Executive Summary

L’Equipe faced the challenge of estimating the daily market need for printed newspapers, dealing with both excess production and shortages, leading to missed sales and high costs. BearingPoint leveraged an in-house AI and machine-learning solution, Nitro, to help L’Equipe forecast next-day demands accurately, which improved efficiency and reduced their carbon footprint.

Sales performance demands accurate forecasting

In an age when the press is mostly delivered in digital form, L’Equipe engages its readers in both digital and print: a strategy that contributes to their long-standing success.

Although L’Equipe has a high, daily paid circulation, anticipating the actual demand for copies would seem to be an insurmountable challenge. Accurate sales forecasts of print editions are impeded by the fluctuating nature of sports events, as well as the influence of generic factors like weather conditions. Overestimating sales would result in papers being left unsold, creating a financial deficit; underestimating demand would lead to a shortage of copies and missed opportunities to make additional sales. L’Equipe is currently sold in approximately 25,000 vendor locations throughout France, with each retailer having allocated a specific average sales volume, adding to the difficulty of knowing the exact number of papers that need to be printed.

Using AI to transform historical data into accurate forecasts

L’Equipe joined forces with BearingPoint to address the issue of sales forecasting. The in-house data science and media team leveraged BearingPoint’s own Nitro AI-driven solution, which was developed specifically for publishers.

Nitro is a comprehensive set of managed services that use machine learning and an AI approach to focus on print-media supply chain forecasting. The in-house team inputted vast amounts of historical data, including units sold by period, units delivered, holiday sales, and weather variations. Nitro used this information, as well as new data added every day, to produce forecasting models that predict the exact number of paper copies needed by every retail location for the following day.

Optimizing the number of copies for each day

L’Equipe has successfully lowered the rate of unsold units by more than 5%, cutting the number of unnecessary printed copies by approximately 2 million. L’Equipe distribution planners are now able to easily adapt to different scenarios, relating to the impact of current events on sales. The user interface allows them to make changes at all scales, including individual units, with no specific AI knowledge required.

Planning resources were reallocated to higher value activities, such as analysis of market dynamic and customer behavior. Nitro’s ability to quickly compute numerous KPIs was essential in performing these activities effortlessly.

Even in the unprecedented and volatile context of the Covid-19 pandemic, planners were able to reduce damage to sales figures by using Nitro and maintaining a high accuracy in forecasting. L’Equipe’s social responsibility has grown, with Nitro playing a crucial role in reducing the newspaper’s carbon footprint.

Client

L’Equipe is the French market leader in sports’ press. It is famous for its extensive coverage of football, rugby, motor sports, and cycling. It is one of the country’s largest paid print publications.

With NITRO, we have an autonomous vehicle whose engine settings are optimized automatically, giving us more control. Our demand planners can fully develop their know-how and correct the projections by adjusting the forecasts made by the machine.

E. Matton, Editor & Director of the print division - Groupe Amaury

 

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