Data Governance: Start From Where You Are

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1 Data Governance: Start From Where You Are Dan Power Hub Solution Designs, Inc. Why Govern Master Data? The most important thing about data governance is to start from where you are. Most companies are just getting started on their data governance journeys. It can be hard to admit that your company is at data governance maturity level 0 or 1. But the most critical step is the first one getting started. We live in interesting times. Poor information security practices led to the release of a huge number of secret diplomatic cables to WikiLeaks. The Federal Aviation Administration admitted that registration information for as many as one-third of all private aircraft is out-of-date and inaccurate, forcing the FAA to cancel and re-register all civil aircraft. And the private sector isn t immune. TUI Travel, Europe s largest tour operator, accepted the resignation of its CFO after restating its 2009 results to the tune of $155 million, blaming problems in integrating computer systems following a 2007 merger. Sound familiar? Hopefully, your company doesn t have any data governance skeletons in the closet like these. But if you hunt around a bit, you ll undoubtedly find people in your business who can tell you about: decisions that were made based on reports with wrong or missing information, the real costs of duplicate data in your customer master database, cash flow being impacted because invoices were being sent to the wrong addresses, supplier master issues causing millions in avoidable costs in lost volume discounts the penalties for not complying with industry and government regulations on customer data and privacy, failure to comply with tax laws because of inaccurate billing information, information-heavy projects that run over time, or require length rework after go-live, decommissioning systems becoming nearly impossible because clear retention and destruction policies have not been defined, manual correction and alignment of content and documents takes time away from resources because these items aren t well governed, IT staff spending a lot of time re-integrating data and dealing with data fire drills because data service level agreements and fit-for-use levels have not been established and tracked. If you take the time to talk to business owners across functional areas like R&D, Marketing, Sales, Finance, Operations, Human Resources, and Customer Service, you ll fill up a small notebook with the stories about what not having a data governance organization is costing your company. First, What Is Master Data? Good question. Master data is the lifeblood of your company. It s information that s critical to the enterprise, including entities such as customers, products, employees, suppliers, and locations. It s shared (or should be) across applications, systems and databases, and across multiple business processes, functional areas, organizations, geographies and channels. It s generally not anything that happens at a particular time, but is instead a person, place or thing that changes slowly over time. Master data is not transactional, but is used by and linked to your transactions. COLLABORATE 12 OAUG Forum Copyright 2012 by Hub Designs Page 1 of 11

2 What is Data Governance? Master data needs to be governed just as you would any other critical asset in the enterprise with diligence, formal processes and metrics. I ve often said that if companies treated their cash, inventory and real estate assets the way they treat their customer and product data, a lot of people in corporate America would be going to jail. Jill Dyché, in Ten Mistakes to Avoid when Launching Your Data Governance Program, defined data governance as the decision rights and policymaking for corporate data. Whenever 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 important enabler. One of my favorite quotes is by Dean Kamen, the inventor and entrepreneur: 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. 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 have created shadow IT organizations in some Lines of Business in an effort to speed up results have created complex processes for dealing with data issues, causing individual groups to creatively work around those processes have more diverse groups of workers with diverse experience (and preferences) for enabling software tools (like Excel) As a result, most companies suffer from significant data silos and data fragmentation what I call the Islands of Data problem. These data silos increase costs, hurt business and IT agility, and result in bad decisions being made throughout the enterprise because of low quality, inaccurate, inconsistent data. Master Data Management Can Solve the Islands of Data Problem Master Data Management (MDM) technology brings master data together in an MDM hub. In addition to the MDM hub itself, you ll usually need: Data Integration (usually using Service-Oriented Architecture) Data Profiling and Data Quality Business Process Management and Business Rules Management Third Party Data Enrichment Technology to facilitate Data Governance The MDM Hub centralizes master data, providing the much-desired Single Source of Truth, streamlining business processes (which reduces costs and increases productivity and agility), and increasing revenue (through ability to support more targeted marketing and cross sell / up sell initiatives) and improving compliance. COLLABORATE 12 OAUG Forum Copyright 2012 by Hub Designs Page 2 of 11

