In recent years, unprecedented market pressure, increased regulation, and unforeseen natural disasters (such as the recent earthquake in Japan) have caused turmoil in the insurance industry across the Asia-Pacific region.
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Business intelligence (BI) can deliver the information that managers need to make critical decisions, and many are hungry for the value that added insight would deliver; yet they are cautious about projects that could take years to implement and returns that are difficult to predict.
One way to alleviate these concerns and build a strong business case for BI is to use both quantitative and qualitative metrics to evaluate the total potential return to the business.
For most companies, the return generated by a BI implementation extends well beyond traditional cost-savings analysis to encompass far-reaching benefits, such as:
ï¶Â  Fewer wrong (and costly) decisions made based on insufficient data
ï¶Â  Knowing which products to bring to market
ï¶Â  Knowing which policies to stop writing
ï¶ Â Understanding renewal rates
Before proceeding, IT and business managers need to build a strong case for a BI implementation. A number of challenges stand in the way: according to published analyst reports, common reasons why BI projects fall shortinclude the lack of a data model, the difficulty of making changes to systems as reporting needs change, and the lack of ETL (extract-transform-load) capacity.
Fortunately, if you know where the value of BI is likely to appear, you can set up the initiative for success from the start.When measuring return on investment (ROI) for business intelligence, many people default to standard financial metrics.
They weigh revenue enhancements, cost savings, and cost avoidance against hard dollar costs such as license fees, server costs, ongoing maintenance, internal labor, and any external services.
This is a fine place to start, but quantitative measurements will fluctuate wildly depending on the project scope, system design, management commitment, and the organization’s ability to handle change. Moreover, these numbers alone cannot tell the whole story.
To form a complete picture, it’s important to factor in the larger business benefits. For example, what is the value of higher customer satisfaction, better decision making, or a single version of the truth? To be meaningful, ROI measurements must reflect overall corporate strategy objectives. Ask yourself: what is the value of better decision making to my organization? It might lead to lower costs, improved market share, or increased revenue.
Customer satisfaction often improves when companies have better insight into customer needs – and with increased satisfaction comes higher retention rates, lower churn and more revenue. In a 2009 survey, the majority of respondents who realized benefits from a BI initiative reported that they had experienced faster, more accurate reporting, improved decision making, and improved customer service.
Consider these and similar factors in any ROI calculation, and you’ll be in a good position to estimate the value of BI to your business.
Some sample questions to ask include:
ï¶Â  How many questions go unanswered due to the difficulty of getting information?
ï¶Â  What is the cost of not having quick access to information at every level of the organization?
ï¶Â  How fast can you go to market with a new product today?
ï¶ Â Do you know if you are profitable at a policy and/or claims level?
Traditional ways of calculating ROI do not tell the whole story of the value that a business intelligence solution can bring to the enterprise. Companies that consider a broader range of returns will have a more accurate picture of expected results and a strong business case to present to their stakeholders.
Ready to begin? Start by setting up a BI project that spans several business and IT groups. Establish shared goals, and identify the projected revenue enhancements and cost savings. Break the project up into manageable steps and tackle one at a time, always keeping the overall goal in mind. In the end, you’ll have pervasive business intelligence that enables better decision-making throughout the enterprise.
Jason McDonald, Director, Product strategy at Oracle Insurance, responsible for business intelligence and data warehousing applications.
