From checking the list to ensuring a smooth (and timely!) delivery of presents, in this blog we explore Santa's business process to see how Google Cloud could make the busiest night of the year easier for him.
As we enter the festive season, many of us are counting down the days until Father Christmas’ visit. But, have we stopped to think what happens behind the scenes to make this day possible? In this blog, I’ll take a look at Santa’s business processes and suggest ways he and his team could embrace cutting edge tech to outsmart their future.
When we consider what business Santa is actually in, we can see that there’s a mix of manufacturing and logistics, with a large amount of customer contact. Let’s break it down step-by-step;
Firstly, children from all around the world write their letters to Santa, pleading their case that they’ve been good this year and would like this, or that toy.
He then checks the list to see who’s been naughty and who’s been nice, to decide who should receive a toy. These then must be made by the hard working elves at the North Pole.
It’s important to check the list twice because it will impact the final process; the logistics of travelling the world delivering all the presents.
So, now that we have a basic understanding of the core processes, let’s discuss where cloud solutions might help:
A better way to handle children’s messages
Today’s children don’t just write letters. They’ll be using messaging tools and social media much more, and may even pick up the phone to call. So, the elves will need to staff a multi-channel contact centre to handle all this.
Google’s Contact Centre AI product can assist in different ways. Firstly, Virtual Agent uses Google Dialogflow to respond to customer requests 24 hours a day, even while the hard working elves are sleeping. Additionally, Agent Assist provides real-time assistance to the live agent, staying active during the conversation and suggesting answers to aid the elves.
Written communications, like letters and emails, can be passed through AutoML Natural Language to infer sentiment and key information from these messages.
The output of all this will be a queue of requests with information about specific children and their toy requests. This all has to be passed to manufacturing, who are likely to be slower than the contact centre. In this case, we’ll put the messages into Google Cloud Pub/Sub, so that they can be retrieved as needed by a subscriber service.
Lastly, we’ll feed all this data into Google BigQuery to start building our data warehouse. This will ultimately be used as the knowledge base of the entire operation.
Checking the list twice
The famous list has been getting steadily bigger over the years as the world’s population expands. There are now over 2 billion children, and that’s a lot of names for one person to check; twice! So we’ll keep the list in BigQuery, our serverless data warehouse with AI.
We’ll run a simple query which will return results in seconds:
SELECT * from the_list WHERE behaviour = ‘nice’
DataStudio allows the list to be easily visualised so we can see geo data and trends: Have girls been naughtier than boys this year? On average, have boys been nicer this year than last year?
Giving the elves an extra hand
As the elves make each toy by hand, we want to be able to easily identify any defects so that children don’t receive teddy bears with missing eyes or trains with wonky wheels. To tackle this, we’ll use Google AutoML Vision with a trained model of what each toy should look like.
In addition, we’ll update our BigQuery data warehouse with an ongoing inventory of toys as they are made. Finally, the elves in the workshop can collaborate with their colleagues in the contact center and Santa himself in his grotto using Google Workspace for real-time co-editing of documents and video conferencing using Hangouts Meet.
More efficient route planning
Let’s now look at how we can take a smarter approach to defining the route.
How about using historical weather data from Google Cloud Public DataSets? This will help us predict if it’s going to be a foggy Christmas eve in which case we’d need to deploy Rudolph with his red nose.
We can combine this with “the list” and toy inventory data in BigQuery and feed that to Google Maps Platform to help us plot the most optimum present delivery route.
Smarter and safer present delivery
Usually, when Santa sets off to deliver the presents, he’s on his own, apart from the reindeer of course. Yet, when we go on any car journey, we’ve probably got breakdown cover and many of us will use Fitbit type devices to track our health. Let’s consider how we can provide some peace of mind for Santa and Mrs. Claus.
We’ll start by giving Santa and the reindeer, health monitors to measure their heart rate and other vital signs. We can also kit out the sleigh with sensors for altitude, speed, vibration and a host of other indicators. These are managed using Google Cloud IoT Core, which allows us to securely connect, manage, and ingest data from millions of globally dispersed devices.
Some of this sensor data may be streamed real-time via satellite while other data may be stored in the device and then downloaded when back at base. Google Cloud Dataflow handles this stream and batch data, and is a useful integration point to Google Machine Learning where our model will learn from all sensor, route, list and weather data to become more accurate at predicting the optimal route for next year.
And to all a good night
This way, with Google Cloud’s help, Santa, the elves and the reindeer can take a smarter approach to Christmas and make it a magical season for millions of children around the world. .
Whatever you celebrate at this time of year, best wishes to one and all.
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