Big Data Analytics for La Poste

Utilizing an integrated Big Data Analysis platform to develop a Predictive Analytics application

The French Post Office (La Poste) needed to provide reliable forecasts for the management and distribution of its material




La Poste


Data Analytics


Bouquet platform


Evidence –based decision making
Evidence –based decision making
Reliable forecast of workflows and workload
Reliable forecast of workflows and workload
Optimized usage of material sorting and storage facilities
Optimized usage of material sorting and storage facilities

The insights behind the project

The French Post Office (La Poste) handles huge volumes of letters and parcels every day. It is an entity that relies on the speed and accuracy of receiving mail and packages regardless of location, time, or cost. The variety of postal products and services available has led to a rapid increase in the data associated with these flows. Due to this, the non-automated (manual) processing of this data made it almost impossible to effectively access critical information.

What we did for the client

Athens Technology Center (ATC) developed a predictive analytics application, utilizing Bouquet, an integrated Big Data Analysis platform.

The application provides assistance for important administrative decisions, mainly in terms of the recorded daily and weekly traffic. The relevant forecasts are based on statistical and mathematical models applied to historical traffic data.

Specifically, there were 4 basic modules developed:

  • Administrative, for the provision of route lines forecast in key facilities.
  • Delivery, for the mail and package forecasting delivery to factories, headquarters, and post offices.
  • Business Correspondence, for the traffic forecasts for bulk shipments of advertising and information material (e.g. free samples, promotional letters, coupons, etc.), delivered from various companies to consumers.
  • Performance management, a combination of the above 3 forecast types to find the remaining capacity at a factory level, either for maintenance purposes or for professional mail promotions, in order to optimize the use of the facilities.

The outcome

The ultimate goal of La Poste was to reliably predict workflows and workload, especially in the fields of management and distribution. The ability of having easy and direct access to grouped, visualized, and directly comparable data, is rather important for the French Post as it ensures the safe and fast execution of their work.

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