An Oracle Strategy Brief November Better Business Intelligence for Insurers: Three Ways to Think Differently

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1 An Oracle Strategy Brief November 2011 Better Business Intelligence for Insurers: Three Ways to Think Differently

2 Executive Overview... 1 Introduction: The Benefits of BI... 2 Why Business Intelligence Is Difficult... 2 Three Strategies to Change How You Think about BI... 4 Business-Driven BI... 4 Put Business Intelligence First... 5 Choose Adaptive, Flexible Tooling... 5 Oracle BI for Insurance... 6 Conclusion... 6 About Oracle Insurance... 7

3 Executive Overview In an information-dependent economy, every insurer wants to maximize insight that may hold the key to a stronger competitive position. However, the reality is that while the benefits of business intelligence are clear, adoption and maturity levels remain low across the industry. Given the lack of adoption and maturity, insurers may not have the knowledge to better accomplish their BI goals. While it s true that BI projects present certain challenges, the issues are not as daunting as many insurers believe. Insurers that dare to think differently about business intelligence set themselves apart from the competition. An adaptive approach to BI and data warehousing allows business users take control of the data warehouse and reports, while automating many of the tasks that typically fall to IT. Oracle s adaptive data warehousing and BI solution helps you extract meaningful insight from insurance data and achieve your corporate goals. It starts with a business-driven approach to data warehousing and depends on a pre-built, configurable, insurance-specific data warehouse with flexible data models and reporting accelerators. When implemented this way, BI can be far more straightforward than you think. 1

4 Introduction: The Benefits of BI Done right, business intelligence offers many benefits to insurers. It eliminates guesswork, sheds new light on customer behavior and accelerates the internal reporting process. With better visibility, management can make quick decisions, reduce costs, prepare for the unknown and identify new areas of growth. This is not news to you. For all of these reasons, BI is a top priority among insurers today. According to Novarica, 40 percent of P&C insurers rank BI among the top three projects they have undertaken or will begin in the future, and most IT departments are working on more than one BI project at a time. 1 Yet a very small minority of companies report that they have executed their BI strategy with success. Why are so few insurers able to realize the vision and capture the value of such a promising technology? And if BI is so beneficial, why aren t more insurers realizing the benefits? In this strategy brief, we look at the underlying factors that make it difficult to implement BI and suggest three strategies to think differently about enterprise insurance data warehouses. Why Business Intelligence Is Difficult Several obstacles stand in the way of BI success for insurers large and small. To begin with, the need to consolidate and replace core systems forms a high barrier to building data warehousing solutions. Then there is the question of how you store the data once you get it out of your source systems. Finally, there is the challenge of data quality. Ninety-five percent of respondents in a recent Novarica survey saw significant challenges with the quality of the source data in their systems. 2 If it takes six months to deliver a report, and users don t trust the reliability of the data, your BI project will fail. As you begin to think differently about how you approach BI, it helps to see where you are on the BI continuum today, and where you d like to go tomorrow. As Figure 1 shows, getting the most business value out of BI requires maximizing BI capabilities. Very few companies are able to analyze, monitor or predict business activity. 1 NOVARICA MARKET NAVIGATOR : US Business Intelligence Solutions 2011 (Q1), Novarica, Business Intelligence in Insurance: Current State, Challenges, Expectations, Novarica,

5 Figure 1: The BI Maturity Model The implementation problems surrounding BI often leave insurers in a development quandary. With separate teams responsible for different aspects of the project from defining requirements, to data modeling, to Extract, Transform and Load (ETL) to building reports projects can take years to complete and fall well short of expectations. In the handoff between business and IT, the business requirements often get lost in translation. Figure 2: The BI Development Quandary. Business needs can get lost in translation between each step. 3

6 This experience suggests the need for a new approach one that positions BI as more than a reporting tool or the last step of a transformation process. It s time to think differently about the enterprise data warehouse. Three Strategies to Change How You Think about BI At Oracle Insurance, we see three ways for insurers to think differently about business intelligence and maximize the outcome of BI projects: 1. The business should own the success or failure of BI projects, not IT. 2. Make the data warehouse the first step in core system transformation. 3. Simplify the BI development quandary with adaptive, flexible tools. Business-Driven BI IT alone cannot solve the BI development quandary. Business decision makers need to establish accountability, ensure that business objectives are met, and increase user adoption by taking control of the BI strategy. Set up a centralized BI Competency Center to oversee the vision and strategy and ensure objectives are met. The BI Competency Center should establish clear objectives such as improving cross-line correlation, expanding and micro-segmenting product offerings, and reducing claims expenses. It should be managed by the business, with representation from each department, including IT. Each department will have a vested interest in achieving its goals and guaranteeing the success of the BI solution. Once you ve empowered the business and secured executive sponsorship, you can build a foundation for success. One insurer that has done this successfully is Canada s Desjardins General Insurance. Sonia Sevo, vice president of the insurer s Business Intelligence Competency Centre, notes that, A cross-functional organization spanning the business and IT groups is a must-have within any company that is serious about business intelligence and providing the most value to its user base. 4