3 But committing to MDM technology isn t enough, unfortunately. Nor is it the first thing you need to figure out. In order to make the entire exercise work, we also need data governance. So Why Do It? Why Govern Master Data? The alternative not governing it is information chaos and anarchy. A disaster of biblical proportions. Human sacrifice, dogs and cats living together... mass hysteria! (from one of my favorite movies, Ghostbusters). Seriously, why would we bring together master data from all over the enterprise, cleanse it, build golden records of customers, products, suppliers, etc. and not govern the decision-making process, result, and resulting analytics? That would be a value destruction exercise worthy of the Guinness Book of World Records. Data governance is a critical success factor for master data management. MDM isn t a lights out operation. Don t try to do master data management without a data governance organization in place or under construction. Using a Data Governance Maturity Model Something that I recommend early in a new Data Governance program is using a Data Governance Maturity Model to realistically assess how well you currently govern data at the enterprise-wide level. This is helpful so that you ll know where you re starting from relative to the four dimensions of People, Process, Technology and Information, before embarking on your initiative. Most Data Governance Maturity Models are based on the Software Engineering Institute s Capability Maturity Model (CMM) for software development. A Data Governance Maturity 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: they usually have 5 levels, and they re just a tool to assess where you re starting from, not something to get hung up on or on which to spend a lot of time. The National Association of State CIOs (NASCIO) did a great study of the different Data Governance Maturity Models available from organizations such as IBM Data Governance Council, DataFlux, EWSolutions, Gartner, Knowledge Logistics, the MDM Institute, and Oracle Corporation, concluding that data governance maturity models can be used as references in communication, awareness building, and the marketing of data governance. Where Are Most Organizations Today? The important thing is to be realistic about where you re starting from most companies start at 0 or 1. A lot of companies are doing governance, just not formally. People are managing data, they just need to figure out who s doing it, and what and how they re doing. Then group them and provide some central guidance to get them started. Here are three things to think about: 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. And 57% of organizations do not measure the performance of data management activities at all. COLLABORATE 12 OAUG Forum Copyright 2012 by Hub Designs Page 3 of 11

4 Most companies with which I ve worked haven t been successful making the required organizational, cultural, process and technological changes with internal resources alone. Most of the companies with which I ve worked have a research & analysis period of up to two years under their belts before they start making serious progress on their programs. The reality is that with cross-functional, multi-year programs such as MDM and data governance which involve multiple organizational, process, technology and information disciplines, it s better to proceed deliberately and have a series of incremental wins that show business value, rather than go for a rapid implementation or a big bang approach. Progress in this area is not linear you make investments, you build competency, you do the hard work (and sometimes even get frustrated), and then by doing a relatively small amount of remaining work, you start to achieve your goals. Like a baby learning to talk, or an adult learning a foreign language, there s a steep learning curve that flattens out rapidly at the top. Companies will seem not to make progress for a long time (while they re making the investment in growing their data governance capability), and then their abilities will come together rapidly, as people get a chance to put their new skills to work in a new Data Governance Organization. Why Is This Stuff So Hard? Companies aren t used to governing data across the entire enterprise. It goes against their well-honed instincts, which are to break things up into silos. Where they do have data governance in place, it s usually done at an application or business unit level. And it can be tough to show ROI for data governance. But companies with effective governance processes in place generate up to 40% higher ROI on their IT investments than their competitors, according to Peter Weill and Jeanne Ross in IT Governance: How Top Performers Manage IT Decision Rights for Superior Results (Boston: Harvard Business School Press, 2004). The bottom line is that managing things, when you have control over them yourself, is hard enough. Governing them, when you have to consult with others, gradually win them over, and lobby for things that matter deeply to you, is hard work! How To Get Started First, it s important to 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 as we discussed in the previous article, provides a framework for planning your activities and managing your expectations, enabling you to proceed. Start by defining with some degree of precision (1) where the company is now, (2) where the company wants to be, and (3) over what period of time. Then look at the critical elements such as MDM, data integration, data quality, data enrichment, data governance, business process management, BI, enterprise content management, and information lifecycle management over time. This should lead to a realistic plan and design. For more information on how to create a strategic roadmap, see James Parnitzke s article on that topic. COLLABORATE 12 OAUG Forum Copyright 2012 by Hub Designs Page 4 of 11

