Hub Solution Designs. Data Governance: Start From Where You Are. Monday, April , 2:30-3:30 pm

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2 Hub Solution Designs > Data Governance: Start From Where You Are Monday, April , 2:30-3:30 pm Dan Power Haidong Song President Product Strategy Director, MDM Hub Designs Oracle Corporation Copyright 2012 by Hub Solution Designs, Inc.

3 Today s Speaker: Dan Power Founder and president of Hub Solution Designs, a global consulting firm specializing in master data management (MDM) and data governance. His role at Hub Designs is a combination of best practice expert, industry analyst, client advisor, and thought leader. He s responsible for client strategy and delivery in the areas of MDM, data governance, content marketing and social media. Dan is the author of more than 30 articles and white papers on MDM and data governance, and is a featured speaker at industry conferences, webinars and vendor events. He writes for Information Management magazine and The Data Warehousing Institute, and is the publisher of the Hub Designs Magazine, a widely read blog on MDM and data governance. Page 2

4 Agenda: May You Live in Interesting Times What is Master Data, Today s Complex Enterprise Architectures, Solving the Islands of Data Problem through Master Data Management (MDM) What is Data Governance? Why Govern Master Data? Using a Data Governance Maturity Model; Where Are Most Organizations Today? Why Is This Stuff So Hard? How To Get Started; When to Start Establishing Data Governance; Spend Time on The Design Before Launching Sample Organizational Model; Data Governance Steering Committee; Data Governance Office; Who ll Head Up the Data Governance Office? Data Stewardship Teams Where Will Data Governance Live? Who ll Pay For It? What To Do on Monday Morning; Data Governance Lifecycle What About Data Governance Technology? So What We re Really Talking About Is Business / IT Alignment; Which Brings Us Full Circle Page 3

5 What is Master Data? Information that s critical to the enterprise, including data entities such as customers, products, employees, suppliers, and locations. Shared (or should be) across applications, systems and databases, and across multiple business processes, functional areas, organizations, geographies and channels. Generally not something that happens at a particular time, but instead a person, place or thing that changes slowly over time. Not transactional, but used by and linked to transactions. Master data is the lifeblood of your company Page 4

6 What is Data Governance? Govern master data as you would any other critical asset in the enterprise with diligence, formal processes and metrics. A good definition from Jill Dyché: Data governance is the decision rights and policymaking for corporate data. When you see the word decision rights and policymaking next to the words corporate data, you know that you re dealing with an area that is more political than technological. But technology can be an enabler. The technology is the easy part. Understanding what drives people - individuals, societies, what makes cultures clash - all of those questions are way, way harder to answer than how to solve any particular technical problem. Dean Kamen, inventor/entrepreneur Page 5

7 Enterprise Architectures Have Become Too Complex Today, most companies larger than $500 million $1 billion in revenue: have grown through merger & acquisition activity, have a mixture of front office and back office suites and best of breed applications have some acquisitions and applications that are integrated and some that aren t As a result, most companies suffer from significant data silos and data fragmentation These data silos increase costs, hurt business and IT agility, and result in bad decisions being made (because of low quality, inaccurate, inconsistent data) Page 6

8 Solving the Islands of Data Problem through MDM Master Data Management (MDM) technology brings master data together in MDM hubs. In addition to the MDM hub itself, you ll usually need: Data Integration (usually using Service- Oriented Architecture) MDM Hub Data Profiling and Data Quality Business Process Management and Business Rules Management Third Party Data Enrichment Data Governance and technology to facilitate it ESB The MDM Hub centralizes master data, providing a Single Source of Truth, streamlining processes (which reduces costs), potentially increasing revenue and improving compliance Page 7

9 Why Govern Master Data? We re going to try to do MDM without a data governance organization? The alternative is information chaos and anarchy A disaster of biblical proportions. Human sacrifice, dogs and cats living together... mass hysteria! (Ghostbusters) Seriously, why bring together master data from all over the enterprise, cleanse it, build golden records of customers, products, suppliers, etc. And not govern the result? A value destruction exercise worthy of the Guinness Book of World Records And data governance is a critical success factor for MDM. Page 8

