have been brought so far. Recently, we realized that while Lokad is tremendously capable of orchestrating a complex quantitative modelization of a world-spanning supply chain, the user experience could be somewhat overwhelming when logging into an account that contains dozens of advanced dashboards. [Less]

Supply chains are complex and as a result our clients frequently end up with a dozen bespoke dashboards, each dashboard being designed as an entry point to address a key business challenge. As the modelization of the supply chain gets refined over ... [More] time, the complexity of the Lokad account tends to grow as well, merely reflecting the incremental improvements that have been brought so far. Recently, we realized that while Lokad is tremendously capable of orchestrating a complex quantitative modelization of a world-spanning supply chain, the user experience could be somewhat overwhelming when logging into an account that contains dozens of advanced dashboards. [Less]

Many supply chain challenges can be framed as either classification or regression problems. For example, forecasting demand can be seen as a regression; while deciding whether aligning a price with the price point of a competitor is acceptable can ... [More] be seen as a classification. A random forest is a machine learning technique that can be used to learn patterns from data, typically with the intent of performing either a classification or a regression. While random forests are no longer state-of-the-art machine learning - deep learning outperforms them in many if not most situations - there are still distinctive practical advantages associated with random forests, which have been nicely summarized by Ahmed El Deeb in The Unreasonable Effectiveness of Random Forests. Indeed, when Ahmed El Deeb points out that It’s really hard to build a bad Random Forest!, I do concur, and this represents a significant practical advantage. In contrast, deep learning models are, well, finicky to say the least, and a trove of obscure parameters can improve - or degrade - performance in ways that are not always very clear to the data scientist. Thus, random forests are now built-in within Envision. Bonus: the predictions of random forests are returned as random variables which makes a nice combo for probabilistic approaches of supply chain optimization. [Less]

Many supply chain challenges can be framed as either classification or regression problems. For example, forecasting demand can be seen as a regression; while deciding whether aligning a price with the price point of a competitor is acceptable can ... [More] be seen as a classification. A random forest is a machine learning technique that can be used to learn patterns from data, typically with the intent of performing either a classification or a regression. While random forests are no longer state-of-the-art machine learning - deep learning outperforms them in many if not most situations - there are still distinctive practical advantages associated with random forests, which have been nicely summarized by Ahmed El Deeb in The Unreasonable Effectiveness of Random Forests. Indeed, when Ahmed El Deeb points out that It’s really hard to build a bad Random Forest!, I do concur, and this represents a significant practical advantage. In contrast, deep learning models are, well, finicky to say the least, and a trove of obscure parameters can improve - or degrade - performance in ways that are not always very clear to the data scientist. Thus, random forests are now built-in within Envision. Bonus: the predictions of random forests are returned as random variables which makes a nice combo for probabilistic approaches of supply chain optimization. [Less]

Many supply chain challenges can be framed as either classification or regression problems. For example, forecasting demand can be seen as a regression; while deciding whether aligning a price with the price point of a competitor is acceptable can ... [More] be seen as a classification. A random forest is a machine learning technique that can be used to learn patterns from data, typically with the intent of performing either a classification or a regression. While random forests are no longer state-of-the-art machine learning - deep learning outperforms them in many if not most situations - there are still distinctive practical advantages associated with random forests, which have been nicely summarized by Ahmed El Deeb in The Unreasonable Effectiveness of Random Forests. Indeed, when Ahmed El Deeb points out that It’s really hard to build a bad Random Forest!, I do concur, and this represents a significant practical advantage. In contrast, deep learning models are, well, finicky to say the least, and a trove of obscure parameters can improve - or degrade - performance in ways that are not always very clear to the data scientist. Thus, random forests are now built-in within Envision. Bonus: the predictions of random forests are returned as random variables which makes a nice combo for probabilistic approaches of supply chain optimization. [Less]

2018 has been a fantastic year for Lokad - we achieved more than 50% growth while remaining profitable. For 2019, I am wishing the best to our all clients who trusted us and made this possible. Anecdotally, in 2018 among the employees of Lokad ... [More] French citizens have become a minority, representing no more than 40% of the workforce. Our customer base was already highly international, as France amounts for less than 20% of our revenue, and now the very composition of the Lokad team is catching up with the diversity of our clients, and the reach of their own supply chains. [Less]

2018 has been a fantastic year for Lokad - we achieved more than 50% growth while remaining profitable. For 2019, I am wishing the best to our all clients who trusted us and made this possible. Anecdotally, in 2018 among the employees of Lokad ... [More] French citizens have become a minority, representing no more than 40% of the workforce. Our customer base was already highly international, as France amounts for less than 20% of our revenue, and now the very composition of the Lokad team is catching up with the diversity of our clients, and the reach of their own supply chains. [Less]