3 Crucial Steps Toward Becoming a Data-Driven Organization

In order to avoid the pitfalls that ultimately waste time and resources, it is important to understand what causes insurers implementing business intelligence (BI) technology to struggle on their way to achieving digitally driven decision making.

Even though insurance has always been a data-driven business, changes in input, structure, and quantity mean insurers continue to struggle to achieve data mastery (DM) on a daily basis. Why is this a difficult task? Data mastery, or the ability to use internal and external data to facilitate better decision-making with actionable insights, is a constantly moving target. This means DM investments are crucial to helping insurance organizations make more informed decisions and identify opportunities to reduce costs.

Implementing a business intelligence (BI) solution can provide a DM roadmap that aligns corporate goals and helps to achieve those goals across the functional areas within an organization. The power of BI to learn from the past, accurately portray the present, and, with analytics, predict the future, is simply too great to ignore. A growing number of experts believe this capability will increasingly be the difference between the winners and losers in the future. While pulling data together and looking randomly for pearls of wisdom may be successful, organizations focusing their efforts on business goals, such as acquiring or retaining customers or improving risk selection and pricing via advanced BI solutions, have been far more successful overall.

When the Oakland Athletics’ General Manager Billy Beane ditched established methods in favor of using performance statistics and analytics to build a winning baseball team, he was greeted with skepticism. Through positive and measurable business results, Beane eventually showed that the method works. He realized that within the league there were many general managers who didn’t understand the numbers and what they really meant. They relied on old methods of team building, which resulted in poor player valuation and team mismanagement. The same thing happens in all industries – including insurance.

Simply having a large data repository doesn’t mean you are actively involved in DM. Having the right tools is essential to parsing the data and extracting actionable intelligence from that ocean of data. The right BI solution provides insurers the tools needed to gain valuable insights from the information buried within vast amounts of data. The process requires three crucial steps:

1. Identifying the right data;

2. Getting and organizing that data; and

3. Cultivating a process and organization for gleaning insights from the information to take action. 

Outlined in three steps, it sounds easy, but the reality is often a painful, costly endeavor that falls short of original projections. In order to avoid the pitfalls that ultimately waste time and resources, it is important to take a closer look at what causes insurers to struggle.

Identify the Right Data

“These aren’t the droids you’re looking for.” – Obi-Wan Kenobi

Identifying the right data is a mix of basics – every insurer needs fundamental pieces of information for reporting and operations, as well as differentiating “secret sauce.” The basics are simple enough to identify and usually to acquire, but the secret sauce is more difficult and company-specific. Pinpointing the components in a company’s secret sauce is a process that must go hand-in-hand with company strategy and goals from the highest level down to the most task-oriented levels. An insurer’s secret sauce should resonate with the overall direction of the business and be punctuated by the actions that will be taken to get there with distinct, measurable key points in the process. Alone, together, or compared in various ways to other information, this data should be able to give you actionable insights.

Get the Right Data

“Make it so, Number One.” – Captain Picard

Perhaps no industry is more dependent on current, insightful data than the insurance industry. The data is maintained in great detail for low-level, granular facts, but can also be summarized to reveal patterns and trends over time. This allows insurers to see and understand information pertinent to all facets of the business: customers, agents, policies, claims and more. It brings a fresh perspective and alternative insights to questions being asked or questions soon-to-be asked. It finds the answers buried in the data and brings everything out for self-service consumption.

Within any insurer, there are many examples of using BI to enhance capabilities:

1)      Underwriting: Providing feedback on all relevant factors affecting performance of products enables underwriters to analyze risk and adjust coverage and pricing accordingly.

2)      Claims: Loss reserving trends and established metrics can be used to analyze the full claims lifecycle process to find bottlenecks and can then be extended to measure adjuster performance.

3)      Reinsurance: Provide greater leverage and more accurate risk characteristics during negotiations.

4)      Distribution: Proactively identify the best performing third-party organizations across programs, multiple lines of business, and regions.

5)      IT: Reduce the burden on IT in dealing with requests for detailed reports or data analysis by providing a self-service environment that allows users of all experiences to gain access to information without relying on high-cost technical skills.

BI empowers users by providing a complete business perspective which transcends traditional organizational boundaries. In correlating information from all divisions within an organization, BI reveals opportunities that may otherwise go unnoticed.

Achieving the Ultimate Goal: The Data-Driven Organization

“The fate of the world will now be decided.” – Gandalf

The ultimate goal is to improve decision-making at every level of an organization. In order to achieve that, the quality of the information upon which decisions are based must be improved. Technology and tools for core systems and BI have come a long way, but they can only improve decision-making if accompanied by a willingness to embrace the need for such insights.

Change is never easy, and inertia is a deceptively powerful force. Even after Billy Beane showed that the “Moneyball” approach could succeed in changing the way a baseball organization makes business decisions, he still faced challenges because others viewed his methods as a threat. Nevertheless, many realized that anyone who wasn’t adopting his method would become extinct.  The same principle applies to insurance. The hidden jewels of actionable insights are buried in your data waiting to be discovered. You just need the right data strategy, BI solutions and organizational support to start differentiating in the market.

Shailesh Mehrotra // As Cover-All Technologies' senior vice president of Product Management and Technology, reporting to the CEO. Shailesh oversees the development of Cover-All’s products including product strategy and technology innovation. His teams are responsible for delivering innovative products for insurance. Mehrotra joined Cover-All in 2010 as VP for the Business Intelligence division. Prior to Cover-All, Mehrotra spent over a decade at Ernst & Young where he was responsible for several enterprise-level global solutions. Earlier, he held several technology management positions Tata Consultancy Services. Mehrotra holds a master’s degree in computer science from IIT, Mumbai, and a bachelor’s degree in Computer Science from SGSITS, Indore.

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