Probably more than companies in most other industries, insurers have enormous amounts of information they need to sift through hour-by-hour to better understand customer needs and claims. A report just released by IBM and the Saïd Business School at the University of Oxford makes a series of recommendations for delivering a successful Big Data initiative—especially when first starting out. The recommendations are based on observations and experiences culled from 1,144 business and IT professionals participating in a global survey:

1) Start with customer analytics. “It is imperative that organizations focus big data initiatives on areas that can provide the most value to the business. For many industries, this will mean beginning with customer analytics that enable better service to customers as a result of being able to truly understand customer needs and anticipate future behaviors.” In IBM's survey. When asked to rank their top three objectives for big data, nearly half of the respondents identified customer-centric objectives as their organization’s top priority.”

2) Develop an enterprise-wide big data blueprint. “An effective blueprint defines the scope of big data within the organization by identifying the key business challenges to which it will be applied, the business process requirements that define how big data will be used, and the architecture which includes the data, tools and hardware needed to achieve it,” the report states.

3) Don't try taking on the whole world of data at once. It's best to be pragmatic, especially at the beginning, the report's authors advise. “The most logical and cost-effective place to start looking for new insights is within the enterprise. Looking internally first allows organizations to leverage their existing data, software and skills, and to deliver near-term business value and gain important experience as they then consider extending existing capabilities to address more complex sources and types of data.”

4) Grow big data talent from within: Big data skills aren’t easy to come by. The report's authors recommend that companies address any skills gaps by investing in the professional development and career progression of in-house analysts who are already familiar with the organization’s unique business processes and challenges.

5) Create a business case based on measurable outcomes. As with anything new that requires investment, the business needs to see return on investment. The IBM report suggests building a business case based on the ability of a big data project to deliver smarter decisions, faster decisions, and decisions that make a difference. “Focus big data efforts toward areas that provide true differentiation. The most effective big data solutions identify the business requirements first, and then tailor the infrastructure, data sources and quantitative analysis to support that business opportunity.”

6) Create a foundation for action. “Work with different business units and functions to identify your most critical business opportunities and challenges that can be addressed with better and more timely information access. Many organizations begin with customer data and analytics to support their front-office transformation agenda. Remain vigilant about information governance (including information lifecycle management), privacy and security.”

7) Put plans into action. “Confirm active business leader sponsorship as you develop your big data strategy and roadmap. Develop the business case for one or two key business opportunities or challenges that you plan to address through proofs of concepts or pilot projects. Document the detailed project plan for migrating pilots into production. This plan should include confirmation of expected business value, costs, resources and project timelines.”

8) Embrace the innovation of big data. “Document quantifiable outcomes of early successes to bolster future efforts. Initiate formal big data communications across the organization to continue building support and momentum.”

Joe McKendrick is an author, consultant, blogger and frequent INN contributor specializing in information technology.

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