Draft Webinar Template Enterprise Master Data Mgt Oct24 2011(V5)


Published on

Webinar for enterprise data management. One version of the truth is what all business leadership wants from their data.

  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Draft Webinar Template Enterprise Master Data Mgt Oct24 2011(V5)

  1. 1. Presented By: Speaker Firms and Organization: Danny Miller Principal & National Solutions Leader Grant Thornton, LLP Thank you for logging into today’s event. Please note we are in standby mode. All Microphones will be muted until the event starts. We will be Phil Teplitzky back with speaker instructions @ 11:55am. Any Questions? Please email: Info@knowledgecongress.orgChief Technology Officer and Managing Director HPSquared, LLC Group Registration Policy Please note ALL participants must be registered or they will not be able to access Rocco Maggiotto the event.Managing Director – Business Advisory Council If you have more than one person from your company attending, you must fill out the group registration form. HPSquared LLC We reserve the right to disconnect any unauthorized users from this event and to deny violators admission to future events. To obtain a group registration please send a note to info@knowledgecongress.org or call 646.202.9344. 1 October 27, 2011
  2. 2.  If you experience any technical difficulties during today’s WebEx session, please contact our Technical Support @ 866-779-3239. You may ask a question at anytime throughout the presentation today via the chat window on the lower right hand side of your screen. Questions will be aggregated and addressed during the Q&A segment. Please note, this call is being recorded for playback purposes. If anyone was unable to log in to the online webcast and needs to download a copy of the PowerPoint presentation for today’s event, please send an email to: info@knowledgecongress.org. If you’re already logged in to the online webcast, we will post a link to download the files shortly. “If you are listening on a laptop, you may need to use headphones as some laptops speakers are not sufficiently amplified enough to hear the presentations. If you do not have headphones and cannot hear the webcast send an email to info@knowledgcongress.org and we will send you the dial in phone number.“ 2 October 27, 2011
  3. 3.  About an hour or so after the event, youll be sent a survey via email asking you for your feedback on your experience with this event today - its designed to take less than two minutes to complete, and it helps us to understand how to wisely invest your time in future events. Your feedback is greatly appreciated. If you are applying for continuing education credit, completions of the surveys are mandatory as per your state boards and bars. 6 secret words (3 for each credit hour) will be give through out the presentation. We will ask you to fill these words into the survey as proof of your attendance. Please stay tuned for the secret word. Speakers, I will be giving out the secret words at randomly selected times. I may have to break into your presentation briefly to read the secret word. Pardon the interruption. 3 October 27, 2011
  4. 4. Brief Speaker Bios:Danny MillerDanny Miller is a principal in Grant Thornton’s Business Advisory Services group in the Philadelphia office andis a member of the leadership group for business consulting, which includes technology, cybersecurity andbusiness consulting for the firm in the U.S. He is also the national solution practice lead for cybersecurity for thefirm in the U.S. He is a member of Grant Thornton’s national Higher Education and Not-for-Profit leadershipgroup. Danny has over twenty-five years of experience in the Information Technology, Cybersecurity, BusinessConsulting and Audit fields.ExperiencePrior to joining Grant Thornton, Danny was a partner for a consulting firm where he was responsible for all clientdelivery operations, QA and IT for the firm. Danny has a range of international experience as a director for aninternational consulting firm, a software developer, database administrator, a global IT audit manager, and theCIO of a group of European-based e-commerce companies. He also has experience in data privacy laws andstandards including all ISO standards regarding data governance protection and the European Union’s Directive95/46/EC on data privacy. He has extensive experience in cybersecurity, privacy, IT strategy and transformationand business transformation using technology as a catalyst.Industry experienceDanny has comprehensive experience in a variety of industries, including higher education, not-for-profit,financial services, banking, oil, gas, consumer and industrial products, Internet, construction, real estate andmanufacturing. He has broad experience in those same industries internationally, including European Unioncountries and Southeast Asia. 4 October 27, 2011
  5. 5. Brief Speaker Bios:Phil TeplitzkyPhil is a professional with 35-years of experience in the management and operations of information technologyand information technology consulting. He has been involved in the day-to-day management of systemdevelopment projects, the establishment of Standards Procedures and Guidelines for softwareengineering, quality engineering and change management at major institutions. He has extensive experience inbringing new technologies and software engineering disciplines into Financial Services. Previously Phil was the CIO at The Harry Fox Agency and CTO at both TheVitaminShoppe.com, NeighborhoodPay Services and Mibrary. He has also been a Managing Director of Technology at SHL SystemHouse withresponsibility for its Northeast Region, Vice President of Technology at Citibank and National Director atCoopers & Lybrand with responsibility for Data Base technology and Architectures.Phil has been a frequent lecturer and speaker at Data Base, Software Engineering and Architectureconferences. He has a Master of Science in Computer Systems from the School of Advanced Technology(Watson School of Engineering) at State University of New York at Binghamton. 5 October 27, 2011
