Today, really successful companies understand where their customers are, what they are doing and where they are going. They know what’s happening as it’s happening and they allow that information to guide their strategy and inform their decision-making.

Companies that won’t embrace this smart revolution will be left behind.

Big data offers business an unparalleled opportunity to extract insight into the behaviour of their customers, which can transform business results. But just because we can measure, monitor and access everything doesn’t mean we should.

Business leaders need to understand that lack of data is not the issue. Most businesses have more than enough data to use constructively; they just don’t know how to use it. The reality is that most businesses are already data rich but insight poor.

>See also: Is big data dead? The rise of smart data

As in all revolutions, there will be winners and losers. But it’s not as simple as saying that those with the largest amount of data will win.

Smart business is a solution that encourages businesses to step back from the hype.

Don’t start with the data. If you do, you will find yourself lost in an impossible rabbit warren of options. Start with strategy. Get really clear about what you need to know and why and link that back to your strategic and tactical objectives. By starting with strategy, and not data, you will immediately focus on your really important data requirements instead of being overwhelmed by what’s possible.

In order to reap the benefits of big data, businesses don’t have to collect everything and produce the biggest, most complex database in the world. Their aim should actually be the opposite – to get really clear about what data they need and build the smallest, most straightforward database in the world.

A ‘smart strategy’ – as outlined in the book Big Data: Using Smart Big Data Analytics and Metrics To Make Better Decisions and Improve Performance – can help business leaders step back and ask what their strategic information needs are.

For example, if the strategy is to increase the customer base, smart questions will include : who are our customers? What are the demographics of our most valuable customers? What is the lifetime of our customers?

Organisations’ data requirements, cost and stress levels are massively reduced when they move from ‘collect everything just in case’ to ‘collect and measure x and y to answer question z’.

For example, a small fashion retail company that had had no data other than their traditional sales data wanted to increase sales but had no smart data to draw on.

It worked out the smart questions to which it needed answers, such as how many people passed its shops, how many stop to look in the window and for how long, how many of them come into the shop, and how many then buy.

The company installed a device in shop windows to track mobile signals to measure how many people were stopping and how many of those were coming in. By combining this data with transaction data, it was able to measure conversion ratio and test window displays and offers to see which ones increased conversion rates most effectively.

>See also: Big data: not a magic pill, but an antidote

Big data and analytics are paving the way to greater customer understanding and real-time monitoring of what’s actually happening in business, but unless the results are presented to the right people in a meaningful way then the size of the data sets or the sophistication of the analytics tools won’t matter and the results will not inform decision-making or improve performance.

Software that promises to turn the endless streams of data pouring out of businesses into sexy one-page info-graphics are the latest technological hotspot. Gartner have estimated there will be a 30% compound annual growth rate in data discovery tools this year.

The problem is that these self-service business intelligence and data discovery solutions belong with the data scientists, not the business executives who need the data. There needs to be a two-way collaboration between the people creating the results and people who need the results to make decisions.

In business, especially in large companies, there needs to be uniformity in the way the data is presented. Take Proctor and Gamble – a global business with hundreds of brands that has chosen to institutionalise data visualisation as a primary tool of management.

Working with a visual analytics software vendor, P & G put visual displays of key information on more than 50,000 desktops that now provide access to a ‘Decision Cockpit’.

P & G have initiated a set of seven ‘business sufficiency models’ that specify what information is used to address particular problem domains. For example, if a P & G executive is focused on supply chain issues, the sufficiency models specify the key variables, how they should be displayed visually and sometimes even the relationships between the variables and forecasts based on the relationships.

>See also: Get smart: how smart machines are bringing us closer together

The uniformity means that everyone is on the same page. Executives from any division or any brand, in any country, can quickly and easily interpret the data they are given. They spend much less time trying to understand the data and more time putting it to use.

It’s practical for large companies to have data analysts and visualisation experts to bridge the gap between the data and the decision makers; for smaller companies, it may not be. But if you want to be a smart business, you must develop these competencies in-house or outsource to a trusted provider.

There’s absolutely no point identifying metrics and data that can help answer smart questions and applying the analytics to come up with those answers, if the answers are then buried in a 50-page report that no one reads or understand. Finding a way to report the results quickly, clearly and engagingly is crucial to any smart business.

Sourced from Bernard Marr, author and founder of the Advanced Performance Institute