On the Confluence of Business Information and Technology: The Best Is Yet to Come

By Scott G. Stephenson

Ernest Hemingway once said that the laws of prose writing are as immutable as those of flight, of mathematics, of physics. The passage of time may require updating Mr. Hemingway’s list with a few laws of business and technology. Taken together and without exaggeration, these three laws might truly suggest the best of business agility is yet to come — in large part due to the confluence of information, technology, and actionable insight. Here’s how:

Immutable Law of Business #1

The volume of data available today is greater than it ever was — and less than it’s going to be.

If a company wants to be competitive today, it must strive for what we at Verisk call the n+1 data set. If a company’s data set has a certain number of elements — n — it must work to include one more. It must continually add elements, advancing toward the next layer, adding richness to its analysis. It requires investment — in data resources, in analytics, in technology, in people. But the return on investment is to thrive, rather than survive or fail. That’s true for all industries but especially so in data-driven industries such as insurance, healthcare, and the retail supply chain, among others.

The truth behind n+1 is almost self-evident. In homeowners insurance, carriers are supplementing or replacing physical inspections of a property with technologies such as digital photography and aerial imagery, reducing the cost of evaluating the risks associated with a property before issuing an insurance policy. 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 underwriting insight with verified image-based data.

Other lines of business, functions, and industries can apply such data-enhancing technologies, too. For example, most new vehicles contain telematics devices that can transmit vehicle-generated data, including speeds, locations, and risky maneuvers, to their 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, insureds can install telematics devices under their dashboards. Everybody wins.

That’s n+1.

In 2011, Moody’s Investors Service noted that usage-based insurance (UBI) products are “credit positive” for insurers, giving pioneers an advantage over competitors that may become victims of adverse selection. Launching a UBI pilot allows an organization to limit its investment; however, insurers must possess the expertise and entrepreneurial spirit to fully use these new n+1 data sources. Industry organizations may play a role in providing technological assistance, decision support, and data management services that help insurers benefit from economies of scale.

Immutable law of business #1

The volume of data available today is greater than it ever was — and less than it’s going to be.

In the healthcare industry, some hospitals are equipping patient wristbands with devices that can transmit blood pressure and heartbeat readings. Now, imagine devices as innocuous as a henna tattoo 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 a heart attack or overexertion. 

That’s also n+1.

So, too, is a comprehensive supply chain risk management strategy — and the incorporation of an array of predictive analytic tools to measure and manage risk. Such a strategy often extends beyond the supply chain itself to encompass all major operations of the organization. In fact, modern predictive analytics is fast becoming a tool to recognize key trends, patterns, and potential disruptions within supply chains and a means to protect the enterprise’s most valuable assets while also creating sophisticated risk mitigation models.

Immutable law of business #2

The scale of collaboration available today is greater than it ever was — and less than it’s going to be.

The devastation from major catastrophic events can disrupt supply chains locally and worldwide, in turn causing significant repercussions in the global economy. Organizations that employ analytics and innovative weather intelligence can mitigate the costly effects of such events. Analytics can help manage environmental health and safety (EH&S) regulatory compliance and sustainability across supply chains and product life cycles. EH&S analytic tools present a comprehensive view of relevant trends, and the resulting business intelligence enables more effective management of product stewardship and workplace safety regulatory requirements. Predictive algorithms can alert supply chain managers to major issues in operations and processes. Companies can also apply predictive analytics to historical cargo theft data to plan the safest routes for the transport of goods.

n+1 again.

Immutable Law of Business #2

The scale of collaboration available today is greater than it ever was — and less than it’s going to be.

Last year, the National Association of Insurance Commissioners’ Center for Insurance Policy and Research wrote:

“The use of social media in the business of insurance is becoming widespread. Insurance companies and producers use social media for a variety of purposes, including increasing visibility, developing relationships, and building trust. Insurance companies are not using social media to overtly sell their products and services, but to provide customer service in order to build and maintain relationships with consumers. The goal of developing these relationships is the creation of market presence and product branding, which, in turn should generate new customers. Most state insurance regulators have observed the increasing use of social media within the insurance marketplace and are actively addressing social media use and issues via market conduct examinations; others have addressed complaints regarding the misuse of social media through the consumer complaint process.”

The main implication of interactive technology is that people can communicate with counterparts on a level not possible 20 years ago. The amount of data available and the ease and speed of its use are revolutionary and change the nature of the work we do. That allows for greater collaboration and greater innovation.

It’s not profound to say that in any industry the reward goes to the companies that find the way to be most innovative. On the other hand, what’s interesting is how to do that.

In 1986, Eric von Hippel, an economist and professor at the MIT Sloan School of Management, developed the term “lead user.” According to his definition, lead users identify needs that will be general in a marketplace — but experience those needs months or years before the bulk of that marketplace encounters them. Equally important, lead users are positioned to benefit significantly by obtaining a solution to those needs. Because lead users innovate, they serve as a weather vane for companies, indicating which way the wind is blowing.

Immutable law of business #3

The value of unique data sets sourced from specific vertical markets, complemented by thoughtfully chosen data from outside those markets, results in predictive power greater than it ever was — and less than it’s going to be.

Combine such customers with greater collaborative tools, vast data resources, and sophisticated analytics, and over a period of years, a business may produce profitable new products and services. Along with that comes the consistently improved performance necessary to generate return on the initial investment, not to mention databases large enough to support even more predictive modeling and analytics. Which brings us to…

Immutable Law of Business #3

The value of unique data sets sourced from specific vertical markets, complemented by thoughtfully chosen data from outside those markets, results in predictive power greater than it ever was — and less than it’s going to be.

In an article (“Is Big Data a Big Economic Dud?”) from the August 17, 2013, edition of The New York Times online, James Glanz makes a provocative statement about the economic utility of big data:

“…some economists [are] questioning whether Big Data will ever have the impact of the first Internet wave, let alone the industrial revolutions of past centuries. One theory holds that the Big Data industry is thriving more by cannibalizing existing businesses in the competition for customers than by creating fundamentally new opportunities.”

Perhaps surprisingly for someone who makes his living in the data/analytics space, I find myself in (partial) agreement with Mr. Glanz’s statement. There is so much data available, with more to come. And much of it is streaming toward us not because we demand it or know what to do with it, but simply because it is increasingly easy to make it available in digital form and in quantity.

However, the author himself puts forward an important caveat in his piece:

“…far more useful is specialized data in the hands of analysts with a deep understanding of specific industries.”

This, I think, is key. Big data analyzed with a vertical view remains a potent source of decision support. In fact, in the face of information overload, the truly unique data sets stand out even more sharply because analytic methods permit more meaning to be teased from them.

The value of large data sets thoughtfully assembled from within dynamic markets will prove their value, as they always have.

A very good place to be, it seems to me, is in a world that combines n+1 data aggregation with innovative technology-driven collaboration to arrive at vertically driven big data analytics and decision support.

In sum, the rewards are greater than they ever were — and less than they’re going to be. And yes, that said, the best is yet to come.

Scott G. Stephenson is president and chief executive officer of Verisk Analytics.