  6. 6. Brief Speaker Bios: Rocco Maggiooto Rocco Maggiotto is a Managing Director member of HPSquared’s Business Advisory Council and a retired Executive Vice President and Global Head of Customer and Distribution Management for Zurich Financial Services General Insurance Business. Mr. Maggiotto was responsible for the development and implementation of Zurich’s customer and distribution management strategies, their global industry practices, and Chairman of General Insurances Growth Agenda. Mr. Maggiotto held this position since June 2006, recently retired and joined HPSquared LLC as a Business Advisory Council Member. As a Council member, Mr. Maggiotto consults with Financial Services and Insurance Companies. Prior to joining Zurich, Mr. Maggiotto’s career was divided equally between management consulting and financial services executive roles. He was a Senior Executive Advisor in Booz Allen Hamilton’s Management Consulting business where he specialized in finance and risk management, strategic design for client development and integrated client relationship management processes. Rocco’s previous career has included roles as Chairman of Client Development for the Parent Company of Marsh & McLennan Companies, Inc. as well as Senior Partner for PricewaterhouseCoopers, where he was a member of their Global Leadership Team and Global Markets Leader. This role included PwCs global industry practices, their client relationship management programs, and strategic planning, e-business and marketing and communications functions. Rocco was also a Vice Chairman for the former Coopers & Lybrand as well as Managing Partner of their New York region, and Chairman of C&L’s financial services industry practice worldwide. Rocco also developed and managed Coopers & Lybrand’s US Financial Consulting Business. Before that, Rocco was a Partner with KPMG Management Consulting Practice and, for 16 prior years, held management positions in a New York banking institution, covering areas of finance, operations, management information systems and corporate services. Mr. Maggiotto holds a Bachelor of Arts degree in Political Science and a Masters in Business Administration in Finance. He is also a certified systems’ professional. He is on the Boards of the Ronald McDonald House of New York, The Weston Playhouse Theatre Company, and the Council of Governing Bodies of New York States private colleges and universities. He is also on the Board of Directors of inXpay, a private company specializing in matching of commercial invoice and payment vouchers; and Lucid Inc. Lucid is a medical device and information technology Company that develops, manufacturers, markets and sells FDA cleared non-invasive diagnostic confocal imagers for accessing skin lesions suspicious for skin cancer.For more information about the speakers, you can visit: http://knowledgecongress.org/event_2011_Data_Management.html 6 October 27, 2011
  7. 7. What would you say if you found out that most of the reports, dashboards and other information that youwere using to run your business are incorrect? Do you think it might impact your ability to competitively runyour business, or even make good, sound decisions? If you don’t have confidence that you are makingdecisions on the right data, you are not alone. Many businesses are awash in data and are unable tostate with certainty that the information that they use daily is correct. That calls into question how we thinkabout data and how its used.Enterprise Data Management (EDM) is the management of an institution’s fundamental data that is sharedacross multiple business units, everything from project budgets to donor contacts to employee contactinformation. You can think of master data as all of the enterprise data (people, places, things andactivities) that the institution needs to conduct its business.The goal of EDM, consequently, is to ensure the accuracy, consistency and availability of this data to thevarious business users. 7 October 27, 2011
  8. 8. In the webcast, we will discuss what Enterprise Master Data Management (EMDM) is and how strategiesbuilt around the EMDM framework can benefit businesses. We will also discuss several key concepts ofdata management, including: • What business problems do EDM help address • Data maturity models, their meaning and value to an organization • Data quality strategy and practices • Applying EDM in data warehouse situations • Security considerations when it comes to enterprise master dataWe will discuss real life examples of actual companies in multiple industries that have been impacted by alack of enterprise data management and how implementing EDM standards and practices has improvedtheir businesses. 8 October 27, 2011
  9. 9. Featured Speakers:Danny Miller Phil TeplitzkyPrincipal Chief Technology Officer and ManagingGrant Thornton, LLP Director HPSquared, LLC Rocco Maggiotto Managing Director - Business Advisory Council HPSquared LLC 9 October 27, 2011
  10. 10. Topics we will cover• Business Drivers – Why EDM is important for Business, Information and Technology Leaders• What is EDM – What comprises an EDM Framework• Benefits of EDM – What do enterprises realize from an EDM Framework• Guiding Principles of EDM – What are the keys for success• Convergence of EDM and Business – Information Leaders (Finance and Risk), Technology and Business need to work in concert• Reference Models – There are proven models that can be adapted• Summary 10
