Peter Drucker famously said, “If you can’t measure it, you can’t manage it.” No industry has benefited from the adoption of this philosophy as much as the analytics industry. But analytics as we know it is about to change completely — and for the better.

As agency co-founders, my partner and I fully believed in this adage and have always looked for the informational advantage to give our clients the edge. Like many others, we quickly realized that current analytics tools are often better at causing paralysis than analysis. The current response to more data availability appears to be flooding an end user with as much data as technologically possible. Yet new tools that educate the user about next steps based on that data are lacking.

Although you wouldn’t know it from the current analytics offerings, we’re at the point in many industries where there is enough accessible data to finally do just that: intake data, synthesize it, apply subject matter knowledge and output a next step to ensure the user makes optimal choices. We’re happy to lead that charge in the social media marketing realm, but for other industries, here are four things your analytics tools must do to survive the coming big data wave:

1. Close the loop with the data. As big data becomes available for your industry, don’t take the easy road and simply give users an endless data playpen. Your tool should make them more efficient, not give them an endless rabbits hole in which to get lost. Take on the big problems and find ways to use that data to provide actionable next steps and immediately valuable improvements to their work.
2. Offer action-based interfaces. The majority of business people are not overly fluent in statistics. Their jobs often require varied and specific non-math skill sets — so your analytics tool shouldn’t require them to learn yet another skill. Remove the burden of statistical know-how from the end user by providing action-based interfaces (“Today, do this” “For tomorrow, make these” etc.). Make these changes and see how elated your clients are. The user looks better to his boss and his boss sees better and more efficient output from the user.
3. Provide backup. The only thing more aggravating than an analytics tool that increases your workload is one that provides a magical, unsupported recommendation. “Post an article at 5 p.m. on Tuesdays for maximum success” or “Change the color palette to include more orange and yellow” are helpful recommendations … if they’re right. When making a next-gen analytics tool, make sure users can check your logic and understand the reasoning. It helps both in user compliance and client confidence.
4. Focus on in-time impact. The majority of current tools are phenomenal at reporting what happened last week or last month. Very few focus on what’s happening now and more importantly, on changing what’s happening now. Furthermore, the few that understand the importance of this are going about solving the problem in the wrong ways. They think that by filling their graphs with data more quickly, the user will suddenly know how to change the game as it’s being played.The real impact will come when the creators of these tools stop focusing on how quickly they can get the data to the user, and instead focus on what form the user needs that data in in order to react quickly and accurately. Optimal analytics tools of the future will present the data in an actionable format, rather than presenting the data in a more data-heavy format a few seconds earlier.

The data is out there, and it’s only becoming more accessible. Meanwhile, the analytics market is finally beginning to deliver on its promise to make complicated aspects of business vastly easier to manage. I believe the tools that embrace these changes will become the market leaders over the coming years.

If you’re using analytics tools in your business, demand more. If you offer an analytics tool, adapt it. The new wave is coming quickly.