But Santa and crew could still benefit from using things like machine learning and data analytics and even robotic process automation for what they do. Five ways:
Machine learning for data analytics
According to the United Nations Population Division, there are currently 1.9 billion children under the age of 15 worldwide. Not all of them write letters to Santa for the presents they’d like to get, but assume that at least a billion or so kids do send letters. That’s a lot of data to analyze — part of the trend of big data becoming ginormous data — and it’s getting to be far more information than anyone can make sense of.
In Santa’s case, Naughty or Nice lists must be verified. Toy selections must be confirmed. Data must be ingested, processed, stored and presented at the North Pole. A machine learning model could help Santa and his team more effectively gather data from submitted letters and other sources, such as apps and web portals, and analyze it at a deeper, more intelligent level.
For example, by creating enhanced data patterns in Naughty or Nice lists and wish lists, Santa could use these advanced data analytics to more accurately determine whether a child has been good or bad, and assure that he or she gets exactly what they asked for.
Machine learning to augment the work of elves and helpers
Elves do an incredible amount of work as it is. There is little reason to try to replace them. However, machine learning would augment their work by making processes at the North Pole more efficient.
Particularly for the global operations the North Pole supports, a machine learning model could be engineered to optimize logistics, supply chains and production tasks. This would streamline work for elves and other helpers and increase their toy production outputs. Elves could also easily be trained in IoT and artificial intelligence technologies to marry their production knowhow with new technical skills for the digital transformation. Industrial manufacturing is just one industry now reskilling its workforce in this manner.
And should Santa ever decide to implement robotics for North Pole production, AI-based robotic process automation could be a further step.
Robotic process automation (RPA)
Many enterprises have increased their use of intelligent automation tools like RPA for business tasks such as inventory management, production support and order fulfillment. Despite its reputation for hand-crafted toys and little need for automation, RPA could similarly enhance the North Pole’s production practices.
By combining RPA with artificial intelligence, for instance, RPA applications could go from simply collecting and processing data to performing in-depth data analytics and making contextual decisions (in lieu of Santa) to determine how toys are developed and produced. RPA could also encourage a strategy for intelligent automation across the North Pole as Santa recognizes its ability to reduce operational costs and increase elf workforce capacity and involvement.
To date, executives who’ve chosen to implement RPA in their enterprise note that employees are more engaged by way of strategic planning and creative thinking. This kind of robotic process automation could impact elves and helpers in the same positive way.
IoT and data analytics for predictive sleigh maintenance
In the movie Elf, we saw what happened to Santa’s sleigh in Central Park when the rocket blaster fails. Had the sleigh been equipped with IoT-connected sensors and AI for predictive maintenance, Buddy would never have had to come to the rescue to get Santa back in the air.
To monitor sleigh performance and detect a system outage before it occurs, engineers at the North Pole could continually gather and analyze data via connected sensors on Santa’s sleigh. Devices could also be connected to Rudolph and each reindeer for associated data collection. Then, using Google Cloud Platform as an IoT foundation for predictive modeling and data ingestion and storage, engineers could retrieve and analyze data at determined intervals in line with scheduled sleigh maintenance.
During Santa’s flight, defined conditions for sleigh components and each reindeer could automatically trigger alerts to North Pole engineers for performance issues. Alerts could be presented on a world map tracking Santa’s location in real time. Engineers could then quickly diagnose an issue based on the alert and specify the needed repair and any parts to be replaced… such as a failed rocket blaster.
Prescriptive analytics for foresight
It’s said that Santa and his elves take only one day off before gearing up for the next year’s holiday season and children’s requested wishes. Prescriptive analytics would provide a lengthier head start with foresight for wish list intelligence and toy production requirements over an extended period of seasons.
In conjunction with predictive analytics, which would predict what would happen if the North Pole’s circumstances never changed (i.e., insight), prescriptive analytics could let Santa and his helper staff modify specific variables of a predicted outcome to achieve a best possible result longer term (i.e., foresight). IoT, machine learning, and prescriptive analytics tools like Google Cloud Machine Learning and IBM Watson all feed into building a prescriptive model to optimize critical factors.
For the North Pole as a whole, these factors could include toy outlooks, elf workforce capacity, scheduling, supply chain management, and so on. Santa could then prescribe a corresponding long-term course of action to address demand for the most popular toys over the next several holiday seasons and how best to produce needed volumes. And rather than one day off before gearing up for next year, he and his helpers could take an entire week.
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