Why is data important?
Dad, why is math so important? ~ the Tech Innovator’s son.
My son is 8 years old and in 2nd grade. The other night, after he finished his homework, I said, “Let’s do some extra homework – let’s do division.” He said, “Dad, why do you want me to do extra work? Why do you want me to learn this?”
Like many Americans of Indian and Asian decent, our family places a high value on math and science, and I have an engineering background. So I replied to my son that you need math. Math is important. It is important to be very good in math.
Math is one of the foundation subjects. Just as English is the language of this country, math is the language of business. Math itself does not have a tangible “physics and chemistry” feel. You can’t accidentally set fire to your shirt sleeve with a math experiment, as I almost did once in chemistry class. But you can use math as the underlying toolset for everything you do. We use math when buying gas, banking, slicing up a birthday cake for twenty hungry 2nd graders – it’s all math.
The same philosophy applies in business. The revenue numbers, budget calculations, profits, expenses and creating efficiency – all we are using is math.
Math has different flavors. Basic multiplication, division, addition and subtraction evolve into statistics and probabilities. In terms of design, it is all about geometry and trigonometry.
Now consider the question of Data Analytics – why is data so important? Why are analytics so important? Analytics are based on math, statistics and probability. And it’s important that companies know how to use that toolset effectively.
For example, Ford Motor Company is using the data available in their cars to get insight into how their customers are using their products. Each car’s computer is connected via satellite to the Internet but, until recently, that data had always remained in the car. Now Ford is able to analyze and extract simple things like mileage, what time you are driving, how long between oil changes, etc. They have so much data in the car – more than they can possibly use. The internal machines collect the data, which is extracted and fed back to Ford’s Product Development analytics, where it can potentially give insight into how customers are using their vehicles, what they are potentially looking for, and any other analytics they can draw from customer usage, based on data.
Companies that learn to use the Data Analytics toolset effectively can grow to be healthy, wealthy and wise – just like people who learn to be very good at math.
A valid question from a kid’s point of view.
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