10 Using a Data Governance Maturity Model Usually based on the Software Engineering Institute s Capability Maturity Model (CMM) for software development. The model states what should occur at each level, not how to accomplish the activities. There are many different DG maturity models, but they share some common characteristics: Usually have 5 levels. Just a tool to assess where your starting from and where you want to go Be realistic about where you re starting from most companies are at 0 or 1 Page 9

11 Where Are Most Organizations Today? Just getting started: a recent survey of over 100 organizations found that only 10% have been able to move their DG programs beyond the lowest two levels of maturity. IT is still accountable for the data in 63% of organizations. Only 27% have established a data governance council with business representation and formal data stewardship. 57% of organizations do not measure the performance of data management activities. Even if you re just getting started, mighty oaks from tiny acorns grow. Page 10

12 Why is This Stuff So Hard? Companies aren t used to governing data across the whole enterprise goes against their instincts usually done at an application and business unit level. Can be tough to show ROI for data governance (doesn t mean it can t be done) but companies with effective governance processes in place generate up to 40% higher ROI on their IT investments than their competitors. 1 Governing anything is hard work! 1) Weill, Peter and Jeanne Ross, IT Governance: How Top Performers Manage IT Decision Rights for Superior Results. Boston: Harvard Business School Press, Page 11

13 How To Get Started First, avoid analysis paralysis Since many organizations don t know where to start, they do nothing at all Analyzing your current state and desired future state (using a maturity model) can provide a framework for planning your activities and managing your expectations, enabling you to proceed Define (1) where you are now, (2) where you want to be, and (3) over what period of time Then look at dimensions like MDM, data integration, data quality, and data governance over time, and do a gap analysis, leading to a roadmap This should lead to a realistic plan and design Page 12

14 When To Start Ideally, about 6 months before starting any master data management initiative So your new DG group will have a chance to form itself, and then help drive the MDM initiative But don t start before you ve got your executive sponsorship and funding lined up You ll just end up with a failed data governance effort to explain away later Better to wait until everything is lined up than start before you re ready Then get ready for the ride of your life corporate politics, new technology, org. change, marketing communications, project management, you name it! Page 13

15 Design Before You Launch Don t be rushed into getting organized too soon Setting up a Data Governance Council too early is a classic failure mechanism! Each company is different your DG program should be tailored to how your company is structured and to your corporate culture What works for a bank probably won t work for a high tech firm You ll need active, involved executive sponsorship don t try to do this from the bottom up Don t go beyond the research phase until your executive sponsorship is in place! Working from a solid design is a lot easier than making it up as you go along Page 14

16 Sample Organizational Model A three level model can work well. Data Governance Council (Steering Committee): a cross-functional, executive level group that makes policy decisions; with representation from all business and technical stakeholders. Data Governance Office (DGO) is charged with coordinating data governance (strategic) and stewardship (tactical) activities. Typically manages communications from councils to data stakeholders. One or more tactical groups (Data Stewardship Teams) in each functional area, which provide guidance to individuals with stewardship responsibilities MARKETING GPO Marketing Data Desk Team Marketing Business Community PRESIDENT SALES, MARKETING, SUPPORT SALES GPO Sales Business Community Sales Data Desk Team DATA GOVERNANCE VIRTUAL TEAM CHANNELS GPO Channels Business Community CEO EVP PRODUCT DEVELOPMENT Most important to have the organizational structure that will work in your company SUPPORT GPO Support Data Desk Team Support Business community PRESIDENT FINANCE FINANCE GPO Finance Data Desk Team Finance Business Community Courtesy: Rhapsody Technologies IT GSO Application Manager Configuration Team IT Operations Community Page 15

17 Data Governance Steering Committee Like the Supreme Court in the Federal Government Probably not going to take the time to make data policy (except on an escalated or exception basis) But has the power in the corporation to make sure policy is being followed, and to resolve issues escalated from lower levels Will usually include business owners and executive sponsor(s) Operates at strategic level Courtesy: Teradata Magazine It doesn t matter what you call this group; what matters is that you ve got the right people on it and that once it starts meeting, it accomplishes some useful things Page 16