7 Underwriting IT Actuarial Executives Finance BI Governance and Competency Claims Figure 3: BI competency requires multiple groups. Put Business Intelligence First Once the business is responsible for the success of your BI initiative, think about when to begin. Many companies tackle BI as an afterthought to enterprise transformation. They consolidate and upgrade their core systems first, and gather data later. Imagine how your strategy would change if you loaded historical data, which typically resides in multiple administration systems, into a central insurance-specific warehouse before modernization began. This would allow you to: Uncover data quality issues in all of your source systems prior to transformation, reducing your costs on new systems. Understand the limitations that your current source system are placing on your agility, reporting capabilities and data granularity needs. Leverage the insight of the analytic environment immediately in your day-to-day business and allow the core system transformation to occur in the background without affecting your ability to make quick decisions. Such a data-centric architecture would allow business users to focus on business problems, instead of worrying about IT problems. You d create a stronger backbone for transformation and a long-term strategy for data migration. Choose Adaptive, Flexible Tooling When you take advantage of a pre-built foundation and automate BI, you eliminate information silos and resolve the lost in translation problem. This empowers the business to make informed decisions based on accurate, timely data. 5

8 Oracle BI for Insurance Technology such as Oracle Insurance Insight an adaptive, insurance-specific data warehouse can enable straightforward BI. With Oracle Insurance Insight, business users have the ability to configure the data warehouse, and the system automatically generates ETL between staging, warehouse and data marts. By engaging the business more in the warehouse development, IT can focus on more strategic initiatives. Pre-configured data marts for multiple lines of business in Oracle Insurance Insight provide a quick starting point. These lines can be easily configured, and any line can be created from scratch. The application provides a design-time warehouse palette tool that allows business users to define and customize the data model by adding risk items and attributes. This makes it easy to tailor the solution for separate lines of business. These features greatly accelerate the define-load-report cycle, making it easy to verify that the solution meets the business needs. Built on core Oracle technology, Oracle Insurance Insight fits the business immediately, providing faster implementation, more accurate data structures, and what-if BI development, which allows flexible testing and deployment cycles all key requirements of the adaptive approach to BI. Scorecards, dashboards, KPIs, guided analytics and ad-hoc reporting can be easily personalized for specific roles, and delivered anywhere through mobile technology. This is adaptive BI, an approach that overcomes the BI development quandary and helps insurers realize the promise of better business intelligence. Conclusion Thinking differently about BI requires organizational and process change around three questions: Who owns the success or failure of BI projects (the business) How to prioritize BI projects in a transformation-driven environment (BI can come first) Which tools will allow the business to drive the project with IT as support, and provide the capabilities to adapt as source systems change Oracle s adaptive BI and data warehousing approach helps insurers extract meaningful insight from enterprise data and achieve their corporate goals. It starts with a business-driven approach to BI and leverages business intelligence to help drive transformation projects, rather than leaving it as an afterthought. Finally, use of the right tools such an insurance-specific data warehouse with an adaptive data model can make BI projects simpler and easier than insurers have ever thought possible. Insurers who approach BI projects in this way will not only complete their projects faster, they will more fully reap the benefits of business intelligence and build a foundation for the company s long-term success. Jason McDonald is director of product strategy and development for Oracle s BI and data warehousing solutions for insurance. Kyle Abel is a product manager with Oracle Insurance, responsible for Oracle Insurance Insight. 6

9 About Oracle Insurance Oracle believes that insurers should be able to leverage technology to help transform their business. Oracle Insurance provides adaptive, rules-driven systems that let insurance companies easily change business processes as their business needs change. These systems position insurers to become more adaptive themselves, ready to respond to dynamic market conditions and take advantage of new opportunities as they arise. Engineered to work together, Oracle s solutions support the entire insurance lifecycle from product development, to marketing and sales, to customer service and support, to management and compliance. For more information on Oracle Insurance, please visit oracle.com/insurance, contact us by at or call to speak to an Oracle Insurance representative. 7

10 Better Business Intelligence for Insurers: Three Ways to Think Differently November 2011 Oracle Corporation World Headquarters 500 Oracle Parkway Redwood Shores, CA U.S.A. Worldwide Inquiries: Phone: Fax: Copyright 2011, Oracle and/or its affiliates. All rights reserved. This document is provided for information purposes only and the contents hereof are subject to change without notice. This document is not warranted to be error-free, nor subject to any other warranties or conditions, whether expressed orally or implied in law, including implied warranties and conditions of merchantability or fitness for a particular purpose. We specifically disclaim any liability with respect to this document and no contractual obligations are formed either directly or indirectly by this document. This document may not be reproduced or transmitted in any form or by any means, electronic or mechanical, for any purpose, without our prior written permission. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. AMD, Opteron, the AMD logo, and the AMD Opteron logo are trademarks or registered trademarks of Advanced Micro Devices. Intel and Intel Xeon are trademarks or registered trademarks of Intel Corporation. All SPARC trademarks are used under license and are trademarks or registered trademarks of SPARC International, Inc. UNIX is a registered trademark licensed through X/Open Company, Ltd oracle.com

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