- Is There a Difference Between Analytics and Analysis?
- Where Does Data Mining Fit In?
- Why the Sudden Popularity of Analytics?
- The Application Areas of Analytics
- The Main Challenges of Analytics
- A Longitudinal View of Analytics
- A Simple Taxonomy for Analytics
- The Cutting Edge of Analytics: IBM Watson
Why the Sudden Popularity of Analytics?
Analytics is a buzzword of business circles today. No matter what business journal or magazine you look at, it is very likely that you will see articles about analytics and how analytics is changing the way managerial decisions are being made. It has become a new label for evidence-based management (i.e., evidence/data-driven decision making). But why has analytics become so popular? And why now? The reasons (or forces) behind this popularity can be grouped into three categories: need, availability and affordability, and culture change.
As we all know, business is anything but “as usual” today. Competition has been characterized progressively as local, then regional, then national, but it is now global. Large to medium to small, every business is under the pressure of global competition. The tariff and transportation cost barriers that sheltered companies in their respective geographic locations are no longer as protective as they once were. In addition to (and perhaps because of) the global competition, customers have become more demanding. They want the highest quality of products and/or services with the lowest prices in the shortest possible time. Success or mere survival depends on businesses being agile and their managers making the best possible decisions in a timely manner to respond to market-driven forces (i.e., rapidly identifying and addressing problems and taking advantage of the opportunities). Therefore, the need for fact-based, better, and faster decisions is more critical now than ever before. In the midst of these unforgiving market conditions, analytics is promising to provide managers the insights they need to make better and faster decisions, which help improve their competitive posture in the marketplace. Analytics today is widely perceived as saving business managers from the complexities of global business practices.
Availability and Affordability
Thanks to recent technological advances and the affordability of software and hardware, organizations are collecting tremendous amounts of data. Automated data collections systems—based on a variety of sensors and RFID—have significantly increased the quantity and quality of organizational data. Coupled with the content-rich data collected from Internet-based technologies such as social media, businesses now tend to have more data than they can handle. As the saying goes, “They are drowning in data but starving for knowledge.”
Along with data collection technologies, data processing technologies have also improved significantly. Today’s machines have numerous processors and very large memory capacities, so they are able to process very large and complex data in a reasonable time frame—often in real time. The advances in both hardware and software technology are also reflected in the pricing, continuously reducing the cost of ownership for such systems. In addition to the ownership model, along came the software- (or hardware-) as-a-service business model, which allows businesses (especially small to medium-size businesses with limited financial power) to rent analytics capabilities and pay only for what they use.
At the organizational level, there has been a shift from old-fashioned intuition-driven decision making to new-age fact-/evidence-based decision making. Most successful organizations have made a conscious effort to shift to data-/evidence-driven business practices. Because of the availability of data and supporting IT infrastructure, such a paradigm shift is taking place faster than many thought it would. As the new generation of quantitatively savvy managers replaces the baby boomers, this evidence-based managerial paradigm shift will intensify.