Scenario & Challenge
Christmas is no joke, especially for Santa Claus. Each year Father Christmas has only one night to deliver gifts to the entire world population, which in 2022 reached 8 billion people. Even considering only children and young people under 18, we are talking about 2,3b potential recipients to be visited and given gifts in very few hours – flying east to west. This is why optimising delivery has become of paramount importance.
This year we have had the lifetime opportunity to team up with Santa’s team in Rovaniemi. Santa’s Office CEE (Chief Executive Elf) asked us to devise a solution for maximising the efficiency of sleigh-based delivery, in order to guarantee a safe and effortless distribution of gifts all around the world.
We immediately thought of using technology to monitor in real time sleigh and reindeers’ performance, leveraging data to dynamically adjust the gift-delivery strategy. This can be achieved thanks to the combination of connected telemetry sensors and machine learning models to generate descriptive and prescriptive intelligence.
Since the year 2000, Santa has started collecting a vast range of gift-delivery data thanks to a sensor-based telemetry system on his sleigh and reindeers.
Data collected can be grouped into 3 categories:
- Wind Speed
- Altitude above sea level
- Oxygen in the atmosphere
- Delivery place conditions
- Presence of chimney
- Type of house
- Presence of in-house pets
- Distance from next delivery place
- Balancing of transported cargo
- Weight of transported cargo
- Reindeer energy
- Wear of runners
- Temperature on board
The two main challenges to overcome for Father Christmas are:
- Assess when he will be able to safely reach the following point of delivery
- Estimate when he will be able to complete all deliveries
Thanks to the historical data collected in 22 years, from Christmas 2000 until 2021, Santa Claus was able to label the two targets. This allowed us to create a supervisioned multi-target AI model that is capable of accurately predicting in real time the necessary delivery time. In this way, Santa can dynamically adjust his delivery speed based on the model’s output.
Following Exploratory Data Analysis, it can be seen that all variables collected have an influence on the target. For instance, if Santa’s sleigh is flying at high altitude, the reindeers can experience shortness of breath and thus reduce the speed. If they are tired and flying on low energy levels, they need to stop to rest and eat. If the delivery point lacks a chimney, or a watchdog is in place, dropping the cargo may be more difficult and thus time consuming.