Today’s business world has come a long way since the days of Henry Ford. Software, databases and automation tools help turn managing business data into a more approachable task. So how did we go from the days of painstaking manual labor to a streamlined technological future?

The first formalized system of business analytics in the U.S. was developed during the late 1800s by Frederick W. Taylor. Taylor’s System of Scientific Management, sometimes called Taylorism, tracked laborers’ body movements to discover greater efficiencies that ultimately boosted industrial production. He developed the stopwatch time study, where he broke a job into its component parts and measured each one to the hundredth of a minute to see where workers could be more efficient with their movements.

One of the more famous examples of business analytics was Taylor’s study involving shovels. He noticed that workers at the Bethlehem Steel Company, where he was employed at the time, used the same shovel for all materials even though they were vastly different materials, such as dense iron ore and feather-weight ash. He determined the most effective load to prevent excessive worker fatigue was 21½ lb., so he found and designed shovels for each material that would scoop exactly that amount. For the Bethlehem Steel workers, this amounted to eight different shovels. “The tools nearly quadrupled the productivity of each shoveling laborer, improving the average worker’s daily output from 16 to 59 tons,” according to Mental Floss, who dubbed Taylor “The Patron Saint of Shovels.”

As a consultant to Henry Ford, Taylor influenced his car assembly line time measurements. Taylor believed that there was “one right way” to perform a task, and Ford used that as inspiration to break down assembly line tasks into simpler ones. Taylor also believed that all employees should be given work that suited their capabilities and strengths. Innovations like these helped Ford reduce the time it took to build a car from 12 hours to just over two.

In the early 1900’s, Taylorism spread as the “best practice” for business analysis and management. Harvard University, one of the first American universities to offer a graduate degree in business management in 1908, based its first-year curriculum on Scientific Management. Taylor even lectured at the university every year before he died in 1915. Eight years later, the school broadened the business management curriculum to be more inclusive of other business types as Taylor’s systems primarily benefited manufacturers, who used them to increase the efficiencies of their production lines.

Today, the business analytics field is more universally used by various organizations. It’s used to predict customers’ behavior, prepare budgets and decide fund allocation. Computers do much of the record keeping and calculations, which puts an emphasis on the business analyst to do the “analyst” part of the job.

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Defining Business Analytics

The definition of business analytics is “the study of data through statistical and operations analysis, the formation of predictive models, application of optimization techniques, and the communication of these results to customers, business partners, and executives.” In other words, business analysts are number crunchers who know how to translate business figures, like sales, traffic and budgets, into patterns and analyze them, then share that information with people who can make changes.

There are several different processes involved in business analytics, including:

•  Business intelligence: An analyst examines historical sales data for a company to get a sense of how the company has performed over time. Historical data can reveal trends. For example, a bookstore may sell more books during the winter holidays every year; this can reveal that the bookseller needs to boost their inventory during those months. Perhaps a car dealership has consistently underperformed on Mondays, suggesting the dealership should be closed on Mondays and opened on Sundays instead.

•  Statistical analysis: Using algorithms, analysts can turn non-mathematical occurrences into mathematical code and use computer programming to make predictions or solve problems. Recently, Dalhousie University math professor Jason Brown and Harvard’s Mark Glickman, a senior lecturer in statistics, analyzed Beatles’ songs and used statistical analysis to determine who wrote each song – John Lennon or Paul McCartney. They turned every aspect of the songs from octave changes to word choice to chord progression into code and then ran that information through their computer program. Some in the music industry are testing the use of this technology during copyright disputes to determine authorship for songs in question.

•  Prescriptive analytics: An analyst uses past performance as a basis for recommendations on solving future problems. While statistical analytics looks at data that already exists, prescriptive analytics uses that data to predict future outcomes and make recommendations. Because of the nature of this process, it isn’t fool-proof; it cannot consider outside and unexpected forces. A sports analyst may look at a player’s past stats and how much he or she has improved over time and make predictions about how that player will perform in the upcoming season. Of course, the results will be irrelevant if the player suffers a season-ending injury.

Working in the Business Analytics Field

Businesses are looking for people who are trained to track profits, dissect budgets and improve their company’s bottom line. Typical duties for business analysts include:

•  Leading data-driven analysis and creating analytic models to assist in developing business strategies. Some of these models may be visual and represent data in graphs or charts, for example. Knowledge of statistical concepts like descriptive statistics, moving averages and regression would benefit analysts.

•  Drafting reports and presenting results and recommendations to key stakeholders and business partners. Analysts must also have strong communication skills, both written and oral, to be able to share their findings clearly.

•  Establishing performance indicators and success metrics for proposed and existing initiatives, products and services. Typically, the success or failure of an analysis by the quality (profit) of the resulting business decisions, its speed and robustness (continued yield of good results).

Business analysts work mostly in an office setting during business hours, although it’s not uncommon for them to be “on call” in professions where the data is particularly volatile and changes quickly, like ones that deal with the stock market or fossil fuels. There may be times when an analyst must work overtime. The career path of a junior business analyst might lead to a position as a manager or as a lead or senior analyst.

Typical applicants have a degree in business administration, economics, finance or math. Entering the field with a master’s degree in analytics will likely increase chances of being hired at a higher income level. The aspirational position for a business analyst would be to serve as a chief operations officer or even a CEO to a company. Advancement to these senior levels would likely required an advanced degree, such as a Master’s in Analytics.

Though the median annual salary for the overall field is $59,358, Payscale reported $131,394 as the median salary for a business analyst in a senior position. Users on the site stated business analysts working for Target average between $55,00 – $60,000 a year; at Cisco Systems, between $61,000 – $87,000; and Amazon’s salaries range from $61,000 – $100,000 a year. None of those figures include commissions or bonuses, which are common practices in the field.

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