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3 Ways Big Data Analytics is Driving Growth and Innovation in Insurance

Posted on September 06, 2016 by Guy Weismantel in Digital Insurer

vertafore big data analytics process predictive dashboard

Big data analytics growth is on the mind of Fortune 1000 firms who want to outpace competitors and improve revenue. The Big Data Executive Survey 2016 by management consulting firm NewVantage Partners found staggering growth in big data use in just the past four years. Don’t feel like reading the report I linked to? Here are a few of the stats that had an impact on me:

More than 60% of organizations have big data in production, up from 5% in 2012.

In 2012, 24% of organizations expected to invest more than $10 million in big data – In 2017, 63%.

If you’re looking for an indicator of importance: 70% of organizations say big data is of critical importance, up from 21% in 2012.

The writing is on the wall, and the trends in data are there to support it. If you're not investing in big data analytics yet, you’re a step behind your competitors.

Let’s get you brought up to speed.

big data analytics vertafore performance predictive process reporting dashboards

According to a Forrester research study, there are three top analytics categories and features that successful companies credit with helping create growth and drive innovation: performance analytics, predictive analytics and process analytics.

Diverse industries use these different types of analytics to improve their products and boost customer satisfaction. The lessons learned are important and applicable to the future and growth of the insurance industry. Here's a look at how these different types of analytics are shaping consumerism, healthcare, and the economy worldwide.

Performance Analytics Makes Your Smartphone a Personal Shopper

Retailers are improving the in-store shopping experience for customers to bring them out from behind their laptops and back into actual stores with the use of beacons, or Bluetooth-enabled devices that communicate with a shopper's smartphone. 

Beacons enhance the in-store shopping experience by sending shoppers media such as ads, coupons and product information as they shop. They can direct a customer to their desired aisle and reward loyal customers as soon as they enter or leave a store. By activating their phone's location services while they shop, customers find exactly what they're looking for and discover new products related to their interests.

Beacons have been embraced by some of the biggest names in retail, such as Macy's, CVS Health, Target and Rite Aid. Compared to deals such as coupons that are emailed, the highly relevant and targeted messages that are delivered to shoppers as they're shopping work exponentially better. 

Technology news site ZDNet reports that a “geofenced” message, or one that is delivered within a specific geographic area, has an open rate of 25 to 30 percent, which is much higher than the open rate for a mobile notification without location data (4 to 8 percent) or a coupon via email (1 to 2 percent).  Howler, a proximity marketing solution, has measured that hyper-local, targeted offers tailored to consumers' precise interests generate a more-than 50 percent conversion rate for traffic passing by the store, and an 89 percent engagement rate with the ads after they are broadcast.

Shoppers may also use apps that will send them coupons for stores nearby. Retailers can use beacons to better target advertising, since they can deliver deals based on what shoppers are already looking at or purchasing. 

Beacons provide a new unique form of advertising for retailers, who can sell coupon space to brands. Apparel magazine reports Hillshire Brands experienced a twentyfold increase in purchase intent for its sausage links after using beacons, with 6,000 in-store engagements within 48 hours of applying beacon technology.

Besides improving customer satisfaction by rewarding shoppers with promotions based on their interests, beacons capture rich performance data that helps them optimize their stores. Beacons show retailers how shoppers travel through a store and can be used to measure foot traffic in particular areas of a store by showing number of visits, unique visitors, new visitors and people passing a store. 

Retailers can discover what areas in a store aren't performing as well as others and improve them, or they can place high-performing items near items that need help. Beyond beacons, retailers can use performance analytics to examine what people tend to purchase in one basket, and think about grouping those items together in a store.

In insurance, performance analytics techniques that are used by retailers can improve insurance programs for clients, as well. Usage-based insurance is being embraced by auto insurers, as costs of plans take into account the actual driving behavior of customers. 

The National Association of Insurance Commissioners & The Center for Insurance Policy and Research reports that by 2020, 70% of all auto insurance carriers will use telematics usage-based insurance, which involves customers installing a wireless device in their car that transmits real-time driving data to carriers. This data captured by tools such as Progressive's Snapshot device includes everything from hard braking and acceleration, to miles driven and times of day spent driving.

How would you write insurance differently if you knew how much risk your insured was actually taking on?

Predictive Analytics Helps to Wipe Out Type 2 Diabetes

The human population is in dire need of a health checkup. Less activity and more consumption of processed and fatty foods with high sugar contents has skyrocketed over the past few decades. 

