Is analytics really new?

Data analytics is now the craze. From the “sexiest” job (“data scientist”), as previously indicated by the Harvard Business Review, to the overabundance of demand vs. supply of data scientists, organizations are clamoring to tap the expertise of business analytics professionals and data scientists to look for insightful trends and improve organizational decision-making.

I am certainly part of this fan club, as evidenced by launching a new book series on data analytics applications to be published by Taylor & Francis. (We already have 12 books signed, ranging from sports, education, business and healthcare to government, law, cybersecurity and beyond). However, in stepping back and contemplating this emerging field, I wonder if “analytics” is really something new.

With my background in operations research (O.R.) and artificial intelligence (AI), I see many of the underlying foundations and techniques being applied in analytics coming from these disciplines and other fields (such as social psychology if looking at intuition-based decision-making and analytics). Whether looking at structured or unstructured data, the database management, AI and OR/OM (operations research/operations management) communities have certainly contributed greatly to the field of analytics. Of course, with some of the newer languages like R and Python and Hadoop architectures, the field of data analytics has some potentially unique elements that have evolved from computer science, statistics, mathematics and other fields. But, is this field of analytics so new and what’s driving it?

If you look at industry research like Gartner’s, you see that business intelligence (BI) and analytics are focused on some hot topics such as modern BI-modal BI, advanced analytics, automated decisions, self service, Internet of Things, data lakes, chief analytics officers, algorithmic business and the cloud. And, if you look at the Forrester Wave for BI and Analytics, you see that predictive analytics will continue to be an important capability needed by organizations, with prescriptive analytics the hope for the future.

Organizations continue to be inundated with data, both internal and external, and they need improved ways of making sense of this onslaught of both structured and unstructured data. This is where analytics seems to be playing an important role, along with filling other niches such as customer analytics and healthcare analytics.

But again, is this really new? There is a growing trend for a relatively new position in organizations, namely the chief analytics officer (CAO). However, in my experience, many companies have decentralized the analytics expertise within the various functional/business units in the company. I believe there may be some sub-optimization and duplication of analytics resources being used without having a more centralized CAO function. The annual SAS Analytics Summit typically attracts more than 150 CAOs as part of its executive component, and there seems to be a growing trend for this type of position. This reminds me of my knowledge management days with the chief knowledge officer (CKO) position. Unfortunately, though, the CKO position didn’t rise to as much prominence as many people thought. I wonder if this may be the same fate with the CAOs.

Well, no matter whether new or old, the analytics field will speedily grow in the coming years. As a shortage of data scientists looms and the influx continues with varied types of data of great quantity and velocity, it probably is a safe bet to encourage those individuals who have some technical orientation to pursue analytics. Of course, cybersecurity would be another great opportunity for those with similar inclinations. More analytics and data science programs are being developed at universities worldwide in order to meet the growing demand for graduates with these types of skill sets. In our MS in Analytics program, we already have about 300 students in this degree at Harrisburg University of Science and Technology.

In a way, analytics is taking a similar path as knowledge management. Knowledge management is a multidisciplinary field with some of its roots laden in AI, organizational learning, human capital strategy and business process innovation. Analytics has its underlying foundations in the computer science, AI, statistics, O.R. and management disciplines. As knowledge management initiatives are fading a bit in organizations, hopefully analytics will pick up the slack and ensure a greater longevity for improved decision-making and insights. If not, we will wait until the “next great thing” in order to make our organizational lives easier, and still debate whether this “next great thing” seems new or not.