18 Data Governance Office Like the Executive Branch of the Federal Government Heavily involved in making data policy Oversees the business data stewards and the IT stewards Usually includes the global process owners (from the business) and the global solution owner from IT Operates at the tactical level but needs to be comfortable managing up (to the strategic level) and down (to the operational level) Critical to a successful Data Governance organization the right Data Governance Office can make or break the whole effort Page 17

19 Who ll Head Up the Data Governance Office? There s a tendency in these job descriptions to be a little over the top looking for people who can in effect walk on water, leap tall buildings in a single bound, etc. Data Quality Pro had a great article: Data Quality Director Required - Must Possess Powers of Invincibility Vincent McBurney wrote an interesting article titled Data Governance is Career Suicide My Hub Designs Magazine responded with an article titled Data Governance: The People Make It Real, explaining how to support data governance leaders in their new roles This person does need the delegated authority of the CEO and a strong leadership style Page 18

20 Data Stewardship Teams Like the Legislative Branch of the Federal Government Works with the Data Governance Office in making data policy, and in carrying it out Needs to be from the business side in order to know the ins and outs of the data, but includes IT stewards as well Usually includes stewardship teams from various functional areas and geographies Works at the operational level but selected people will be (non-voting) representatives to the Data Governance Office Spends time responding to issues raised by others; monitoring data quality and developing new data quality and business rules; but real skill set is collaboration with multiple organizations at multiple levels Page 19

21 Where Will Data Governance Live? Where in the enterprise will your new data governance organization reside? Make sure it s in the business, not in IT May not be a popular position, but what other critical business assets is IT held accountable for? Operations, Finance, Customer Service, where ever your company can logically find a home for it Won t succeed in IT, because business won t give it the attention it needs to be successful Of course IT will be heavily involved, but the business needs to feel ownership, otherwise it will always be someone else s problem Page 20

22 Who ll Pay for It? How will the new data governance organization be funded? This will be influenced by the where will Data Governance live? question, since it will probably be funded out of that group s budget Reasonable to do allocations or charge-backs from the other parts of the enterprise that DG is serving Make sure the funding is on a continuing basis, not just a one year commitment Track all of the benefits (revenue increase, cost savings, compliance improvements) that Data Governance produces to help with inevitable funding renewal battles Page 21

23 What To Do on Monday Morning Once you ve started building out your data governance organization, what should it be doing? Assess your situation know exactly where you re starting from where is the enterprise DG today? Develop a sound data governance strategy Create some early wins and value Define and operationalize your DG processes Build out the rest of the Year 1 DG organization Year 1: plan for the Year 2 DG organization Continue to evangelize DG to the organization Document and communicate progress and wins to the enterprise Start with a plan for Year 1, and then during Year 1, plan out Year 2 Page 22

24 Data Governance Lifecycle Define data governance policies Author or update policies Analyze the impact Approve and publish (using BPM tool) Implement data governance policies Communicate policies to affected parties Translate into business rules (using BRMS) Deploy business rules Enforce data governance policies (!!) Handle policy violations Manage remediation Measure performance against goals (using DQ tool) Courtesy: Kalido Data governance must have teeth in order to be more than a paper exercise Page 23

25 Data Governance Technology Data governance involves People and Process, but Technology is an important enabler, for things such as: Data Policy Management Data Profiling and Data Quality Tools Business Process Management (BPM) Business Rules Management (BRMS) Metadata Management Tools Collaboration Tools Data Security Management That s a lot of technology for a group that s supposed to live in the business (and be business driven) to master The Data Governance Organization is going to need lots of IT support Page 24

26 What We re Talking About Is Business / IT Collaboration How can important initiatives be owned by the business, driven by the business, and have IT heavily involved in them and supporting them But not controlling them? Not the usual way of doing things for most company s IT organizations Need to get rid of the us vs. them mentality that is prevalent at many companies Blend the IT people for the DG initiative into the business? Courtesy: IBM That s the key getting IT and the business to work together; it can be hard when the IT people don t report to the business people they support Page 25