  11. 11. Business and Market drivers that are elevating the importance of Enterprise Data• Market (identity and cross sell), serve, and know your customer better• Improve competitive position• Reduce technical complexity and cost• Meet Regulatory requirements• View data as a valuable enterprise asset• Manage the explosive growth in data• Leverage advancements in technology and software• Align and share fragmented storage – across silos 11
  12. 12. A View of Some Executive DriversCEO/CFO  Signoff on financial statements, quality of the data and the systems that produce them.CIO  Balance the need to support business growth with cost. Balance founded in efficient architectures, synergistic investment in technology, and availability of good informationCRO  Siloed approach to compliance is no longer acceptableCMO/BU Leader  Leverage customer relationships, manage distribution channels, develop more responsive products and services, grow profitable revenues and meet regulations of new economy  Support rapid change not supported by older databases, and  Overcome silo behaviors for cross sell & up sell.  Merge external data for total view of customer. 12
  13. 13. What Is Enterprise Master Data Management?MDM is the management of an institution’s fundamental data that is shared across multiplebusiness units, everything from project budgets to employee contact information. You canthink of master data as all of the enterprise data (people, places, things and activities) that theinstitution needs to conduct its business.The goal of MDM, consequently, is to ensure the accuracy, consistency and availability ofthis data to the various business users.All organizations would benefit greatly from creating a strategy for MDM and implementing anMDM program in light of its current state and an organizations future data and informationneeds. 13
  14. 14. What Is Enterprise Master Data Management?• Master Data is the common business data that need to be organizationally agreed and then shared globally inside.• Companies are awash in data, but which data is the right data to use? Data grows by 50%+ each year.• Company leadership needs "one version of the truth" on dashboards, reports and in analytical datasets.• Financial, Internal Audit and Compliance departments should be concerned about controls, availability, integrity and quality of data.• Conceptually:  Data and information are valuable corporate assets and should be treated as such  Data must be managed carefully and should have quality, integrity, security and availability addressed. 14 October 27, 2011
  15. 15. To satisfy the Business and Market drivers the Enterprise needs to:• Align information (data), technology and business strategies• Clarify roles and responsibilities for enterprise data management• Develop a common data management language for business and technology• Identify data uses, values and interdependencies• Prioritize data improvement efforts with its value, align with existing project priorities, and capture short wins for momentum• Make relevant, accurate and useable information (data) available to support decision making and business processes• Ensure data is shared and appropriately secured in our IT systems as define by law and market demands• Leverage information (data) in business decisions, processes and relationships 15
  16. 16. Common EDM Issues Found Across Many Enterprises• Discovery – can not find the right data• Redundancies – can not create value due many versions of the same data exist in different hands• Business Intelligence:  Integration – can not access, manipulate and combine the data  Integrity – can not reconcile data across the enterprise  Insight– can not extract value and knowledge from the data  Collaboration – can not leverage and share data for market facing activities• IT Leadership – can not manage or control data growth• Management – can not make confident business decisions 16
  17. 17. Pragmatic Business Benefits for the Enterprise• Assurance that common data reconciles across systems and the organization• Improved data quality across the enterprise• Reduced complexity in the management of data through standards• Ability to trace flow of data across systems and the enterprise• Can scale to meet future business volume – increasing data volumes• Meet the needs of any project and can extend across the wider enterprise 17
  18. 18. Keys of a successful EDM StrategyAccommodates • Changing business requirements • Delivery of tactical projects • Progressive changes in technologyAligns with other strategic initiatives • Consistent frameworks, blue prints and roadmaps • In touch with organizational culture • Allow for parallel activitiesImproves data management competency across enterprise • Integrate data management metrics across activities • Data governance • Solutions which integrate conceptual, logical and physical to insulate for change 18
  19. 19. A Good EDM Strategy Must Include:• Vision which aligns business to technology and strategic to tactical• Executive /C-Level Sponsorship• Data Governance & Data Stewards for relevant subject areas• Solutions which are architected versus systems that are build• Standards, policies, and procedures• “Data Management” Organization• Technology solutions which are open, based on common standards, flexible and promote re-use 19
  20. 20. What Is Enterprise Master Data Management? 20
