In one of his recent blog posts, Big Data: On Carts, Horses, Lamborghinis, and Executives, Insurance-Canada.ca’s Patrick Vice highlights the mixed points of views in various research reports and industry articles on the usage of big data in the insurance. He poses the question: where are we now, is it ugly, is it hard – is it a toss up?
Historically, companies across multiple industries have struggled with data. Advancement in technology has further exposed these challenges. Coupled with new mainstream data sources some are raising the white flag – or refer to it as hard and ugly. These companies tend to focus on the attributes of “Volume, Variety, Veracity and Velocity”. Good marketing words but, unfortunately, they are just “buzzwords”.
Value Focus = Success
In working with insurance companies, those that focus on Value are successful. These companies are moving ahead and not looking back. These are “Data-First Enterprises”. (Unfortunately, the insurance industry has a tendency not share successes because of competitive advantage, so the information is not wide spread.)
These are the insurance companies who have a renewed focus on leveraging data as a strategic asset and gaining new insights. These companies tend not to focus on the definition of “big vs. small” data – they have two common objectives throughout the company:
Transitioning Data to Currency: Business information is captured, quantified, explored and used to identify new revenue streams, enrich existing business streams and optimize performance.
Transforming Business Value Streams: Business operations move from post-transaction “reporting” to pre-transaction intelligence to continuously evolve value streams and optimize resource requirements.
These companies look at data much differently from the past and are addressing those challenges head-on using new ways of thinking (an “analytic-mindset”) and “know how”. New data sources are constantly discovered and explored. Their core business values include data with a new perspective:
- All data for every facet of the Customer or Product must be captured, stored and searchable for use now or in the future. (Single View Focus)
- Predictive Analytical Models continuously learn (Machine Learning)
- Data is explored and combined with new data sources (Data Discovery)
Where you can find out more
At the 2015 Insurance-Canada.ca Executive Forum, on August 31, 2015, I look forward to sharing additional information and insights on working with insurance companies who are realizing value from their “business initiatives” leveraging data in new ways.
Editors Note: Cindy Maike is GM of Insurance at Hortonworks, and is responsible for the center of excellence for the insurance industry. She has over 25 years of finance, consulting and advisory services experience in the insurance industry assisting clients globally with their business and IT strategy with a specific focus on the business strategy and the usage of advanced analytics to drive results.
