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Analytics Magazine

Executive Edge: Keys to unlocking innovation in organizations

How to take a concept through infancy into reality and then on to profitable innovation.

Scott Stepheson data analytics innovation organizationsBy Scott G. Stephenson

“Drive thy business or it will drive thee.”

Benjamin Franklin offered this sage advice in the 18th century, but he left one key question unanswered: How? How do you successfully drive a business? More specifically, how do you develop the business strategy drivers that incite a business to grow and thrive?

The 21st-century solution has proven to be data and analytics – from which emerge ideas large and small that can be the springboard to success. That solution begs yet another question: Where does an idea begin? And how can a concept be nursed through a promising infancy into reality and then guided to adulthood as a profitable innovation?

As a leading provider of data and analytics, we at Verisk Analytics spend our time developing answer keys to such questions – keys that unlock innovation within an organization.

The C-suite Vision

Lasting innovations often take root from evolutions in thinking. Data analytics is not a program or bolt-on accessory for business operations; it’s a strategy that should be embraced as sinew and fiber through the body of an organization. Instead of an afterthought, analytics must stand at the forefront of business strategy and be embraced throughout the organization – and not just by a data analytic “elite.” A business so tooled for the 21st century will seamlessly use data from within and outside the enterprise to generate new and unique insights.

To realize this vision, corporate leadership should ask: Are line managers thinking, behaving and sounding more like data analysts? And are data scientists and data engineers sounding more like line managers?

Ideally, both the business mindset and the data analytic mindset should reside between the ears of the same individual. But even short of the ideal, the goal is to assimilate the notion of using data to create meaningful information and not merely to warehouse it.

Companies need – and can achieve – continuous, agile improvements propelled by the skillful use of data analytics. If C-suite executives can harness the power and fluidity of data analytic methods, they should insist that projects deliver results within nine months. A monolithic plan or “Manhattan Project” isn’t necessary to derive substantial benefits.

Looking ahead, risk decisions will become more targeted and in real time with the advent of remote imagery, textual analyses, connected homes and the Internet of Things. Analysts estimate that current North American smart-home penetration may reach 25 percent to 30 percent by 2020. What this all means is that new technology is providing us with different kinds of data points, in greater volumes and with faster speed. That information will enhance analytic models to improve risk selection and assessment.

The Choice to Be Innovative

Two things about innovation are true: It’s sometimes expensive, and it’s never without risk. That’s the trade-off. And because of the trade-off, a company has to make a conscious decision to become a leader in innovation.

That said, if you look across any industry in the world with a technological basis, the reward for being innovative, and the penalty for not, are both greater than they ever were. In almost any industry, the differential in performance based on innovation has spread – it’s bigger than it used to be.

In the pursuit of innovation, businesses first need to determine what innovation means for them. Will the innovation address process or product, service, pricing or any number of value propositions? How deeply entrenched will innovation be in the organization’s thought processes? How much will the organization commit? How will the business demonstrate an innovative process or product as one of its distinguishing characteristics as it goes to market?

The next choice is how to sequence the innovations. There’s no single correct path. What needs to be done first or third may be based on what’s important to the customer or simply what appears to be the logical progression – that is, what needs to be built first, which is then built on and built on again.
For every company, the sequence will be different. And that’s what makes innovation interesting. Those are the decisions we make at Verisk every day.

Data’s Competitive Edge

Today, to be competitive, companies must strive for something Verisk has dubbed “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 the analysis.

Although this process requires investment in data resources, analytics, technology and people, the return on investment can mean thriving, rather than merely surviving or even failing. While it’s true for all industries, it’s especially relevant in data-driven industries such as insurance, energy and financial services.

Let’s consider two examples of how to apply n+1:

Example 1: In the traditional approach, fraud investigators start with single-suspect data points, such as a name or address. Then they build a network with the associated data. However, a newer, more proactive approach scans data sets to detect fraudulent networks, uses advanced analytics to identify network attributes, and then scores and prioritizes those networks based on their fraud potential. Finally, when we overlay data from social media or data derived from unstructured data, such as mining the text of claims adjusters’ notes, and then apply the new data-enhanced analytics, we have a more comprehensive toolbox to use in fighting fraud.

Example 2: Relentless pressure to lower coal consumption will intensify competition among producers for the remaining coal market. Some producers will meet this challenge using a conservative approach and focus on mining coal, which is what they do best. As market opportunities fade, only low-cost suppliers with access to prime-quality coal and superior market knowledge will succeed. Ultimately, it will become a survival-of-the-fittest contest. However, diversification is another strategy, and that would rely on the latest data and analytics.

Diversification for coal producers is a “stretch” strategy aimed at participating in a wider, non-coal energy market that’s growing, not declining. So again, here we clearly see the value of the n+1 mindset.
At Verisk, the seed of innovation began with a question that prompted more questions and created a company culture that finds solutions. As Ben Franklin also once said, “An investment in knowledge always pays the best interest.”

Scott G. Stephenson is chairman and chief executive officer of Verisk Analytics. Verisk’s mission is to help customers understand and manage the risks they face every day. On Oct. 7, 2009, Verisk Analytics debuted on the NASDAQ Global Select Market as the largest domestic IPO of the year. Four decades of continuous innovation were recognized in 2015 and 2016 when Verisk Analytics was named to the Forbes list of the World’s Most Innovative Companies.

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