  21. 21. Data QualityPre-Governance Governance Provides• Overly complex IT infrastructure • Uniform communications with customers,• Silo-driven, application area-centric solutions suppliers, & channels due to veracity & accuracy of• Slow-to-market delivery of new or enhanced key master data application solutions • Common understanding of business policies & processes across LOBs & with business• Inconsistent definitions of key corporate data assets partners/channels such as customer, supplier, & pricing masters • Rapid cross-LOB implementation of new apps• Poor data accuracy within & across business areas requiring shared access to master data• LOB-focused data with inefficient or nonexistent ability • Singular definition & location of master data & to leverage information assets across LOBs related policies to enable transparency & auditability essential to regulatory compliance• Redundant IT initiatives to re-solve data accuracy • Continuous Data Quality improvement as Data problems for each individual LOB Quality processes are embedded upstream rather than downstream • Increased synergy for cross-sell & up-sell. 21
  22. 22. Data Quality - Governance• Establish institutional data standards• Identify and resolve data disputes• Implement necessary changes to data standards and policies• Communicate actions to the organization as appropriate• Ensure accountability of institutional data policies and standards• Escalate issues to Governance Team as necessary 22
  23. 23. Data Quality• Definition: timely, relevant, complete, valid, accurate, consistent• Role of Data Quality• How to measure Data Quality• Poor data quality and its cost• Process efficiency impact as a result of poor data quality• Potential benefits of new systems not be realized because of poor data quality – if you dont address it up front, you will pay for it!• Decision making is ultimately negatively affected by poor data quality – many examples available 23
  24. 24. Data Architecture• Is the transformation of the Data:  Requirements  Operational Characteristics and Attributes  Data Base and Data Structures  Standards and Frameworks Into a Physical instantiation – the Data Ecosystem• All Architectures are based on the universal truth that Form follows Function and in this instance it is the physical Form of the Data Ecosystem Dimensions – which are defined in the Data Maturity Model 24
  25. 25. Data Operations: Security & Privacy• Information Risk Management (security) is a process that identifies risk to all information assets and provides an approach to control and mitigate risks.• Need to consider impact of loss, alteration or exposure of information to the organization.• Privacy of Personally Identifiable Information (PII)• To start the process, perform an analysis of risks by:  Identifying all information assets that are important (data classification)  Assign a value and important (data classification)  Looks at threats and vulnerabilities  Measure the risk to assets  Come up with a game plan that is economically feasible to protect assets 25
  26. 26. Data Operations: Data Warehouses• What is a Data Warehouse?• Issues that can occur in Data Warehouses and attempting to apply EDM principals• Role of EDM in the creation of Data Warehouses  Consistency of Semantic and Syntax  Translation and normalization  Common language, edit and validation• What should I do?  Create a Data Warehouse Data Maturity Model  Asses your level of Data Maturity at both the:  Operational  Data Warehouse level of abstraction  Create an Action Plan to mitigate identified issues and deficiencies 26
  27. 27. EDM requires Business & Technology to Work in Concert• Information/data management is a shared responsibility between data management professionals in IT and business data owners representing the interests of the data producers and data consumers• Business data owners are concerned with:  Definition and value of the data  Data quality (data is useable at deferent times and different degrees of accuracy)  Data stewardship (roles and responsibilities vary)  Availability and sharing of the data• IT is the custodian of the data and responsible for the systems which store, maintain, process and deliver the data 27
  28. 28. Enterprise Data Management Reference Model• Model is based upon multiple dimensions• Core areas for the evaluation process include and are not limited to: 1. Data Governance and Strategy 2. Data Platform 3. Data Operations 4. Quality Management• Each business will have a specific set of dimensions and definition of target long term maturity levels, as industry information management needs vary. 28
  29. 29. Data Maturity Reference Model Data Maturity Model Level 5 The Data Maturity Model (DMM) is Optimized an Industry accepted model support by the Software Engineering Institute Level 4 (SEI) from Carnegie Mellon.Level of Maturity Managed DMM provides an auditable Level 3 framework and methodology for Defined defining the specific components at the business – process level required Level 2 for effective Data Management. Reactive Full DMM defines best practices and Level 1 provides a framework for assessing Initial and measuring capability. Maturity Criteria Data Governance & Strategy, Data Operations, Quality Management, Data Platform 29
