Auto-refresh your data from Salescast

Published on by Joannes Vermorel.

The user interface of Salescast had barely changed since the last major upgrade we shipped two years ago. However, under the hood, Salescast had been undergoing steady changes to improve reliability and performance.

This summer, we released native support for Brightpearl, Linnworks and TradeGecko. However, those new capabilities of Lokad were not integrated into Salescast, and, as a result, generating a new forecast report required 4 steps:

  1. Go to Sync in Lokad, and trigger a refresh.
  2. Wait until the data refresh is completed.
  3. Go to Salescast in Lokad, and trigger a run.
  4. Wait until the forecast reported is generated.

Obviously, the steps 1 and 2 were less than desirable. Thus, we opted for a more drastic revision of the Salescast user interface. The webapp has now a Project creation wizard that let you directly bind a data source with your Salescast project.

Once the data source is bound to the project, any Salescast run will start by automatically refreshing the data source. This entirely removes the two convoluted steps 1 and 2 as detailed above.

If you have been using Salescast already and if you wish to benefit from this new feature, you need to delete your existing Salescast project - look for the Delete button below the settings in the project view - and then to re-create a project. If you have already configured a data source in the Sync tab, then Salescast will offer you the possibility to use this data source directly, leveraging the existing configuration.

We have another major evolution for the user interface of Salescast in the development pipeline. Stay tuned.

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Job: Quantitative Business Analyst

Published on by Joannes Vermorel.

Once again the Lokad team needs to expand. This time we are seeking a quantitative business analyst.

Job description

Your goal will be to drive commerce companies - our clients - to improve their performance when tackling a variety of quantitative challenges such as inventory forecasting or pricing optimization. In order to achieve this goal, you will benefit from the technologies that Lokad has developed, and you will also benefit from a direct mentoring from the Lokad founding team. You will be reporting to the COO of the company.

Your contributions will be varied:

  • deciphering ins and outs of businesses and assist the clients in extracting the data actually relevant to the resolution of their challenge.
  • communicating a vision of how to best address the business goals considering the technologies available and through a realistic use of the data.
  • exploring the data of the client and assessing both potential data problems and potential data usages aligned with the clients’ business goals.
  • implementing some quantitative optimization logic, along with the corresponding workflows to consume the results produced by Lokad.

The quality of your contributions will have a significant impact on the business value generated by Lokad for the client.

Most of our clients operate either in North America or Europe. You will primarily communicate with them by email and phone. Once in a while, a large client may require an actual meeting to take place, but this is rather the exception than the norm. From the client perspective, Lokad will train you to become the Lokad expert who manages their account.

This position is in our office in Paris (13th arrondissement). This job is not eligible for remote work. Salary depends on the experience and subject to negotiation. We’d prefer at least 1 or 2 years of experience.

Desired Skills

Excellent communication skills, both oral and written, and both in English and in French, are necessary. Most businesses are satisfied with abysmal writing, producing documents so boring and confusing that the documents are not even worth the time it takes to read them. You will be expected to be able to produce sharp, technical and well-written reports.

We do not expect you to have any prior knowledge on commerce optimization. However, you will be dealing with a lot of data. If you happen to be a wizard at Excel calculations, this will strongly play in your favor. Also, while programming skills are not required, even modest skills in this area would already be a big plus.

We do not expect you to have much prior knowledge on statistics, especially about the modern statistics flavor favored by Lokad, however, we expect you to have a sharp analytical mind, and to be “good with numbers” in general. “Fixing” a broken quantitative optimization process frequently boils down to pinpointing the one incorrect calculation step among a dozen steps or more.

To apply just drop a mail to with your resume.

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Inventory forecasting for Aerospace

Published on by Joannes Vermorel.

While the core focus of Lokad’s activity has been on commerce since the very beginning, over the years, we have also delivered forecasts and optimized stock levels for a variety of other verticals. Some verticals prove to be more challenging than others as far forecasting is concerned, and the aerospace industry with its low rotations, its highly expensive parts and its costly stock-out incidents - i.e. grounded aircrafts waiting for a missing part - is certainly one of the most challenging verticals in terms of forecasting. In particular, classic inventory forecasting models tend to work very poorly for aerospace, primarily because the underlying assumptions behind these classic models (normal distributions, Poisson distributions, weekly or monthly forecasts) completely misfit the actual statistical patterns observed in aerospace.

Over the last 6 months, we have re-engineered a brand new forecasting engine purely dedicated to aerospace. At its core, this forecasting engine also leverages quantile forecasts, because this type of forecasting is about the only class of statistical models that actually works for aerospace. However, unlike our initial forecasting engine targeted at commerce, this variant natively integrates the logistics associated with high-cost repairable parts where components are first changed and then repaired. In particular, the TAT (turn-around times) are also modeled through quantile forecasts. In addition, among other industry-specific factors, fleet composition over time, including known future evolutions, is also natively integrated into the forecasting engine.

Considering the complex structure of the aerospace market, Lokad does not offer a packaged inventory forecasting solution readily accessible online as we do for commerce. However, if you are interested in forecasting for aerospace, don’t hesitate to drop us an email anytime at

Categories: Tags: aerospace No Comments