Since 1913, the New York Yankees have compiled 27 World Series Championships in their 104 years as a member of Major League Baseball. That is a rate of about one title every 3.85 years. The Oakland Athletics have compiled just four championships in their 49 years as members of the same league. That is a slightly lower rate of one every 12 1/4 years. There is a reason for this. The Yankees play in a far larger market area that gives them the resources to produce a much larger farm system where they can find new players than the Oakland team can afford. Then how would a small market team like the A’s compete against the Goliaths of the league like the Yankees?
In 2001, the general manager of the A’s asked that very question. He knew that baseball was the most statistically analyzed game in America, and had been since 1971 when the Society for American Baseball Research, or SABR, was founded. All he had to do was use those statistics to find the best players his organization could afford. He did, and his team of unwanted players won 20 straight games on its way to the playoffs. The tool of sabermetrics was born.
Data Science: Applying Statistics to Your Small Business Operation
If a small market sports team can use statistics to evaluate and improve its bottom line and find hidden gems within its own organization, why can’t a small business owner do the same? That is what data science is about. It is combing through the financial records of the company to correlate what may appear on the outside to be complete disparate elements of the business, only to see a hidden connection and possible financial hole or windfall.
Not Only Retail Business, but Medical as Well
One of the largest industries in desperate need for a statistical overall is the medical field. In this review by Sanjeev Agrawal in the Harvard Business Review, he delineates multiple areas where data analytics can reduce the cost of the hospitals doing business and therefore make them less likely to increase the cost to their patients. Analyzing scheduling procedures and correlating them with wait times at blood centers enabled an infusion center at NY Presbyterian to reduce their patient wait times by half. Emergency departments are well-known to have exorbitant wait lines.
Applying analytics to both the wait times and the use of the operating facility itself dramatically reduced wait times by rerouting procedures to open rooms. Emory University Hospital used software and predictive analytics to cut lab test wait times by 75 percent. That not only lowered the wait time but also improved the efficiency of the operation as a whole. That lowered operational costs. Sharp Healthcare in San Diego cut its admission-to-occupy time by three hours.
Then there is the benefit of accelerated discharge, which saves hospitals hundreds of thousands of dollars each year by enabling new and needy patients to admit sooner rather than later. Using simple statistical software, Georgetown University Hospital was able to predict which patients would be more difficult to discharge and therefore triage those patients in a more efficient manner. The software reduced hospital cost by 24 percent.
Data Science Also Includes Artificial Intelligent Devices
The insurance industry is now using artificially intelligent devices with built-in data analytics to accelerate the process of enrolling new members and ensure they are enrolled in the appropriate plans. No longer do prospects need to meet in person with an agent when an artificially intelligent bot on the insurer’s website can do that for them. This saves the insurer time — and therefore expense — that they can then spend building their business.
The underwriting process is where insurers usually run into trouble as the underwriter finds issues with the applicant’s background or scripts. This process can take weeks with a human underwriter doing the work. Or the underwriter can take a vacation for weeks while the applicant waits for their results. Bots do the work far faster, and they do not take vacations. This makes enrolling in the insurance plan a far more pleasing adventure for the consumer and radically reduces the cost of performing that underwriting to the insurer.
But, it isn’t just insurance companies. Banks are doing the same for the same reasons. Loans are processed faster and more correctly, as the bot and its software determine if the loan is correct and should be approved.
Easy Method of Identifying Ponzi Schemes
Had data science been accepted at the start of the millennium, Bernie Madoff’s Ponzi scheme could have been avoided. Data analyst Harry Markopolos used analytics to investigate the scheme and quickly figured out it was a fraud. Sadly, the SEC was very much behind the times and did not believe his results.
Data Science Is the New Frontier for Business
Data science turned a small market baseball team into a Cinderella team on a shoestring budget in 2001 and has continued to fuel similar teams throughout the league. With all of its power, data analytics is the new gold standard for maximizing the returns on any investment a business owner can make. Owners need to invest in new equipment to accelerate their sales and reduce the cost of those sales. They also need to know their customers better to offer them the services and products they deserve. Data analytics can do both.