Business Analytics saves Christmas

As some of you may know, a keen fan of Capgemini’s Business Analytics (previously know as OR) team is Santa Claus. The team has helped him with problems in the past, so, when trouble struck, it was no surprise that Santa turned to the Business Analytics team again.

His request came during a recent internal training course that the team was holding on good techniques for modelling, and indeed came exactly at the moment when they were about to enter a team exercise.

Iain Hubert, who was leading the training, clicked on his link to North Pole HQ and Santa appeared on his screen outlining the problem.

It turned out that for a number of years, Santa had been using a unique flying machine to deliver presents around the world. This machine works at incredibly high speeds to get Santa around the world in time to make the deliveries. However it recently broke, and will not be fixed until after Christmas – which is too late.

So, this year, Santa is resorting to reindeer, and of course the magic dust needed to get them airborne. Each Reindeer amazingly adds 500,000 mph to the sleigh, and the idea is to get enough of them in order to be able to deliver all of the presents on time.

However magic dust is fantastically expensive, and with the heightened economic troubles on earth, Santa wanted to spend as much money as possible on gifts for the Children. So he wanted the BA team to help him determine the minimum number of Reindeer that were needed to deliver the presents.

Oh, and the order for magic dust had to be made within the next ½ hour!

At this, the BA team that were in the room immediately jumped into thinking about the problem and how it could be solved. There was not much information to go on, and so assumptions would have to be made.

Consu was the first to chip in with the idea that we considered the number of households with children around the world. Barry estimated the number of children at 30% of the 7 billion on the planet – a result of 2.1 billion children. And if we assumed an average of 2 children per household, then this meant just over 1 billion homes to visit.

Maddy had been searching on the web and she found that the surface area of the earth was around 150 million square kilometres. This equated to around 57 million square miles. Dawen then pointed out that, if we assumed that the homes were evenly distributed, this meant an average of around 0.05 square miles per house. Neil added that the average distance between houses was the square root of this number or around 0.23 miles. Ursuala did the sums and discovered that the total distance to travel was therefore a massive 245 million miles!

But how long did Santa have for his deliveries? Gráinne pointed out that with the earth rotating, he actually had longer than the 6 hours between 10PM and 4AM – he likely had around 30 hours. So Iain was finally able to put this together and calculate that Santa needed to travel at just over 8 million miles per hour. This meant that 17 reindeer would be needed, although Cathy suggested that one should be added, both to balance the team and just to make sure.

With the answer calculated, Iain contacted Santa again to give him the answer. Santa was overjoyed to receive the news, and promised the team an extra present in their sacks this Christmas.

The team then went on to discuss what colour Rudolf’s nose would be if he were travelling at that speed!

So if your children wake up on Christmas morning and they have a present in their sack, then you know that you have Capgemini’s Business Analytics team to thank.

We hope that you have enjoyed all of our Figure it Out offerings in 2012, and we wish you a merry Christmas.

We will return in 2013, with many more thoughts about numbers and their uses…