“Analytics”, according to IT vendors, can save time, money and improve decision-making. No one would dispute the idea that data that has been filtered, analyzed and synthesized can provide useful information that delivers significant value. Unfortunately, “analytics” is being thrown around generically by vendors in many different contexts, representing a wide range of capabilities that are as different as polar bears and Amazonian ants. As a result, “analytics” has become ambiguous and poorly defined.
Consider the extremes of vendors using the “analytics” label. One vendor claims its management tool provides analytics, when all it does is provide basic data that users can use to further analyze an infrastructure problem. While another vendor's analytics applies sophisticated analysis that provides unique information and new insights that would previously have required a subject matter expert to obtain.
This situation of loosely defined analytics capabilities is a problem for both vendors and IT users — expectations will rarely be met when there is no common ground regarding definitions. The waters get muddier still when customers talk with different vendors, each with their own definitions, and try to compare products and solutions.
Most simply, “analytics” is a catch phrase for a category of analysis that is still being defined, as it evolves with the use of new technologies and approaches. On the other end of the spectrum, more complex definitions of “analytics” involve a discussion of how the underlying math is applied to solve complex problems. Vendors and customers should start with a dialog that falls somewhere in the middle, and looks at analytics within the context of the customer problem that it solves, so that the value delivered becomes apparent.
Buyers should keep in mind that:
Analytics is not one of those capabilities that is a “yes” or “no” checkbox item when evaluating technology tools. Users must investigate what vendors mean by analytics, and the value delivered by the analytics. As a customer, understanding how analytics solves your problem is your main objective when evaluating solutions.
For example, analytics that sift through mountains of data quickly (something that would not have been humanly possible), and provides valuable insights so better or quicker decision can be made, or action can be taken more quickly to keep a critical business service running, that kind of analytics delivers a lot of value.
Until vendors find a better way to define or communicate analytics, the challenge for IT customers is to ask the right questions, so you'll be able to evaluate one vendor's analytics against another's.
For starters, some initial questions are: What exactly does the analytics do? What problem is it solving? What information does it provide? How reliable is the analysis? How does it change how we do our jobs? How difficult/easy is it to use and implement? What benefits can I expect from using it?
Hopefully, this will provide a starting point so users can sort out the apples and oranges of analytics capabilities.
Audrey Rasmussen is a Partner and Principal Analyst at Ptak/Noel.