Driving Business Performance with effective Enterprise Information Management

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Using data quality to drive effective business performance. The Data Quality Associates way, shared on http://www.dataqualityservice.com

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  • 1. A talkbook on Data Governance and Data Quality Management Driving Business Performance with effective Enterprise Information Management

2. Internal Notes Delete before showing to the clients The purpose of this presentation is to introduce clients or prospects to our capabilities in delivering Enterprise Information Management solutions. It is intended for use by non-subject matter experts or SMEs to showcase our capabilities and solutions and to lead prospects to the next conversation, which should be with a SME. Additional slides on our Enterprise Information Management Framework and service offerings can be included as an appendix to this presentation. If your client is ready for a more detailed discussion, you can customize the presentation through the use of these additional slides. Lastly, where ever applicable, the messaging notes can be found in the speaker notes pages. Please delete these notes before sharing electronic copies of the presentation with external parties. 2 3. Contents Market View on Enterprise Information Management Common Enterprise Information Management Challenges and Drivers Our Information Governance Framework and Service Offerings Introduction to our Information Governance Framework Information Lifecycle Management (ILM) Data Governance Framework and Organisation Structure Data Ownership and Stewardship Master Data Management Data Classification Data Flow Analysis Data Quality Management Our Engagement Methodology Appendix- Our Point of view on Business Intelligence v/s Enterprise Information Management Appendix - Other Supporting Slides / Contents 3 4. Market View on Business Intelligence and Enterprise Information Management 5. Business Intelligence and Enterprise Information Management - Defined 5 Our point of view is a little less complicated. Business Intelligence (BI) empowers the right people to receive the right information, at the right time, allowing them to make the right business decisions. Enterprise Information Management (EIM) provides the foundation for the business to operate as truly intelligent enterprise. Business intelligence (BI) is an umbrella term that includes the applications, infrastructure, tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance. Gartner Enterprise Information Management (EIM) is an integrative discipline for structuring, describing and governing information assets across organizational and technological boundaries to improve efficiency, promote transparency and enable business insight. Gartner Enterprise information Management (including Data Quality Management and Data Governance) is the single most important prerequisite to a Business Intelligence implementation. Without the proper data, or with too little quality data, any BI implementation will fail. Before implementation it is a good idea to do data profiling; this analysis will be able to describe the content, consistency and structure - Kimball et al., 2008 1 2 3 6. Executives are focused on BI 6 1. Gartner EXP 2012 Survey of CIOs 2. MIT Sloan Management Review : Findings from the 2010 New Intelligent Enterprise Global Executive Study and Research Project Analytics: The New Path to Value Business Intelligence continues to be the top priorities for the CIOs across the globe.1 Over the next 24 months executives say they will focus on supplementing standard historical reporting of data with emerging approaches that convert information into scenarios and simulations that make insights easier to understand and act on. 2 By 2013: 33% of BI functionality will be consumed via handheld devices 15% of BI deployments will combine BI, collaboration and social software into decision-making environments *Gartner Research 7. . but BI has not delivered on the promise. 7 1. Coming Up Short on Non Financial Performance Measurement, Ittner and Larcker, HBR 2. Does your business intelligence tell you the whole story? - KPMG International. Your BI solution may have you looking at the wrong information. 1Fewer than 10 percent of organizations have successfully used BI to enhance their organizational and technological infrastructures. 2 3 4 More than 50 percent of business intelligence projects fail to deliver the expected benefit. Two thirds of executives feel that the quality of and timely access to data is poor and inconsistent. Seven out of ten executives do not get the right information to make business decisions. 70% of companies employ metrics that lack statistical validity and reliability.1 While 95% of companies forecast cash flows, only 14% of cash forecasts are accurate.2 According to KPMG International, the execution of business strategy is often hampered by a lack of reliable information2: 8. Accuracy of Data continues to drive most Business Intelligence and Information Management Projects 2% 12% 15% 16% 17% 52% 56% 57% 60% Other Reduced risk of noncompliance Reduced risk to business performance Greater control Greater flexibility More-timely, accurate indication of future performance Improved efficiency More-robust analytical capabilities High-quality, more-reliable management reporting Multiple responses permitted. Source: CFO Research Services/Lawson Software 2010 0% 10 20 30 40 50 60% Areas of prioritized spend 8 Ensuring the accuracy of the information reported form a business intelligence system is another central theme that organisations encounter. Integrating information from across your enterprise while keeping the quality of data intact from record to report has revealed a range of issues not previously apparent. The executives are now focused on making their BI solutions more reliable by through an information management agenda. 9. Organisations are using an information agenda to plan for the future 9 Highest data priorities for Organization: Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute for Business Value study. Copyright Massachusetts Institute of Technology 2010. Information Governance: In order to create truly valuable business intelligence, organizations should clearly define who owns, uses, and produces information and how it is presented. Such tight ownership and control should help give consistent, accurate reports and allow fair, like for like comparisons of performance. Information Integration: The sheer volume and types of data an organization generates has grown enormously. Managing this data effectively and being able to rely on its accuracy is now even more critical to businesses. Simplification is a one of the most significant component of the information agenda. Complexity should not be viewed as a burden to be avoided; it should be seen as a catalyst and an accelerator to create innovation and new ways of delivering value - Juan Ramon Alaix, President, Pfizer Animal Health - IBM 2010 Global CEO Study. 10. Business Intelligence is more than just reporting 10 Valued Business Information Dashboards, monitoring, in sight KPIs, scorecards Real time reporting Supporting Framework Data Governance Data Quality Information Integration Reporting and Data Management Platforms Infrastructure Database, Security, ETL There are many benefits to the business at the surface, however a sustainable and defined infrastructure and governance framework is required to support the consistent delivery of effective Business Intelligence and Performance Management information. 