How To Gain More Powerful Insights From Big Data Analysis

Big data is a familiar term to everyone in the world of IT and it's expected to continue impacting everyone across all aspects of their lives.

In 2020, the world will generate 50 times the amount of data it did in 2011 and 75 times the number of information sources according to IDC. But data is only useful when anyone and everyone who needs to can access it. This is why traditional business intelligence tools are being superseded by easy-access software solutions that don't require initiation into some high priesthood of data science, or a PhD in statistics.

The rising tide of information means that every employee - not just those with "analyst" in their titles - has to be familiar with data analysis. Organisations that make better use of data to make decisions tend to be more successful, while those that don't are likely to fall behind.

The democratisation of data has emerged as a consequence of several trends, including the proliferation of devices and consumerisation of IT, and signs point to it becoming an ever more prevalent shift. We are moving to the pervasive use of data, through online and real-world tracking and the Internet of Things.

In a world where people are drowning in data – from information on the web, on spreadsheets, and in databases on tablets and other devices – people need a lifeline, and that lifeline is data analytics. A recent Economist Intelligence Unit survey showed that 60 per cent of CEOs globally now use data analysis to govern their decision making processes. The study underlines the sea change taking place across the board. Company data is no longer the exclusive preserve of the high-priests of IT – it is part of the CEOs' toolbox and represents a fundamental shift from governance by instinct to governance by data insight.

It's not just the C-suite that should be reaping benefits from this. Familiarity with data analysis has to become part of the basic skill set across businesses. Our own research found that companies that rate themselves substantially ahead of their peers in their use of data are three times more likely to rate themselves as substantially ahead in financial performance.

Unfortunately, most business analytics products are built to centralise and control data, not democratise it. As a result, the majority of companies are reliant on specialists just to answer basic questions. They stumble through Escher-like spreadsheets to work around inflexible business systems or they're being stonewalled by enterprise-wide business intelligence platforms that spend more time in development than actually helping anyone.

There's no power in that approach. The power lies in giving people the ability to think, act and deliver – and a self-service delivery means the IT department concentrates on its strategic role – not helping users work out how to generate reports. When a company empowers employees with self-service analysis tools, they are shown to be capable and respected. People start to drive their organisations forward in ways that senior management could never anticipate. The environment fosters their ingenuity and creativity.

For example, BNP Paribas is hunting opportunities to find new customers and develop new targeted marketing campaigns using a mapping tool. One team can pinpoint and visualise the number of prospects in a catchment area, and segment them by income, risk, and which (if any) financial services they already consume. Its tools visualise all of this data is seconds, allowing the team to pass that segmented target audience onto the sales department for follow-up.

Barclays uses dashboards to bring in data about the reasons people complain and who those people are – the insight gained through those visuals helps improve customer service. Being able to see this on a daily basis can help Barclays establish a root cause analysis of what those complaints are about. 

Today, we use more powerful computers and data than we know what to do with, but our own capacity to remember and pay attention is still just as limited as it was 1,000 years ago. We need to be given information in chunks of the right size, and they need to be connected to each other. Stories provide that connecting structure between facts. All data users should consider the principles of good storytelling as a way to gain impactful insights from data, and to present that information in the most compelling manner possible. 

Top tips for driving a data culture within your business

• Get buy-in and excitement - think of data analysis as a story, and use a narrative
• Find the story first - explore the data
• Write out the story to guide your audience through the journey
• Supplement hard data with qualitative data, and add emotion
• Be visual - use pictures, graphs and charts
• Make It easy for your audience - stick to a few key issues and how they relate to your audience
• Determine what you want people to do as a result - write your happy ending
• Encourage data uptake by demonstrating the benefits to the business and your colleagues' roles – data empowerment can make business heroes

Maxime Marboeuf is a data analyst at Tableau Software.