27 Which Brings Us Full Circle People: political and cultural change We started out by saying that data governance is more political than technological Hopefully you can see some of the reasons for saying that Process: new and streamlined processes New processes for governing data Which allows you to streamline existing processes in the enterprise for creating, reading, updating and deleting data Technology: a broad spectrum of enabling technology Information: don t forget it s all about the data Have worked with people on MDM and DG who seem to consistently forget to look at their data People Process Information Technology To be successful, MDM and DG need a balanced approach Page 26

28 What We Covered Today Introduction: Today s Complex Enterprise Architectures, Solving the Islands of Data Problem through Master Data Management What is Data Governance? Why Govern Master Data? Using a Data Governance Maturity Model; Where Are Most Organizations Today? Why Is This Stuff So Hard? How To Get Started; When to Start Establishing Data Governance; Spend Time on The Design Before Launching Sample Organizational Model; Data Governance Council; Data Governance Office; Who ll Head Up the Data Governance Office? Data Stewardship Teams Where Will Data Governance Live? Who ll Pay For It? What To Do on Monday Morning; Data Governance Lifecycle What About Data Governance Technology? So What We re Really Talking About Is Business / IT Alignment; Which Brings Us Full Circle Page 27

29 Companies Need To Change In Order To Survive TUI Travel CFO resigns after major accounts system fault; IT systems merger problem prompts travel giant to $155 million results restatement Relentless cost pressure, coupled with fairly slow demand growth No room to lose and then replace existing customers Most organizations juggling multiple transactional and analytic applications across corporate, regional and local areas While customers demand faster and more complex responses from organizations Leading to a disconnect that threatens organizations ability to make decisions and act quickly within their markets MDM and data governance can solve the Islands of Data problem and unify the corporation s view of the world Page 28

30 Haidong Song, Product Strategy Director Presenting with

31 Data Governance Technology Requirements Define,&Communicate&&&Enforce& Define enterprise master data Define and execute data policies Resolve conflicts at various levels during merge process Monitor&Hub&Opera;ons& Analyze hub DQ metrics Monitor hub transaction status Easily&Operate&Hub& Execute day-to-day hub operations (Consolidate, Cleanse, Share & Master) Conduct what-if analysis Improve&Steward&Produc;vity& Assign data management tasks Manage escalation and collaboration 1 Copyright 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8

32 Define, Communicate and Enforce With Enterprise Data Model, Policy Enforcement, and Conflict Resolution Enterprise party and product model Drag and drop corporate hierarchy management UI Unified infrastructure to capture cross reference Rule based modeling and execution of enterprise merge policies Guided merge process to facilitate generation of best version record during consolidation 2 Copyright 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8

33 Easily Operate Hub With Steward Dashboard and What-If Analysis Consolidate steward dashboard with embedded analytics to provide single landing page for all steward tasks. Provide what-if analysis/ simulation capability during batch data management tasks to reduce errors and efforts in governance 3 Copyright 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8

34 Monitor Data Quality and Hub Operations With Contextual Analytics and Data Quality Metrics Integrated data quality metrics Embedded contextual analytics for data management tasks 4 Copyright 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8

35 Improve Steward Productivity With tasks assignment, collaboration, escalation, and history tracking Ability to assign data management tasks to steward Manage review and escalation process Integrated tagging and group space to facilitate collaboration Track comprehensive lineage and data management decisions made such nonduplicates to reduce rework and errors 5 Copyright 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8

36 Oracle Master Data Management Process MDM Delivered Siebel EBS SAP Custom Apps Other Trusted Master Data Siebel EBS SAP Custom Apps BI Consolidate & maintain a unique, complete and accurate master information across the enterprise for customer, supplier, employee, product, asset, site & financials data Distributes this information as a single point of truth to all operational & analytical applications just in time 6 Copyright 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8

37 For More Information search.oracle.com Master Data Management Oracle MDM Blog 7 Copyright 2011, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 8

38 Questions? Page 30

39 Contact Information Hub Solution Designs, Inc. 188 Whiting Street, Suite 3 Hingham, MA USA office: +1 (781) web: magazine: hubdesignsmagazine.com Dan Power, powerd@hubdesigns.com, twitter.com/dan_power Subscribe to our newsletter at Join the MDM Community at Page 31