11. Common Enterprise Information Management Challenges and Drivers 12. Common Business Information Challenges Everyone is effected 12 CEO CFO Board & Management CxO CIO Associates Customers & Suppliers I cant get the information I need quickly enough to react to the events and changes in the market conditions. Root Cause: Data Governance Framework & Organisation Structure, Data Ownership and Stewardship and Data Flow Analysis. It is too difficult to obtain all the information I need to make better decisions. Root Cause: Data Classification, Data Flow Analysis, Data Mapping and Data Modeling. I dont have enough confidence in some of our information to make critical decisions. Root Cause: Data Quality Management and Enterprise Information Strategy . We run this business by gut feel rather than facts. Root Cause: Data Quality Management, Information Integration and Distribution. I receive a multitude of reports with conflicting information so we waste time debating which measures are correct instead of making decisions. Root Cause: Data Quality, Data Standardization and Master Data Management. Majority of our analysts time is spent gathering data instead of analyzing and the information to create insights. Root Cause: Data Quality and Data Ownership/Stewardship. Your organization does not understand the full breadth of the relationship your customers and suppliers have with you. Root Cause: Master Data Management , Data Flow Analysis, Information Lifecycle Management and Enterprise Information Strategy. All most all executives within your organisation are effected by the quality of your organizational data. For Industries that processes huge amounts of data on a daily basis, Data Quality can make or break an organization. Some of the key information management challenges faced by organizations are: Information Consumers 13. Common Business Information Challenges The root causes are also common Common and critical data resides in separate systems Data is incomplete and critical information is not captured. Obsolete Data. Reference data is not consistent across systems. Data content differs from actual business rules. Data does not reconcile across all integrated systems. The same information is captured from multiple system Inconsistent definitions and standards No common definition of data, including customer data. The same data is not captured in a consistent format across the organisation. Difficult or impossible to consolidate information for cross department / cross geography use. Limited Analytical Capability As the data is not completely captured, the ability to analyse data is limited. Restricted ability to discover potential opportunities for cross-sell and up sell using the current available data. Lack of knowledge of the affiliates with repeated transactions. Income/spend patterns and trends are not easily available. Unclear Data Ownership No formalised governance policy in place. The data ownership and consumption of data is not clearly defined. Manual Processes and Limited Sharing of Data There are high degree of manual processes in place and limited sharing of data between countries and systems. Lack of knowledge for end-to-end process. ChallengesRootCause 14. The Need for Enterprise Information Management Why is information management so important to me? Many organisations fail to effectively manage their data, resulting in greater risks to the business and missed opportunities for commercial and competitive advantage. Effective and innovative data governance and data quality management can help you to reduce the risks and realise the true potential of your organisation's information: 14 o Improved customer profitability and product coverage through single customer view and product insights. o Reduce risk (financial and reputational) through improved data quality, control and security. o Better informed planning based on accurate operational and forecast data o Enhanced anti-fraud measures through linking and forensic analysis of structured and unstructured data. o Auditable regulatory compliance and repeatable decisions on large data- intensive. o Early risk warning systems to continuously monitor and improve operational efficiencies and profitability. o Technology-enabled-solutions that are tailored to your needs and enables you to focus on the most relevant information. 15. Driver for Information Governance 15 Drivers Pressures Information Governance Value proposition Increasing Business Value Merger and Acquisition Activities Business Unit Consolidation/Diversification Off-Shoring/Outsourcing Business Process Improvement Administrative Process Improvement Consistent Security and Compliance Practices Quicker Rebranding of Services Reduced Lost Productivity Reduce Cost of Compliance Improved Business Process and Workflow for Data Improving Compliance Federal and State Privacy regulations HIPPA Safe Harbour COPPA FCRA/FACTA NERC/FERC Improved Compliance Monitoring Compliance automation Improved Auditing and Logging Flexibility to Adapt to New Regulations Improved Compliance Reporting Reducing Risk Regulatory compliance Breach of client, employee data or Intellectual Property (IP) Third Party Management Information Asset Management Increased Security Risks Compliance industry regulations Protection of Critical Data Elements Understanding of Data Location and Flow Improved Control of Information Assets Brand protection Better Enforcement of Policy and 3rd Party Management Containing Cost Breach Recovery/Management Costs Management of Legacy Documentation Consolidation of IT Data Repositories Consistent Security and Compliance Practices Information Life Cycle Management Reduced Costs, Resources Classification of Data Elements 16. Our Information Governance Framework and Service offerings 17. Our Information Governance Framework 17 Our Information Governance Framework is designed to strike the right balance between technical and functional infrastructure for effective information management. There are seven components to the framework, which, although interdependent, can also be applied individually. Our Information Governance Framework also unpins our service offerings that help us to assist our client with designing personnel, process, technology, and controls that address compliance requirements, while also protecting the most important information assets Our approach encompasses the complete governance lifecycle, helping to enable clients to choose the appropriate services to achieve their specific business needs. Information Lifecycle Management Data Governance Framework & Organisation Structure Data Ownership and Stewardship Master Data Management Data Classification Data Flow Analysis Data Quality Management Technology 18. Key Components of Our Information Governance Framework 18 Information Lifecycle Management (ILM) The core of our approach focuses on ILM which comprises the policies, processes, practices, and tools used to align the business value of information with the most appropriate and cost effective IT infrastructure -- from the time information is conceived through its final disposition. Data Governance Framework and Organisation Structure The process of defining the roles / relationships and information management organization structure. It helps to drive ownership rules, set standards and direction for data management and create data quality standards....