There’s a curious mentality associated with application analytics. The expectation is that once someone has data in hand, they might turn it in to a report — a well-organized view of the information with a few graphs or pie charts. Perhaps you summarize the stats, throw in an insightful paragraphs and . . . that’s it?
But analytics are not stagnant — especially in something as continuously evolving as Mobile Application Management. A report doesn’t necessarily represent something definitive. It’s a snapshot, a peek at usage, performance, issues. That’s the drawback of thinking of analytics in isolation — and it’s time to change that way of thinking. Let’s expect more from analytics. They shouldn’t simply exist; they should accomplish. We need to start immediately translating analytics in to something actionable. We need to change the “view” in to a “do”.
Analytics shouldn’t be seen as a review, a backward glance at how an app has performed to date. A more powerful perspective is of analytics as a predictor, in terms of impact and influence. They can inform resolution of open issues. They can drive policy change within infrastructure. Sure, this sounds like common sense, but in my experience the time between getting a data “drop-off” and then doing something with it can be so long as to render the info ineffectual. The reflex needs to be immediate.
And why the hesitation? The industry has addressed device security. We have scores of MDM vendors as a result. What’s next? For me, the answer is this more dynamic, immediate analytical approach. It will drive truly dynamic policy generation, but it can’t languish. There’s a time-based correlation between that information and smart policy management.
Our objective? We want to provide greater control of apps at an operational level, not just turn an app on or off. We want to provide deeper insight and control at the functional and data element level. Use of an app is a start, but there’s much more advantage to knowing what people are doing inside an app, what data elements they are accessing, as well as where, when and how they are accessing them?
That is the true potential power of good analytics. Having control at a device level is understood, but now it’s possible to shape that capability at a data element level, a function level, or at the app itself based on a user profile. Equipped with that depth of insight, imagine the workforce management ability, the user behavior comprehension. That’s when we move beyond colorful charts and short-term summaries of what happened yesterday or last week. That’s when we know what’s happening now — the key to understanding and optimizing an app’s value.
