With 1.9 billion children in the world, keeping track of who is naughty or nice must be an extremely daunting task, even for a person with magical powers such as yourself. If Jimmy has been nice up until April, how do you know if he will still be nice come December? Should you put your elves to work building a model train he asked for or will he be receiving a stocking full of coal? It takes a while to build the train – you can’t afford to wait to the last minute to start building or the elves will never finish in time.
Or what if Jimmy asks for a hot holiday item like AirPod headphones? If the elves don’t buy them soon enough, they may be a faced with an “item on backorder until Jan 4th” notice. This will stress out even the jolliest of men. However, if they buy them too soon and Jimmy ends up on the naughty list, there went $159 out the window. If you multiply that by 1.9 billion kids, the cost could be $302 Billion, and that doesn’t even include shipping or tax. What to do?
You sir, need Analytics! Analytics are the answer for your production and planning woes. If you were to use analytics, you could make an estimate of how many toys to build and buy based on the lists from last year. However, as you well know, kids change their holiday wish lists – and often. And what about their behavior? Who is to say that someone who is behaving well today will be doing so tomorrow? And what about Kirk, who has moved from the naughty to nice list this year? You will not have much historical data on his preferences.
This is where machine learning and advanced analytics can help you, Santa. Using machine learning, you can build a model to determine the probability of Jimmy, (1) wanting a toy train or wireless headsets come Dec 25, and (2) the probability of him staying on the nice list. The machine learning system will ingest the patterns of his previous wish lists and behaviors in the past and build models to predict his wishes and behaviors in the future. It will start by looking at the wishes of other children who match Jimmy’s profile and create a short list, ordering the list based on Jimmy’s personal preferences. The system will take into consideration factors such as: How many times did he change his mind in the past and at what point in the year? Does he usually stick with more traditional toys or does he like trendy toys, and if so, were they ever out of stock before? Has he ever moved from the nice to naughty list or vice versa? And if so, when?
The machine learning models will compare these new predictions against predictions made in the past and their subsequent results in order to give them a confidence score. Now you, sir, will know how likely it is that the toy your elves are building will be the one that Jimmy actually wants.
But what about Kirk who has just moved off the naughty list and on to the nice list? There is not much historical data. This is where AI comes in. AI allows you to make reasonable estimates, without ever having seen past patterns. Based on the information available, you can use AI to make a reasonable guess about what type of toy Kirk will like and the probability of him staying on the nice list.
Santa, just imagine all the time, stress and money you could save using analytics. Your elves could spend less of their timing buying, building and returning unnecessary items and more time with Rudolf and crew, fine tuning the present delivery route. You’d spend less time planning and more time relaxing with Mrs. Claus – maybe even sneak in a quick sleigh ride to Hawaii!
We here at Guavus are ready to help with an advanced analytics solution designed especially for you.
You know where to find us.
The Guavus Team (all on the nice list of course!)
PS – If analytics can do all of this for Santa, imagine what it can do for your business! Just as Guavus advanced analytics can optimize present planning and procurement, service providers all over the world use Guavus software to help them run their businesses more effectively, speeding up their time to market, reducing costs and providing innovative service offerings to millions of customers worldwide.
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