5 Design Before You Launch Don t let yourself be rushed into getting organized too soon. Setting up a Data Governance Council too early is a classic failure mechanism! Spend time on things like developing the data governance program s overall vision and strategy, and its value statement its reason for existing. Your stakeholders will want to know the answers to some basic questions like where will the program live, and how will it be funded? Once you have the basics outlined, you can move on to the more detailed elements of the design. Who will be involved? How will the program be organized? Will it be centralized or de-centralized? Why are we doing this? What will the DG program do for the enterprise? Before you launch a formal governance council, you need to have positioned the initiative to a key executive sponsor. Without them, the council will be just another meeting. Another point to keep in mind is that a global council can work cooperatively with local groups. Some companies think the global group is too big because it has to centrally govern all aspects of Customer, for example, instead of defining the 10 critical attributes across business processes and simply starting there. Whatever you decide on these questions, working from a solid design is a lot easier than making it up as you go along. When To Start Ideally, you d start about six months before starting any MDM initiative, so that your new Data Governance group would 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 wind up with a failed effort to explain later. It s 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, organizational change, marketing communications, project management, you name it! Sample Organizational Model CEO A three level model can work well at a lot of companies: PRESIDENT SALES, MARKETING, SUPPORT PRESIDENT FINANCE EVP PRODUCT DEVELOPMENT 1. Data Governance Steering Committee: a crossfunctional, executive level group that makes policy decisions, provides funding, resolves escalated issues, and provides strategic direction. MARKETING GPO Marketing Data Desk Team SALES GPO DATA GOVERNANCE VIRTUAL TEAM CHANNELS SUPPORT GPO GPO Sales Support Data Desk Team Data Desk Team FINANCE GPO Finance Data Desk Team IT GSO Application Manager Configuration Team 2. The Data Governance Office (DGO) is charged with coordinating data governance (strategic) and stewardship (tactical) activities. It manages communications from the Steering Committee to all stakeholders. Marketing Business Community Sales Business Community Channels Business Community Support Business community Finance Business Community IT Operations Community 3. One or more tactical groups (Data Stewardship Teams) in each functional area and geography (if needed), which provide guidance to individuals with data stewardship responsibilities. What s most important is to have the organizational structure that will work in your company. COLLABORATE 12 OAUG Forum Copyright 2012 by Hub Designs Page 5 of 11

6 Data Governance Steering Committee The Data Governance Steering Committee serves a function similar to the U.S. Supreme Court. Issues escalated by the Data Governance Office are resolved by the Steering Committee. The Steering Committee probably won t make much policy directly (except on an exception basis), except where the issues are serious or the dollar amounts are large. For example, where a new policy may be compliance-related and involve large penalties, the Steering Committee would at least review (and probably sign-off on) the new policy. Similarly, establishing the overall Data Governance organization and its place in the company, as well as its Year 1 funding and annual renewal, is probably a matter that will be settled by the Steering Committee. The ultimate power in the corporation to make sure Data Governance policies are being followed, and to resolve issues escalated from lower levels, resides in the DG Steering Committee. But that group will, to a large extent, rely on the Data Governance Office to make it aware of when policies are not being followed, and when escalated issues need to be resolved. This group will usually include senior level business owners and the overall executive sponsor(s) for data governance, and operates strictly at strategic level. The key things at this level are: getting the right executives involved, and that once it starts meeting, it accomplishes some useful things. Otherwise, the executives will feel like they re wasting their time when they do meet, and the group will quickly disband, usually cancelling the data governance initiative as well. Data Governance Office The Data Governance Office is similar to the Executive Branch of the Federal Government. It s heavily involved in making data policy. It oversees the business data stewards and the IT stewards. The DG office is similar to a Program Management Office (PMO) and usually includes the global process owners (from the business) and the global solution owner from IT. The DG Office operates at the tactical level but needs to be comfortable managing up (to the strategic level) and down (to the operational level). The DG Office is critical to having a successful Data Governance initiative. Creating the right Data Governance Office can make or break your entire effort. Who ll Head Up the Data Governance Office There s a tendency in these job descriptions to be a little over the top. Some companies are 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 recently: Data Quality Director Required - Must Possess Powers of Invincibility. Vincent McBurney wrote an interesting article titled Data Governance is Career Suicide. 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 a strong leadership style and the delegated authority of the executives on the Data Governance Steering Committee. Data Stewardship Teams The third level of the Data Governance Organization is similar to the Legislative Branch of the Federal Government. It works with the Data Governance Office in making data policy, and in carrying it out. COLLABORATE 12 OAUG Forum Copyright 2012 by Hub Designs Page 6 of 11

