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Data—whether it's sales, stock prices, or test scores—helps organizations measure their performance, but it's analytics that helps them identify patterns and make better, more comprehensive decisions. In this interview, awarding-winning mathematics professor Wayne Winston sits down with us to explain why analytics are important, and offer guidance for those trying to break into the field as an analytics professional. He also explains how analytics can provide insights into supply chains, marketing, and financial data, and help cities, school systems, and hospitals better meet the needs of the public.
Well for a long time companies have been using data to try and make better decisions, so analytics is simply a new buzz word to apply to that process. And the word analytics I believe comes from a book Computing on Analytics written by Thomas Davenport around 2005, 2006 and that book popularize the word analytics simply using that for any situation which an organization is trying to use data. To improve their decision making and do better with regards to their cor, their objectives. So, let's give you a couple of examples of organizations that might use analytics.
So let's suppose you're in the education profession, you might be a K through 12 teacher. You might be a college professor. You might be an administrator. So what are some objectives you have? Well one objective is to make the kids in K through 12, more ready for college or the workforce. And so basically, how can you use data to basically improve that? You might work for a company that's goal is to make money, unlike K through twel, unlike the education business, so I think you probably would like to help your company make a higher profit. So how can we use data to help our company make a higher profit? You might work for a non- profit like the Gates Foundation.
The Gates Foundation's goal is fairly simple. Given the amount of money they spend, in most cases, save the most lives. So, basically, can we use data to figure out what's the most efficient way per dollar spent to save lives? Obviously there could be almost no more objective than that. Well, another situation where you might want to use analytics, is when you're trying to basically save for retirement, which we all are doing unless we're retired and then we want to make our money last as long as possible. So the question would be, how should we allocate our assets so we have a minimum level of risk that gives us a desired expected return.
We can put everything in a very risky investment but. If you had bought NASDAQ at 5,000 in 1999, NASDAQ probably won't see 5,000 again for a bunch of years, and so basically you would've lost a lot of money. So using analytics and what we call portfolio optimization is a very important tool. Well, all of use are concerned with our personal health. And then healthcare we know, is basically (INAUDIBLE) in the United States and other countries with a lot of money. And the outcomes the United States achieves relative to other countries, is just not that good for the amount of money we spent.
So how can we use data to improve healthcare outcomes and also possibly reduce healthcare costs? So those examples should give you some feel, for where analytics are using data to solve, to make better decisions, will be helpful.
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