2. Agenda Review Meeting Objectives Agile Projects Information Management Practice Data Warehousing Business Intelligence Data Integration Advanced Analytics Data Governance Next Steps
4. Who we are … Agile Technologies is a nimble, aggressive, consulting firm focused on improving our clients’ businesses by bringing together deep insurance industry experience, the flexibility to build partnership-based engagement teams and technology expertise. Since our founding early in 1997 we believe a critical success factor to achieving breakthrough bottom line results for our clients is understanding their businesses and the difference they are going to make in their markets. We know successful technology investments help them achieve those goals. Our firm’s commitment to client success is demonstrated by our seasoned professionals’ industry experience, knowledge of the technology landscape in the insurance industry and long history of successful projects. We are committed to helping our clients stay at the forefront of rapid industry changes by helping them develop new markets and creating new efficiencies and capabilities for their organizations. Our Mission is to build long-term, durable relationships with our clients that continually deliver improved business results from their investments in technology, business processes and communications.
5. Mergers, Acquisitions, Affiliations and New Players Margin Pressure Global Marketplace Changing Regulatory and Compliance Environment New Products and Services Customer Needs Clear Answers and Partners They Know Broker/Wholesaler/Agency Support, Compensation, Licensing & Education Business Dynamics Creating Opportunities to Differentiate
6. Technology Solutions Making a Bottom Line Impact Improve Process Efficiency Reduce time to market into Custom Development Efforts Reduce Risks (Implementation and Changes) Increase Management Controls Accelerate Program Introduction, Training and Support Improve Customer Satisfaction (Quality time with clients) Drive Technology ROI (Software and Hardware) Enhance Systems Flexibility and Reporting
7. Agile Technologies’ Value PropositionIn Action Industry Knowledge – Our teams consist of industry professionals that understand, have managed and improved all elements of property & casualty insurance businesses. Experienced Professionals – The mix of professionals that service our insurance clients have decades of experience in both the insurance business and the specific technologies used by our clients. Outcome Focused Project Teams – Our standard engagement approach establishes focused objectives at the outset of each effort and project . This is a critical component in our project methodology and will drive the teams toward the critical project objectives. Hands-on Executive Leadership – The entire executive team has extensive experience in insurance and is involved in every engagement. Demonstrated Flexibility in Approach – Our approach positions our clients for success using blended teams.
60. Insurance Data Warehouse – Project Initiation Laying the ground work for your data warehouse project is essential to success. As your data warehouse development partner, Agile Technologies will assist with the project initiation and accomplishing the following goals: Establish project timelines and deliverables Define expected benefits of the project and definition of success Establish overall scope for the project Appoint a steering committee to oversee project decisions, establish priorities and develop an adoption strategy Appoint an executive sponsor Establish a status reporting process Expose the business community to the overall project Establish budget guidelines for the project
61. Insurance Data Warehouse – Data Governance You must understand the quality of your data and develop a plan to cleanse and maintain the data in the operational systems. The quality of the information presented from the data warehouse can only be as good as the data which is sourced into it. Some data can be cleansed in the ETL process however some data may require manual cleanup in the source systems. Profile your operational data to determine what (if anything) needs to be done Establish a data governance and quality team to make decisions on cleansing data Establish a plan to maintain clean data in your operational systems Establish data ownership by the business user community Develop plans to cleanse data via routines in your ETL process
63. Insurance Data Warehouse – Business Requirements Work with the business community to establish formal business requirements. This will provide the information necessary to develop the data design which will service the needs of the business community and identify things such as: Business Data / Source Systems Operational systems (Policy, Claims, Billing, Finance etc.) Spreadsheets External Data Key Performance Indicators (KPIs) Data granularity Load frequency Security Data delivery and reporting requirements How do the business users want the data presented? Target user groups
64. Insurance Data Warehouse – Database design A data warehouse should be designed to service the needs of the business. Proper database design will be extensible and flexible to allow for growth and expansion as your business evolves. Agile Technologies can customize our proven insurance standard data models to meet your specific business needs. Dimensions – Informational data which will provide the means by which data will be segmented, such as: Product Attributes (ASL, Subline, Program) Geography Attributes (State, County, Rating Territory, Zip) Coverage Attributes (Coverage, Limits, Deductibles) Risk Attributes (Risk Class, Location, Sub location) Distribution Channel Attributes (MGA, Retail Agents, Direct) Facts – Statistics which measure the performance of your business or operation. Premiums (Direct, Ceded, Assumed, Net) Losses (Paid, Expense, Reserve, Incurred, IBNR) Exposure (Basis and Units) Ratios (Loss, Expense, LAE, Combined)
65. Insurance Data Warehouse – ETL Design and Development The ETL process will move data from source systems into the data warehouse. The process may include staging databases to control the flow of data and provide points of audit in the process.
