Modern businesses may understand the importance of utilizing big data, but very few have developed the true capability to think and act differently. What’s certain is that some industries—and some specific firms within those industries—capture more value from big data than others. Here’s a look at how some firms are taking the lead in utilizing big data, and how, as an executive, you can take a more strategic approach to information and insight.
Digital transformation has seen data’s role shift from providing information on how firms can cut costs to helping them develop new insights and business models. Think about the rise of start-ups like Uber and Airbnb, which have used information to disrupt established sectors and develop a competitive advantage.
Outside the technology sector, leading retail firms have run loyalty card schemes for many years—Tesco, for example, launched its loyalty card scheme in 1994. Major airlines also have a long history of using data to help improve brand loyalty and customer experience.
The game-changing insight in these fast-moving firms places pressure on slower-moving incumbents, and the fate of your business could rely on its ability to use data and digital tools effectively. Research shows a company’s life cycle is being compressed dramatically; companies lasted an average of 67 years in the 1920s, according to consultant Innosight, and by 2026, the average will be 14 years.
Yet the rise of data-savvy start-ups doesn’t have to mean a death knell for your business. Established firms have already gained a head start. Microsoft bought LinkedIn to leverage its human asset data. GE, meanwhile, is viewed as a pioneer in the Industrial Internet of Things. And household names like Facebook, Google, and Amazon have built billion-dollar businesses through their innovative use of data and digital tools.
Organizations must make their data strategy a priority, but it’s worth noting that some leaders will find it easier than others to get traction for their big data plans. Certain sectors—traditional industries like logistics and construction—have been slower to exploit the information they hold.
Data security is another consideration. Public sector organizations hold huge amounts of information, but much of the data is restricted. These restrictions can prevent the armed forces, for example, from manipulating information and finding new ways to make the best use of resources, such as troop and equipment maneuvers. Healthcare organizations also create significant pools of data—but, again, there are significant constraints on the use of personal data. Data must be encrypted and anonymized before higher-level analytics can be undertaken. In short, utilizing big data is always going to be a work in progress.
What is clear is that the creative use of data is helping organizations overcome restrictions to hone and change their business models. While data-led transformation is often associated with fast-moving start-ups, it’s also creating new opportunities for established firms. Such businesses are using data to rewrite sector boundaries and to break into new territories.
Consider ING’s commercial platform, which stretches beyond traditional banking services to a digital loyalty program and crowdfunding. Swedish financial tech company Klarna, on the other hand, expanded beyond online payments, acquired a banking license, and became one of Europe’s largest banks with 60 million active customers. Outside of the finance sector, the Airbus A380 is a connected aircraft that includes thousands of sensors that capture operation details for manufacturing and engineering teams on the ground. Telecommunication firms Telstra and Telus, meanwhile, are using data to improve healthcare management. And Ford, best known for automobiles, is exploring mobility and the fast-developing area of smart cities.
Identifying strong use cases is the starting point for a more nuanced approach to big data. Your business probably generates thousands of ideas, and you need a process that helps your organization put the best concepts into production.
The key is prioritization. Your business should focus on the projects that are likely to be easier to execute, yet also produce big business value. With priorities set in stone, your team can start to think about time lines and help the rest of the business make the most of big data tools and capabilities.
Each priority must then be linked to the broader 5-year or even 10-year strategic vision, and every big data project should help the organization overcome simple business problems as you move toward the long-term goals. Remember that these goals are likely to flex as business requirements change. So, while big strategic aims set a vision, organizations will also need to update and evaluate their targets on a quarterly basis. Such flexibility and evaluation means your company must develop an agile approach to data insight.
Change, in short, will be the new constant. Think of automotive manufacturing as an example. Big firms in this sector face numerous competitive pressures during the next decade, such as the rise of self-driving cars, new players with new business models, and long-standing concerns related to environmental sustainability.
The capital of dominant players in the automotive sector is often locked into established ways of working and traditional production-line methods. Smart businesses, like Tesla, are disrupting the status quo by using innovation and a focus on energy to generate new, exciting products. Executives at traditional auto manufacturers must compete, utilizing big data technology to generate insights from the information they collect. Being first to market with an innovative vehicle concept will help established players remain competitive.
At the end of the day, data is creating new opportunities in traditional industries. Big data maturity must be measured not only for internal use cases but also in terms of how equipped firms are to compete in an economy that is becoming increasingly sector-agnostic and operating without true borders.
Assess your business in comparison to competitors so you can create a big data strategy that helps you stay ahead.