In a more recent view, Wired magazine observed that "data in the 21st century is like oil in the 18th century: an immensely untapped valuable asset. Like oil, for those who see data's fundamental value and learn to extract and use it, there will be huge rewards."

Critics of the "data is the new oil" analogy have pointed out that oil is finite, while data is renewable and more is created every day. But defining data as the new oil simply helps underline the emergence of data quality, management, and analysis as the next "really big thing." The real impetus and value are the potential insights we can derive from a vast and growing resource. If data truly is the next big thing, then companies need to think about a new business model to exploit it.

If we accept the concept that data is like oil, then a "data refinery" is the strategic operating model for companies with digital exposure. New sources of crude data are researched and provisioned to enable an enterprise to commercialize this resource. Raw data flows into the enterprise, including customer contributed proprietary data, purchased data, freely available data, and streaming data. The enterprise refines the raw data, creating valuable intellectual property (IP) through proprietary processes, subject matter expertise, analytics, software, and combinations of data sets.

The "refined" data is stored in databases appropriate to the type and scale of the data-just as oil products such as gasoline, heating fuel, and motor oil are stored in tanks. The refined data products can then be distributed to customers over the Internet as analytic insights or used to develop new products. All of this requires a full understanding of the legal, regulatory, and contractual restrictions surrounding the use of data.

From a management perspective, data governance is the broader term used to ensure that data stewardship is properly executed. The data steward should strive to make certain that data is a corporate asset and not just an operating unit (or local) asset. That means, where possible, every company needs to define or create data in a way that extends beyond its intended use and maximizes its value-creating potential without hindering future utility.

With that said, if a company wants to be competitive today, it must strive for something we at Verisk call the n+1 data set. If a company's data set has a certain number of elements (n), that set should be stretched to include one more. Elements must continually be added, advancing toward the next layer and adding richness to its analysis. This process requires investment in data resources, analytics, technology, and in people. But the return on investment can mean thriving, rather than failing or merely surviving. That's true for all industries, but especially so in data-driven industries such as insurance and healthcare.

The truth behind n+1 is almost self-evident. For homeowners insurance, for example, insurers are supplementing or replacing physical inspections of properties with technologies such as digital photography and aerial imagery. These cutting-edge technologies reduce the cost of evaluating the risks associated with a property before issuing an insurance policy. Therefore, the future of underwriting doesn't necessarily require a pair of human eyes to be on-site. Ultrahigh-resolution aerial images and digital photography can provide under writing insights with verified image-based data.

Other lines of business, functions, and industries can apply such data-enhancing technologies, as well. For example, most new vehicles contain telematics devices that transmit vehicle-generated data, including speeds, locations, and risky maneuvers, to insurance companies. Insurers use the data to refine their pricing structures, reward safe driving, modify risky behavior, identify fraudulent applications or claims activity, and dispatch emergency assistance or adjusters to accident locations. For older vehicle models, insurers can install telematics devices under their dashboards. It's a case of everybody winning.

That is an example of n+1.

In the healthcare industry, some hospitals are equipping patient wristbands with devices that can transmit blood pressure and heartbeat readings. Now, imagine something as innocuous as a henna tattoo that can transmit the wearer's bio-readings (blood pressure, heartbeat, enzyme and hormone levels, temperature, and so on) to machines that can interpret the information and identify warning signs of high stress or even a heart attack.

That is also a prime example of n+1.

With data and technologies seeming to flow at faster rates, businesses will need to put together plans to redirect the river of information towards a company's best use-and before the river becomes an overflow.