66. Insurance Data Warehouse – Data Validation and Balancing Proper data validation and balancing will ensure the data in the data warehouse is a complete and accurate representation of your business and its performance. Data should be balanced back to the source systems at multiple levels. Creating a simple balancing matrix will provide a comprehensive set of audit documentation along with transactional audit logs systematically generated during the ETL Process.
67. Insurance Data Warehouse – Security and Presentation / BI Security A data warehouse contains data which may be sensitive in nature. Proper data security is required to ensure data is only viewed or accessed by those authorized to consume the data. Presentation / Business Intelligence The data in a data warehouse can be presented to the users in the form of reports, graphs, charts, scorecards or dashboards. These tools can be evaluated based on their data presentation capabilities, performance, and compatibility with selected database platforms. Self-service capabilities must also be considered in selecting which tool is right for your organization. A BI Tool can allow you to easily identify and analyze trends in your business, measure progress to plans and send alerts based on conditions in your business.
68. Insurance Data Warehouse – Capacity Planning Capacity Planning Data in a data warehouse is often denormalized and should be designed for efficient reporting. The denormalization of the dimensions creates a large data store which requires proper capacity planning. Understanding the expected volume of data within your data warehouse will facilitate hardware requirements, database design requirements (partitioning, indexing, aggregate tables) and load execution timeframes.
70. Agile Insurance Data Models Benefits Quick start on development of Insurance Data Warehouse environment Benefit from experience of many Agile Data Warehouse implementations Expedite maturity of data warehouse and analytics that can be generated Property & Casualty Insurance Technology Independent Business Process Independent Uses Normalized (Staging, ODS) Dimensional (Data Marts, End-User Analytics) Cost Included as part of Agile implementation services One example of numerous collateral framework components Agile leverages as part of its substantial experience base
71. Agile Insurance Data Models Line of Business Personal Auto Homeowners & Dwelling Fire Commercial (Admitted and Non-Admitted) Commercial Property Commercial Liability Commercial Auto Program Business Surety Subject Areas Quote Policy Claims Billing Reinsurance Distribution Channels Forecast / Plan
75. Business Intelligence – Introduction Business Intelligence (BI) is an environment in which business users have access to information that is reliable, timely, consistent and understandable. With this information, and with industry standard BI tools, business users are able to conduct analyses that provide an overall understanding of the business. Business intelligence serves two main purposes: It monitors the financial and operational health of the organization and It provides analytical, modeling and forecasting capabilities that allows the business to anticipate and manage future business performance.
76. Business Benefits of BI Implementations Tactical Monitors Financial and Operational Health of the Organization Reports, Charts, etc… Regulates Operations of the Organization Alerts, Dashboards, etc… Operational Gain a better understanding of the market and customers’ needs Reduce operating costs through increased efficiency Reduce customer churn and improve retention through better loyalty programs and customer service Strategic Improved Decision Making Align Strategy with Results Change Processes and Improve Results Source: Microsoft
91. Project Plan - Metadata Design & Construction Data Mart ODS Multi-Dimensional Aggregation Transform Data Create Aggregate Hierarchy Business Terms Create and Publish Construct Metadata Project Organize by Subject Area Metadata Packages
92. Project Plan - Construction Construct Reports New Dashboards Control Reports New Reports New Scorecards Unit Test Construct Delivery and Security Web Portal E-mail Report Bursting Security Unit Test
93. Project Plan - Test and Validate Control Reports Source System Metadata Control Reports Validate all other Reports / Scorecards / Dashboards End to End Test User Acceptance and Sign - Off
94. Data Warehousing - Making BI More Effective Data structure and definition is more easily understood for people constructing analytics and reports Organized for efficient BI processes Analytics and reports run faster Pre-aggregated dimensional models for comparative analysis Data is transformed from source systems to a common level of detail (grain) making it easier to use in analytics and reports Supports drill down and drill through to easily view the details behind a report Manages historical data Historical data is frequently not managed in OLTP source systems Provides point in time analysis Makes BI faster, better, easier and more effective