7 These teams need to be from the business side in order to know the ins and outs of the data, but the teams should include IT stewards as well, to assist with the technology aspects of data governance. There are usually data stewardship teams from various functional areas and geographies. They work at the operational level but selected people may be representatives to the Data Governance Office (i.e. they ll primarily be data stewards but they may attend meetings of the Data Governance Office, even if they re not formally members of the DGO). This is so they can adequately represent the stewardship level on issues they are bringing to the Data Governance Office for resolution. These people spend time responding to issues raised by others; monitoring data quality and developing new data quality and business rules; but their real skill set is collaboration with multiple organizations at multiple levels. Where Will Data Governance Live? After you ve dealt with some basic, design-level questions: why govern master data at all (your program s purpose and vision), using a data governance maturity model to assess where you re starting from, developing a strategic roadmap for data governance at your company, building on that roadmap to design your data governance program, when does it make sense to establish your data governance organization, sample organizational models you can adapt to your company, then it s time to start digging into the more pragmatic, implementation-level aspects and start getting your hands dirty. One of the very first questions that usually comes up is where will data governance live. Where in the enterprise will the new data governance organization reside? Make sure it s in the business, not in IT. This may not be a popular position, because the initial impetus for data governance may have come from IT, and IT may be pushing for the data governance organization to be part of IT. But in order to be successful, the business needs to feel accountability for data governance, otherwise the complex issues of data ownership, data quality and data integrity will always be someone else s problem (that is, IT s problem). Who ll Pay For It? The next question that will inevitably come up is, who ll pay for it. How will the new data governance organization be resourced and funded? This is where the rubber really meets the road. You ll see your previous efforts at getting executive sponsorship pay off here. This usually gets worked out behind closed doors, but you should have a proposal (worked out ahead of time that everyone agrees to) that you can bring to the table, so the executives involved have an easy meeting instead of a big fight on their hands. The funding question is definitely influenced by the where will data governance live question, since it may be funded out of that group s budget. But it s also reasonable to do allocations or charge-backs to all of the parts of the enterprise that data governance is serving (usually the entire enterprise). COLLABORATE 12 OAUG Forum Copyright 2012 by Hub Designs Page 7 of 11

8 And make sure the funding is on a continuing basis, not just a one year commitment, since data governance itself is an ongoing activity, not just a one or two year process. One thing that helps a lot in future budget battles is if the data governance team has a dedicated place to track all of the benefits (revenue increases, cost savings, compliance improvements, etc.) that it delivers, with the business group it worked with signing off, to help fend off the inevitable funding renewal difficulties. If you can point to $x million in increased revenue and $y million in cost savings, it will be much easier to win your annual budget renewal each year. Remember, it s always going to be what have you done for me lately? OK, I Took This Job Now What? There are two big issues for any company creating a data governance organization: finding the right executive, at the right level, to be the executive sponsor and champion, and finding the right VP, director or manager to head up the new data governance office. In Organizing Data Governance for Success, I wrote about the role of the executive sponsor and champion. And in Data Governance: The People Make It Real, I wrote about the role of the person heading up the data governance office. Once those two key individuals are in place, things start to fall into place. But if you are the person charged with heading up the data governance office, once you ve started forming your new group, what should it be doing? First, do an independent survey of your situation so that you know from where you re starting. Where exactly is the enterprise on data governance today? Don t take anyone else s word for it. If you re going to be steering this ship, you want to know your exact starting coordinates. Second, develop a sound data governance strategy for the company. This may take a little time, and you ll be getting some pressure to start taking action. But don t fall prey to the ready, fire, aim temptation. If there isn t a good strategy in place already, or you don t agree with the strategy, take the time to straighten this out. A journey of a thousand miles begins with a single step, but if you start everyone marching in the wrong direction, you re just going to have to back up and start over later on. Third, focus on creating some early wins and value. Start a quick wins program that works with the business owners to find out their biggest problems. Is there a problem in the warehouse where 40% of their shipments are being returned due to address data quality issues? Are salespeople entering duplicate customer records because the commission policy rewards them more for sales to new customers than for existing customers? Does the CRM system suffer from a lack of edits and validations when entering new customer records? Most of these may be fixable in a relatively short time, and allow you to point to some successes even while the data governance program is still fairly new. Fourth, define and operationalize your data governance processes. As you move from design to implementation for the data governance organization, you ll be defining business processes for the data governance lifecycle: Define the company s data governance policies Ø Author or update policies Ø Analyze the impact of those policies Ø Approve and publish (preferably using a Business Process Management tool) Implement data governance policies Ø Communicate policies to all affected parties Ø Translate into business rules (preferably using a Business Rule Management System) Ø Deploy business rules COLLABORATE 12 OAUG Forum Copyright 2012 by Hub Designs Page 8 of 11

