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Page 10


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TechWaTch


Understanding the Benefits of Data Governance


By Christophe Marcant, Senior VP of Strategy and Communication, Stibo Systems M


anufacturers are constantly looking to create trusted mas- ter data, a key element of


true business optimization. Organiza- tional data, such as product, asset, lo- cation, supplier, and customer infor- mation, are only valuable when they are accurate, complete, consistent, and shared across an organization. Achieving the trusted master da-


ta necessary to support today’s busi- ness decisions is difficult, because most manufacturers deploy their data across multiple systems that continu- ally aggregate, consolidate, store and maintain a tremendous amount of op- erational information. Further complicating the mat-


ter is that this data has the potential to change frequently. In most organ- izations there are few clear-cut roles, processes or tools for protecting or enhancing that information as it moves across the enterprise. As a result, information often


becomes replicated and fragmented, which leads to duplicate, conflicting,


incomplete, and erroneous informa- tion that hinders business respon- siveness and decision-making. As the challenge to manage crit-


ical organizational data grows, man- ufacturers are embracing data gover- nance (DG) strategies to protect the integrity of their valuable enterprise assets, and to optimize their master data management (MDM) and prod- uct information management (PIM) initiatives. Data governance is in- creasingly important as data volume grows and organizations of all sizes are challenged to maintain a single version of the truth for each of their critical data domains.


Signs of a Data Governance Issue Data governance involves orga-


nizational change, and because of this, the value of the data and the level of risk a manufacturer is willing to take is likely to shift even after it is rolled out. In fact, many organizations only assess themselves once a year, which isn’t frequent enough to be able to re-


act to, and change, the organizational controls that need adjustment. Organizations know that DG can


add real value to their business, but it is often difficult to sell internally. This is because concepts like technical and business-related metadata, data qual- ity, information models, data owner- ship, and the associated opportunity costs are not always immediately un- derstood. As a result, they often lack funding for implementation. Data governance has existed


since the adoption of IT systems in the 1960s. But, where the initiatives were previously driven by IT with a technical focus based on programs, data governance is now typically ap- proached in a more structured man- ner with a dedicated team and a high degree of interdisciplinary involve- ment. Today, data governance is no longer just hype, but an established term in the executive lexicon. However, that doesn’t mean


that data governance programs are always successful. On the contrary, a lot of programs have failed. There are several key reasons:


3D-MID Prototyping Three-dimensional circuits


Digital Transformation. Practical- ly every successful business has built its success on data. Digital tools are disrupting the business environment and require significant changes in operations, communications, and supply chains; and these changes will only accelerate. The adoption of new direct-to-


consumer sales channels, the abun- dance of product options and the emergence of mass personalization have increased consumers’ expecta- tions and price sensitivity, leading to less brand loyalty than in the past. Data governance can make the digi- tal transformation required to over- come these obstacles achievable.


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The General Data Protection Regulation (GDPR). From May 25, 2018, the European Union is setting new regulatory standards for how businesses that process personal da- ta of European citizens collect, store and use that data. Obviously, it will require a high


level of data quality and well-organ- ized data processes to comply, mean- ing that GDPR will be nearly impos- sible to implement without an an- chored data governance program.


Data Privacy. Data privacy is be- coming a huge competitive factor and a major driver for organizations. To- day, manufacturers are collecting in- creasing amounts of personal informa- tion about consumers, most of which is vulnerable to threats, accidental dis- closure and theft, due to failure in ap- propriate design and usage. This comes with a heavy price


tag, as any negative publicity will have an adverse effect on the compa- ny’s brand, not to mention the bot- tom line. Protecting an organiza- tion’s reputation is the most signifi- cant risk management challenge these days.


Smooth Data Governance Comprising both people and


processes, a sound data governance program includes a combination of people, or in this case a governing body or council, a defined set of pro- cedures, and a plan to execute those procedures. A successful data governance


strategy involves many factors, includ- ing careful, up-front planning com- bined with appointing the right people and the appropriate tools and tech- nologies. This foundation of quality and trustworthy data, combined with an active and engaged group of users, is the hallmark of a company using a governed approach to MDM. Start with people, as careful


consideration needs to be paid to en- sure proper data ownership, since in- consistencies will undoubtedly occur as data elements and types are shared among business users and across data silos. Designated data stewards, who


are the people responsible for the man- agement of the data and the respective attributes, are vitally important to the long-term success of the data gover- nance program. Be sure to create and leverage a data governance team to create a solid data framework that ad- dresses inconsistencies across different departments and adheres to the data quality needs of the organization. Next, determine a set of data


governance policies and procedures. Start by building a clear vision and scope for the data governance initia- tive, to ensure that the organization is able to meet its expectations. De- fine standards and assign business rationale as to why each exists. Out- line the benefits that can be achieved and what level of quality should be reached to realize the benefit. Create metrics that show whether benefits are being realized. Finally, employ tools, such as


MDM, to create higher-quality data and much-needed visibility into data lineage. According to an Aberdeen re- port, companies combining MDM and governance are 2.2 times more likely to see year-over-year revenue


growth greater than 20 percent. Contact: Stibo Systems, Inc.,


3550 George Busbee Parkway NW, Suite 350, Kennesaw, GA 30144 % 770-425-3282 E-mail: chrm@stibosystems.com Web: www.stibosystems.com r


August, 2017


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