The need for speed: A look at real-time analytics

You may feel like the world is moving faster than ever. If so, then you can take solace in two facts:

You're not alone in feeling this way.
You're right. It is.

Celebrating the 25-year anniversary of the Web, The Economist ran a piece examining the increasingly rapid adoption of new technologies. From it:

It took only seven years from the first web pages in 1991 for the web to be used by a quarter of the American population. That compares with 46 years for electricity, 35 years for the phone and 26 years for television. The web, just 25 years old, is still at the start of its life.

Or, visually speaking:

It's hard to argue that business and life haven't speeded up considerably over the past ten years. Offices redolent of Mad Men seem like centuries ago. For instance, up until fairly recently, the notion of a flash sale didn't exist. Ditto for viral videos and trending tweets. What's more, all signs point towards these trends intensifying for the foreseeable future. Brass tacks: things won't be slowing down anytime soon.

This begs the question: With regard to analytics, how fast is fast enough?

A simple question. A complicated answer.

Of course, the answer is neither simple nor is it universal. At the risk of sounding like a stereotypical consultant, it depends. A retailer may possess an acute precisely need to track inventory during Black Friday. That same need doesn't necessarily exist during a slow Saturday in July.

As you're waiting in your doctor's office, you might think that relatively stable industries like healthcare don't require real-time analytics—and you'd be wrong. Big Data can prevent the spread of infectious diseases and even the flu.

I'm a big believer in the axiom: It's better to have it and not need it than need it and not have it. Translation: Being able to turn up the speed dial can only help. For instance, for a long time now, Cisco has been able to close its books at the end of every business day, no small feat for such a large enterprise. Does the company always do this? Of course not, but the ability to easily do this is absolutely invaluable for diagnosing problems, assessing profitability and generally answering business questions before month-, quarter- and year-end processing.

Simon says: Ask more questions to determine your need for speed

In this way, the speed question resembles the "future of data" question. I don't know what it will entail, but it will be more. Put differently, I can't give you a simple, all-encompassing answer. No one can. Instead, let me pose some queries that will help you address your organization's need for speed:

How fast do your employees act on currently act on its existing numbers? Real-time analytics don't mean a hill of beans if an organization's employees never use data to make decisions.
Are there perils to acting too fast? In the race for speed, are we losing time to reflect on what the data isn't telling us?
Is your organization's culture tolerant of failure? If we act faster, then not only are we able to benefit in key areas, but we are concurrently likely to make more mistakes.