9 Enforce data governance policies Ø Handle policy violations Ø Manage remediation Ø Measure performance against goals (using a Data Quality tool) The most important point is that data governance must have teeth in order to be more than a paper exercise. Confirm that you have the support of the Steering Committee to enforce policies, and expect some resistance at first, until the governing aspect of data governance sinks in for people. Fifth, build out the rest of your Year 1 data governance organization. Hire the rest of your team, keeping in mind that you should look for as many people as possible within the company, since they will already know the business. Sixth, don t go too far into Year 1 without starting to plan for what your Year 2 data governance organization will look like. It will probably be quite different from Year 1, not only in terms of size but also in terms of structure. You ll want to adapt to the changing needs of the company and take advantage of lessons learned internally and best practices picked up externally. Seventh (and this is an ongoing process), continue to evangelize data governance to the rest of the enterprise. Create an outreach / education program that you and the other members of the data governance team can carry out, in a continuing series of workshops across silos and across IT and business. This will raise awareness of the impact of people s data outside of its original purpose. Eighth, be sure to document and communicate your progress and wins to the enterprise. A series of newsletters and internal blog articles are probably the best way to get the word out, plus participating in company-wide town hall meetings to let people know what the new data governance organization has been up to, and how you ve been able to help the company, even in your first few months. If you ve taken on the responsibility of heading up the company s data governance office, these points should give you some idea what your new group should be doing on Day 1. Data Governance Technology Data governance mainly involves People and Process, but Technology is an important enabler. Make sure you've got the Five Essential Elements covered: an MDM hub (either already implemented, in the implementation process, or at least planned for the future via the strategic roadmap), adequate data integration technology (an ETL tool by itself is probably not enough, you'll want a service-oriented architecture or service bus based approach to handle real-time or near realtime integration) a data quality tool of some type, with strong profiling, standardization, matching, de-duplication, and "golden record" creation functionality third party enrichment capability, particularly if you're dealing with the Customer domain - don't put this off to a later phase, the information you don't have which is available from a third party provider like Dun & Bradstreet and Equifax (for information on businesses) or Acxiom (for information on consumers) can be invaluable in answering the questions the business has COLLABORATE 12 OAUG Forum Copyright 2012 by Hub Designs Page 9 of 11

10 technology to facilitate data governance, including tools for metadata management, data modeling, information access and security management, workflow and business process management, and policy management. You may not need to buy all of this right away, but Data Governance for a large enterprise is a big task, and anything you can do to automate routine tasks will usually have a positive ROI. Don't try to do everything using Excel spreadsheets, Word documents, and . That type of "least common denominator" approach is a false economy. Technology won't ever be a silver bullet for Data Governance (about 80% of the work will be with organizational, cultural, political and business process matters) but don't ignore it altogether; it can be a powerful "force multiplier". It's also a good idea to set up a "data help desk", which allows anyone in the company to notify the Data Governance Office of a new data related issue. This type of case management capability will help ensure that issues aren't falling through the cracks. Some other technology capabilities you may need (in some form or other): 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. And the Data Governance Organization is definitely going to need lots of IT support I'm always amazed how many companies try to do master data management and Data Governance without one or more of the above capabilities. If you've got your organization built out, your processes designed and in place, some new technology fitting in to automate labor intensive tasks, and your information is starting to get some dedicated scrutiny from the centralized Data Governance Office and the distributed data stewardship community, you're going to be well on the way to a solid Data Governance implementation. What We re Really 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? This is not the usual way of doing things for most company s IT organizations. We need to work hard to get rid of the us vs. them mentality that is prevalent at many companies. It may be necessary to blend the IT people for the DG initiative into the business. The key is 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. Which Brings Us Full Circle To be successful, MDM and DG need an approach that balances: People: political and cultural change. We started out by saying that data governance is more political than technological. Hopefully you now see some of the reasons for saying that. Process: new processes for governing data, which allows you to streamline existing processes in the enterprise for creating, reading, updating and deleting data. COLLABORATE 12 OAUG Forum Copyright 2012 by Hub Designs Page 10 of 11

11 Technology: a broad spectrum of enabling technology. Information: don t forget it s all about the data. I ve worked with people on MDM and DG who seem to consistently forget to look at their data. Why Does All This Matter? Companies Need to Change In Order To Survive Companies today are under relentless cost pressure, coupled with fairly slow growth on the demand side. There is no room to lose and then replace existing customers. Most organizations are juggling multiple transactional and analytic applications across corporate, regional and local areas. And customers demand faster and more complex responses from organizations. All of this leads 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. About the Author Dan Power is the founder of Hub Solution Designs, Inc., a global consulting firm specializing in master data management 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 is the publisher of the Hub Designs Magazine, a widely read blog on MDM and data governance. Follow Dan at twitter.com/dan_power, and join the MDM Community at mdmcommunity.ning.com. COLLABORATE 12 OAUG Forum Copyright 2012 by Hub Designs Page 11 of 11

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