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Insurers Demand Analytics on the Go

Across the insurance industry, carriers, agents, brokers, risk advisors, and consumers have come to expect timely and secure access to vital information on the go.   Forrester reports that 48 percent of global information workers use a smartphone for work, and 21 percent have bought the device themselves demonstrating that they will spend their own money to work efficiently on the go.  Furthermore, many studies show that Millennials—the younger generation of insurance industry customers and employees—demand mobile access to products, services, and jobs that allow them to shop and work where and when they want. 

These expectations have resulted in an explosive growth in demand across the insurance industry for complex and varied data analytics solutions accessible via mobile devices.  For example, claims managers want mobile access to vendor and partner performance information to focus on problem areas that require attention while in the field.   Regional and distribution managers want to receive alerts regarding channel performance via high-touch mobile dashboards.

Sales and distribution managers want to analyze broker and underwriter performance not only on price, but also on the critical issues of contract wordings and claims performance.  They want to identify areas of improvement in product design, customer management, and to recognize cross-and up-sell opportunities, all via any device, anytime, anywhere.  

The growing demand for mobile analytics is coming from customers and from employees at all levels of the corporation.  The expanding list of desired analytics capabilities is extensive, including personal lines policy analysis, portfolio analysis, claims management, risk management appraisal, agent productivity, product distribution and claims by geographic areas, and customer behavioral patterns. 

To respond to this increasing demand for secure, mobile analytics, many corporations in the industry are investing in tools, people, and process improvements that will help them gain greater business value from the volume and variety of data available to them.  If done right, these investments will result in capabilities and innovations that can help improve productivity, enhance customer loyalty and retention, increase sales and profits, and reduce risks. 

Doing it right requires four critical components:  1) an enterprise analytics strategy and roadmap to deliver only impactful analytics that provide high business value; 2) an enterprise mobile strategy designed for “mobile first” and delivers analytics on any device; 3) a predict, prevent, and persist analytics security strategy that reduces breaches and vulnerabilities; and 4) an agile analytics development methodology that continuously delivers and adjusts quickly to changing needs.

The enterprise analytics strategy and roadmap targets and funds only those analytics investments or initiatives that contribute directly to the achievement of business objectives.  The best way to align analytics to business objectives is to frame questions that, if answered with the right data, accelerate the achievement of desired outcomes. 

The enterprise mobile strategy designs analytics for mobile first, making the enterprise analytics accessible via any device (e.g., web, desktop, tablet, smartphone) while personalizing and enhancing the user experience.  It stores little information on the device, making secure, mobile access to analytics cost effective and feasible—even using personal smartphones in bring-your-own-device scenarios.  It enables location-aware and personalized features on the device while protecting the enterprise data in accordance with established policies and rules at the user level instead of the device level.

The predict, prevent, and persist security strategy for mobile analytics is focused around the concept of precognitive capabilities.  This holistic approach uses both artificially intelligent technologies and top industry cyber professionals, with a laser focus on predicting, preventing, and persisting against cyber incidents targeting the data and analytics.

Agile development uses a continuous delivery model to rapidly deploy analytics capabilities in small iterations, providing the opportunity to pivot and adapt quickly as needs change and evolve.

In summary, to secure and retain an increasingly global and mobile workforce and customer base, the insurance industry must accelerate the pace of delivering high value, secure mobile analytics capabilities.  Four critical components are essential to success:  an enterprise analytics strategy and roadmap that focuses on business value; an enterprise mobile strategy that accommodates any device; a predict, prevent, and persist security strategy that reduces vulnerabilities; and agile development to deliver functionality faster while reducing risk and cost to meet changing needs.

Cynthia (Cindy) Walker is the vice president of Salient’s Data Analytics Center of Excellence at Salient Federal Solutions. She leads the development and implementation of Salient’s data analytics strategy to include predictive analytics, agile business intelligence, and big data solutions for Salient’s clients.

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