Business analytics is all about knowing where and how to gather the relevant data, how to compile them in a meaningful way, and how to apply a battery of analytical tools in order to cull meaningful conclusions that drive accurate, valuable guidance. Business analysts look at historic and current data in order to predict future trends. They are concerned with what comes next: how to anticipate, plan for, and manage the future.
Until relatively recently, the field of data/ science was limited by computer processing and memory capacities; the amount of data waiting to be crunched was simply beyond the capabilities of conventional computers. All that changed in the first decade of this millennium, as computing power surged (as did, not coincidentally, data aggregation).
We are now undoubtedly living in the age of big data, at the front end of what will likely be a long period of discovery, innovation, and insight. With the advent of big data, two fields positioned to exploit this treasure trove of information—business/ analytics and business intelligence—have risen in prominence.
The two roles are often confused or conflated, which is understandable given their similarities. Both involve the collection and analysis of data in order to identify and describe shortcomings in a business or business process. Both use an arsenal of software and statistical analytics to draw conclusions and offer recommendations. Both require expertise in quantitative analysis and computing.
Their chief difference lies in the nature of their recommendations. Business intelligence seeks to understand processes as they currently exist in order to improve them. It is concerned with the here and now, how to make what currently exists better. Business analytics looks at historic and current data in order to predict future trends. It is concerned with what comes next: how to anticipate, plan for, and manage the future.
Business analytics is all about knowing where and how to gather the relevant data, how to compile them in a meaningful way, and how to apply a battery of analytical tools in order to cull meaningful conclusions that drive accurate, valuable guidance. These analytical tools include computer simulations, data mining, integer programming, probabilistic modeling, and stochastic optimization: in other words, heavy stuff. A successful business analyst has strong quantitative skills, is generally strong in STEM/ disciplines, has excellent research capabilities, and has an interest in and aptitude for theory.
Be aware that relatively few schools offer a doctorate specifically in business analytics; most programs fold the discipline into a broader PhD in data science. Schools offering a business analytics doctorate include Bentley University, University of Pittsburgh, Drexel University, and Florida International University.
Business analytics PhDs most frequently end up in academic research and teaching roles. The PhD programs we surveyed reported the vast majority of its graduate placements on university business faculties, with only the occasional high-level corporate position. Many business faculty enjoy lucrative consulting sidelines, one of the perks of being a prestigious academic.
In early 2019, Salary.com projected a salary range between $105,409 and $133,488 (median: $118,985), plus another $6,000 to $12,000 in additional compensation for business analysts. Payscale.com, which breaks out its data by terminal degree, reports that a PhD in business analytics draws an average salary of $124,203. Most business analytics doctoral graduates find work in academia as professors and/or researchers. Fortunately, salaries for business school faculty tend to be high; at the University of North Carolina-Chapel Hill, where salaries are published, analytics faculty earned between $178,000 to $231,000 annually.
If your goal is to make a lot of money, the answer is almost definitely no. True, you should earn a great salary and enjoy other earning opportunities as a PhD, but the road to success requires a huge investment of time, money, energy, and passion. Plus, the opportunities for PhDs are typically limited to academic positions and top management/research roles in the corporate world.
In contrast, the opportunities for MBAs with business analytics concentrations and for students with master’s in business analytics are much more numerous, and are also quite lucrative. If your goal is to dig deep in data to find solutions for a corporate employer or client and earn a good living in the process, the MBA or master’s degree is probably the path to travel.
If, however, you want to become a leader in the field, or conduct cutting-edge research and develop new theories, or train the next generation of business analysts, then the PhD is probably the way to go.