  30. 30. Data Maturity Interaction Model • data key resource for process improvement – enterprise asset • semantic metadata and business rules actively managed Levels of Maturity Level 5 • data management process – continual improvement Optimized • automated processes : data consistency, accuracy, reliability • Level 1 - Initial : Data management • central metadata repository - synchronization processes are mostly disorganized and • data policies well documented and enforced Level 4 generally performed on an ad hoc basisLevel of Maturity •business active in data strategy - Stewards Managed • unified data strategy exists •data recognized – enterprise asset • Level 2 – Reactive : Fundamental data •meta data repository exists management practices are •Workflow not linked to data flow Level 3 Defined •data models exist in isolation established, defined, documented and •limited controls exist repeatable •central platform for managing data •data functions •data integrated point to point at local level Level 2 • Level 3 – Defined : Business analysts Reactive • data models and definitions at application level begin to control the data management • risk high – lack of integration, consistency, standards process with T playing a support role •processes not repeatable – not well defined Level 1 Initial • data - general purpose – no consistent formats & definitions • Level 4 – Managed : Data is treated as a critical corporate asset and viewed as •data stored redundantly in unconnected databases -siloed equivalent to other enterprise wide assets ( e.g. capital, resources, technology) Maturity Criteria • Level 5 – Optimized : the organization Data Governance & Strategy, Data Operations, Quality Management, is in continuous improvement mode Data Platform 30
  31. 31. Data Maturity Interaction Model Maturity Criteria Level 5 Optimized Level of Maturity Data Governance & Strategy Level 4 • Strategy, goals & scope definition Managed • Data content and coverage Level 3 • Sponsorship Defined • Governance Operating Model Level 2 Data Operations Reactive • Data policies & procedures Level 1 • Data procurement & sourcing Initial • Business precedence and data validation • Data distribution & entitlement • Archive, retention, security & privacy Maturity Criteria • Business process & workflow Data Governance & Strategy, Data Operations, Quality • Hierarchies & linkages Management, Data Platform • tewardship & ownership • Mapping and cross referencing • Extensibility and reuse  Data Platform Quality Management • Common data model • Data quality strategy & objectives • Loading and application integration (ETL and EAI) • Quality assurance & audit • Semantic and definitions • Data cleansing, enrichment and validation • Format standards and messaging model • Change and exception management • Transformation rules • Inventory, traceability and surveillance • Data repository standards • Classification • Architecture framework (SOA) • Quality measurement and benchmarking • Metadata Repository 31
  32. 32. Standards and Meta Systems• Standards are ubiquitous and necessary components of all civilizations – they are the warp and woof of civilized life• Types of standards in everyday life: – Dictionaries – Grammars – ANSI / ISOYou use them every time you to the Super Market, the Auto, Plumbing and Electrical Supply storeEvery time you go to the Bank, Use a Credit Card or use the WEB or play a song on you iPod 32
  33. 33. Standards• Where do standards come from?• They come from groups of people who need to communicate and make themselves understood• For economic reasons – Trade across countries – Trade across companies• Examples: – Samuel Johnston and the English Dictionary – Otto Von Bismarck and DIN – UCC (Uniform Commercial Code) 33
  34. 34. Summary• Today’s increasingly complex business environment is placing greater data needs on the enterprise e.g. – 360 view of the customer – More demanding regulatory and compliance reporting• Addressing these needs requires an enterprise to manage its data as a cross organization asset• A strategy which combines business and technology to develop and deploy a holistic Enterprise Data Management framework 34
  35. 35. Q&A: Danny Miller Phil Teplitzky Principal Chief Technology Officer and Managing Grant Thornton, LLP Director HPSquared, LLC Rocco Maggiotto Managing Director – Business Advisory Council HPSquared LLC You may ask a question at anytime throughout the presentation today. Simply click on the question mark icon located on the floating tool bar on the bottom right side of your screen. Typeyour question in the box that appears and click send. Questions will be answered in the order they are received. 35 October 27, 2011
  36. 36. Notes: *** Participants in this webcast are given a special discount of $50 in all upcoming Knowledge Congress’ events in 2011 by applying discount code “kcwebcast88” on the second page of the registration form. *** To view the list of our upcoming events, please visit: http://www.knowledgecongress.org/events.htm 36 October 27, 2011
  37. 37. ABOUT THE KNOWLEDGE CONGRESS:The Knowledge Group, LLC is an organization that produces live webcasts which examine regulatorychanges and their impacts across a variety of industries. “We bring together the worlds leadingauthorities and industry participants through informative two-hour webcasts to study the impact ofchanging regulations.”If you would like to be informed of other upcoming events, please click here. Disclaimer:The Knowledge Group, LLC is producing this event for information purposes only. We do not intend toprovide or offer business advice.The contents of this event are based upon the opinions of our speakers. The Knowledge Congressdoes not warrant their accuracy and completeness. The statements made by them are based on theirindependent opinions and does not necessarily reflect that of The Knowledge Congress views.In no event shall The Knowledge Congress be liable to any person or business entity for any special,direct, indirect, punitive, incidental or consequential damages as a result of any information gatheredfrom this webcast. 37 October 27, 2011