Factors such as these have contributed to rising cases of type 2 diabetes, as the American Diabetes Association reports about 28 million Americans have type 2 diabetes -- and more than 8 million cases of diabetes are undiagnosed. Diabetes isn't just a burden to the individual -- it places a massive strain on the economy. The American Diabetes Association shows that total economic cost of diagnosed diabetes in the U.S. in 2012 was $245 billion, a 41% increase from $174 billion in 2007.

The burden placed on the American economy comes in medical costs, absenteeism at work, decreased productivity at work and at home, reduced labor from chronic disability, and premature mortality. People with diabetes have medical expenses that are 2.3 times higher than if they didn't. 

If less than one-fifth of the people with type 2 diabetes in 2012 had prevented it during the prediabetes stage, more than $40 billion could have been saved in direct medical costs and reduced productivity. Thankfully, predictive analytics used in the healthcare industry have helped to show people when they're at risk and prevent the development of diabetes if they are in the prediabetes stage. 

A 2014 study presented by GNS Healthcare at the ISPORT 19th Annual International Meeting used big data analytics to build accurate predication models of the progression toward type 2 diabetes. The report identified risk factors such as being overweight, being 45 years or older, having a family history of type 2 diabetes, and being physically active less than three times a week. Electronic health records give healthcare operators access to valuable data that helps them better treat their patients in mitigating risk factors and preventing the development of diabetes. 

The Centers for Disease Control and Prevention reports people with pre-diabetes who change their lifestyles using a doctor-recommended program can cut their risk of developing type 2 diabetes by as much as 58%. More than 20% of healthcare spending is for people with diagnosed diabetes, which means predictive analytics in healthcare, which also helps improve personalized medicine and clinical trial recruitment, can help drastically decrease the prevalence of diabetes around the world.

These same types of predictive analytics powered by the healthcare industry that determine treatment are also meaningful for health insurers in determining healthcare insurance plan costs for those with high health risks. Predictive analytics also relates to everything from preventing fraud based on behavior patterns, to gauging whether certain geographic locations are more likely to experience natural disasters than others.

Process Analytics Makes Supply Chain Management Smoother to Make Customers Happier

Supply chain management is an industry that is steeped in processes, and every one, no matter how minute it might seem, can significantly affect the whole chain and, ultimately, the customer who is annoyed that their package is late to arrive. 

Using process analytics in a supply chain means every stage integrating a service or product is examined to determine ways to save money, improve efficiency and increase return on investment while still ensuring customer satisfaction. Sensors and data collection points throughout a supply chain allow businesses to track the actions within each process, so they can detect problems early and notify a manufacturer so they can proactively schedule service and prevent bigger problems.

Sensors and process analytics integration may be used on connected products and assets such as equipment, containers and trucks to detect damage, battery life and temperature changes. Process analytics help quickly identify ways to improve a process in operations so it can be implemented and scaled more easily, while transportation modes and delivery times can be changed based on what is happening throughout the chain.

The 2016 UPS The Rise of Smart Operations: Reaching New Levels of Operational Excellence white paper declared that manufacturing firms that invest in technology such as process analytics will experience superior revenue growth and higher margins than competitors in today's digital economy. Supply & Demand Chain Executive magazine reported a global Fortune 500 technology company that used process analytics were able to identify ways to reduce post-sales transportation costs by $8.7 million annually by reducing unnecessary same-day and next-day-business shipments through lower shipping costs and reductions in truck rolls.

Process analytics present manufacturers with the data that uniquely relates to their business and process, data that can help them improve quickly and exponentially compared to data relating to the whole industry.  

Process analytics is vital to your insurance company, too. Examining everything from how you generate leads, to where drop-off occurs during the customer sign-up process, to how claims are processed and communicated to customers gives your insurance company insight into how to make operations better for your team and better for your customers. Using process analytics allows insurance companies to see where efficiency can be improved and where tools such as technology can be used to streamline processes.

As you can see from these examples, data analytics can save entire industries millions of dollars and more, while saving employees and customers’ frustration. Want to learn more about how big data is transforming the insurance industry and what you can do to make the most of it? Learn more in our free e-book here.'

Download the eBook

Guy Weismantel

Mr. Weismantel is the Vice President of Marketing at Vertafore. With 20 years of marketing and financial leadership in companies such as Microsoft, Business Objects, Baxter HealthCare, Caremark International, and Expedia, Guy’s career has focused on bringing differentiated products to market and providing the “compelling reason to purchase” for customers and prospects alike.


Guy has a Bachelor's Degree in Accounting from the University of Notre Dame, and a Master's Degree in Business Administration from the Kellogg School of Management at Northwestern University.

 

 
 

 

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