© 2019 SourceMedia. All rights reserved.

Weighing the pros and cons of real-time data monitoring

We’re in the middle of a data revolution. Thanks to the communicative potential of the internet, breakthroughs in data storage and a realization of the inherent value of data by influencers in many disciplines, companies everywhere are wondering how to take their data-related strategies to the next level.

Because data touches so many areas, there are many possibilities for advancement here, including better tech, more data overall and smarter applications of data within enterprises. But one transformation seems especially promising—and potentially risky at the same time: real-time analytics.

If you aren’t familiar with real-time analytics already, we encourage you to check out datapine’s real-time live dashboard examples. In traditional data analytics models, there’s a period of gathering data, where companies or researchers invest in accumulating as much data as necessary, followed by a period of analysis, where those numbers are manipulated, visualized and otherwise interpreted to lend insights to the reviewer.

Real-time analytics draws fresh data in at a constant rate, allowing data analysts to witness any changes as they unfold, or see snapshots of individual moments, rather than purely retrospective analyses.

real time data 10.jpg
An attendee demonstrates the Touch Bar on a new MacBook Pro laptop computer during an event at Apple Inc. headquarters in Cupertino, California, U.S., on Thursday, Oct. 27, 2016. Photographer: David Paul Morris/Bloomberg

There are many different approaches here, including on-demand vs. continuous real-time analytics, but for this article, we’ll treat real-time analytics as their own category.

The Advantages

There are some major benefits to this approach:

  • Better procedural understanding. Many business-related processes are currently understood on a phase-by-phase level, but real-time analytics have the potential to break those phases down into sub-phases. For example, let’s say you’re running a logistics company that tracks its shipments from production to a retail distributor. You might only track the package at a handful of stages along that journey, such as when it’s loaded into the truck, when it hits a certain checkpoint, and when it’s finally delivered. It’s hard to tell where things could have gone wrong with only three touch points. A real-time analytics system would allow you to track that package at all times throughout its journey, significantly improving the insights you’d gather along the way.
  • Instant snapshots. Real-time analytics also allow you to take moment-to-moment snapshots in time, potentially giving you a better, more realistic understanding of what’s happening in any given moment. For example, if you’ve built an app, you could use real-time analytics to see how your users are engaging with your app at 3:30 pm on a Wednesday, immediately after a big news event, rather than waiting to assemble the data until the end of the day.
  • Alerts and reactions. You can also set up alerts within your real-time analytics system to enable faster (and therefore more effective) reactions. For example, if you’re using real-time analytics to measure your website visitor data, you could set up an alert if your number of visitors drops below a certain figure, or if your site loading speed drops unexpectedly. It allows you to take action on potential problems as soon as they’re detectable.

The Disadvantages

So are there any disadvantages to real-time data analytics?

  • Cost. Depending on which system you use, real-time analytics dashboards could be more expensive to set up and manage than their traditional counterparts. However, these costs may be negligible to an enterprise with a sufficient analytics budget already.
  • Time. If you’re using continuous real-time data monitoring, you’ll need someone available to watch that data in real time. Ultimately, a real-time platform could result in increased time expenditures without a correlating increase in productivity or value.
  • Distraction. Getting stuck on real-time fluctuations can distract you from big-picture trends. For example, if you’re worried about declining traffic on your website throughout the day, your worries and efforts may prove futile if the month-long trend has your web traffic increasing. That’s why many types of analyses are recommended to be done month-over-month or even year-over-year.

Do You Need Real-Time Analytics?

So do you really “need” to have real-time analytics?

That depends on a few different factors. For one, you need to consider your industry. Some industries, such as marketing and advertising, logistics, and manufacturing, will have more potential applications for real-time analytics than others. Some industries are also adopting real-time analytics more frequently than others, forcing the competition to adopt similar strategies as a defensive measure.

In terms of initial costs, real-time analytics aren’t much more expensive than any comparable data analytics system (though they can be costly if you overuse those systems). Therefore, there isn’t a significant risk in making the upgrade, so long as you have a clear plan for when, where, and how to use real-time analytics.

But for most industries and applications, real-time analytics aren’t strictly necessary, and may even work against you. Real-time analytics are a marvelous and powerful tool, but only if you’re using them for the right reasons.

For reprint and licensing requests for this article, click here.