Amerisure using advanced analytics to reinvent the insurance process

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A growing number of organizations are undertaking the journey to become data-driven, using advanced analytics to make better business decisions, to get closer to customers, and to improve processes and efficiencies.

Among them is Amerisure Insurance, a top provider of property and casual insurance with more than 2,600 employees. Amerisure is in the process of unifying its myriad data sources in order to take advantage of self-service analytics and embedded business intelligence.

Information Management spoke with Doug Pontious , CIO, CTO and BI and analytics executive at Amerisure, about the company’s efforts, and how he views the potential benefits of advanced analytics.

Information Management: What is your organization doing in the area of data analytics and what is driving the efforts?

Doug Pontious: Amerisure Insurance has implemented a data management platform and leverages self-service business intelligence to deliver profound insight, reports and operations directly into the hands of our business users. While focusing on advanced analytics, we are also ensuring that the underlying data is accurate and complete with data governance and data quality initiatives that allow our organization to reach higher levels of success.

Our company’s vision for true enterprise-wide reporting and analytics has improved claims processing, premium production, fraud management, finance and other crucial operations, while strengthening relationships with agencies and policyholders. We are also looking to automate analytics within our core systems, tap into descriptive reporting and predictive insight, and embed analytics and artificial intelligence into our own smart applications.

IM: What do you consider to be the biggest trends in data analytics right now and what do you think companies will be doing in that area a year from now?

Pontious: There is a lot of interest in advanced analytics and a path toward employing prescriptive analytics. Identifying patterns and predicting seasonal changes that enables organizations to use their data for strong business decisions requires a predictive model that is constantly changing.

We appear to be a few years away from fully deploying prescriptive analytics and taking advantage of its capabilities. With that said, it looks to be the next big development to take the data industry by storm – just as self-service BI did years before.

As organizations begin to tap into the early days of advanced analytics, we’ll witness which initiatives won’t last and which will be replaced by something better. With that said, many organizations will need to let advanced analytics mature before taking full advantage.

IM: What are some common mistakes or misconceptions about being a data-driven organization that other IT or data leaders should be aware of?

Pontious: You’ll never be the first person to encounter an issue or be responsible for addressing it. It’s important to attend events such as the Gartner Data & Analytics Summit to learn from your peers and communities of thought leaders.

These events allow your organization to build a stable and concrete base for further developments in advanced analytics. Without this base, it’s not possible to build the ultimate enterprise solution without causing unnecessary frustration and potentially losing the trust of your employees.

Establishing a base for advanced analytics also involves building the right platforms, providing executive support, sharing reliable data and enacting some major initiatives. If a roadblock presents itself, there is always the opportunity to reevaluate goals and shift directions to ensure there is a strong correlation between data and how it will be used.

Take advantage of the organization’s own business value and talent to build the right culture that can adapt as advanced analytics is implemented. The right IT and analytics talent can inspire a strong data culture, but don’t forget to lean on partnerships to avoid an imbalance between those who don’t understand analytics and those who do. Give teams the opportunity to learn something radically different than from what they’re used to and allow for proper growth.

Speaking of the recent Gartner Data and Analytics Summit in Grapevine, Texas, what did you see and hear at the show that was new or different in terms of what companies are doing with data analytics?

Pontious: Attending the Gartner Summit, we were able to confer with our peers and learn how others are successfully bringing AI, cognitive computing, IoT and embedded analytics into existing data initiatives so that we can bring those lessons to our organization.

I was amazed at how much the conference has expanded. The number of attendees, quality vendors, and the scope of analytics has grown considerably over the past three to five years. With this growth, the strategies and approach to data initiatives has shifted, and it was fascinating to see which trends are gripping the industry.

Five years ago, we couldn’t stop talking about self-service BI. Now, hyper-speed acceleration, AI and cognitive computing are leading the discussions. The industry is also more equipped than ever before to serve a wider range of companies and their business needs with smart, more affordable data solutions, allowing even small organizations to tap into the power of data innovations.

The event also had an increased focus on providing much tailored experiences for attendees. We were given excellent opportunities to interact with our peers and exchange best practices. For instance, Amerisure Insurance connected with others in our industry to learn how new practices directly affect our industry. As a result on these invaluable conversations, we could gauge if we are headed in the right direction and gain new insights on what we should consider next.

IM: What messages came out of the show that especially caught your interest?

Pontious: The IoT has certainly come a long way, and as a result, we must adapt. This was emphasized in Information Builders’ session on creating an analytics culture to support digital evolution with IoT. The session encouraged attendees to think about how the IoT surrounds us on a daily basis. Building a thriving analytics culture is a key to success in the digital evolution that is driving business trends and reshaping enterprise practices.

It was also evident in the various sessions that we’re beyond basic BI and data warehousing to data governance and data quality. With this in mind, organizations must be sure to have the culture and tools that support this initiative and match the sophistication of its users.

It was also intriguing to look at the innovative ways organizations are collecting valuable data. As an insurance company, we can use drone technology, for instance, to assess damage and risk prior to and after an incident or disaster. Collecting this data helps to make more informed decisions for our customers.

It was clear just how much the data and analytics industry has accelerated and matured – from the capabilities, scope, vendors and the expectations of the attendees.

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