The term "analytics" has become so overused that I'm not sure anyone really knows what it means anymore - or at the very least, it means a lot of different things to different people. Sometimes analytics gets blended in with "business analytics" which gets blended in with "business intelligence." What do all of these things mean? I realize just how meaningless these terms are when I try to explain to my parents what I do for a living. They gently remind me that the words I'm saying don't make any sense and that I need to explain in more granular terms. Good point - everyone should have parents that tell them these things. As "analytic professionals" we need to communicate and educate on what analytics are, how they add value, real examples of how they are used and how to implement them.
When we talk to organizations about their analytic goals, we need to create those common definitions to ensure that we're all speaking the same language. We also need to be cognizant that analytics aren't an end unto themselves. The conversation should always start with business strategies. Once you've identified specific strategies, you can begin to identify the information sources needed to support those strategies, the methodologies, technologies or tools necessary to deliver the insight, and ultimately the process of linking all of those things together. Call it information delivery, business intelligence, analytics, business analytics, predictive modeling, whatever, but don't get lost in the terminology - keep your eye on what’s important to the business and then begin to identify what you have the ability to influence through the strategic use of information.
As an example, one insurer I worked with brought their different lines of business to discuss "analytics." Each line of business was at a very different maturity level from an operational perspective (especially for newer lines where the company might be putting their toe in the water and not yet making significant investments in the business). For one line, analytics meant basic reporting, because they didn't have any mechanism to tell them anything about their business. For another, analytics meant continuing to make strategic investments in their statistical resources so they could continue grow their predictive modeling capabilities, and for another, further along the maturity model, it was how to embed predictive capabilities in operational systems.
This represents three very distinct "analytic" goals. Now, if this company hadn't begun to have this conversation, how would they know where they were supposed to make their enterprise analytic investments? Once there was a common understanding, or language, they could identify needs, capabilities and investments necessary to ensure the organization was marching down the same analytic path.