Part 4 of a six-part series on the “New Age of Master Data Management”
by Julie Hunt
Master data management and data governance have always been about business. However, there has been a history of MDM implementations putting too much emphasis on technology, and less time into over-arching business aspects. For successful outcomes and continuous improvement, the ongoing participation of various business roles is an essential element of MDM strategies and activities. It takes ‘everybody’ to ensure optimal data management processes that bolster important business activities.
Organizations need to make data available to more people, which may mean expanding master data management participation across more of the organization. With additional business personnel involved, new ways to use master data will emerge that will benefit more initiatives, strategies, and decision-making at multiple levels. Data consumers may also exist beyond the organization: partners, business ecosystems, third-party developers, and managed services providers.
Data quality is the cornerstone of producing reliable data. Poor data quality prevents organizations from realizing full value from data and can cause serious problems that derail important business initiatives. Business domain knowledge is a critical part of ensuring data credibility. And, of course, it’s business people who own the understanding of how data is used, for which processes, and what future uses may be in the offing.
For all of these activities, business roles may need access to the appropriate capabilities in MDM software solutions — but will come with different levels of technical proficiency.
Data Governance Leads the Way for Business User Inclusion
Like many well-defined MDM initiatives, data governance approaches that focus on business cases often better connect data management processes to necessary uses by different business roles. Data governance teams that are comprised of business and technical personnel can take advantage of an array of real world experience to improve processes and practices for tracking data ownership and governance accountability.
A collaborative framework (supported by software technology) is essential for successful data governance efforts. Such a framework can support both direct and indirect collaboration between business and technical roles, ensuring continuous work on defining and managing policies and practices, expanding and clarifying business rules, and tracking activities by all users to maintain compliance and accountability for information lifecycles.
Data management software that offers data profiling capabilities extends an important tool to Business Users across the organization. Business users can be included in data quality / data relevance processes through continual use of data profiling, to better examine the accuracy and value of data at any point. This is particularly important since a great deal of data comes with a short shelf life of relevance for business operations and initiatives.
Data governance is also a critical component of self-service approaches to data analytics, data integration and MDM. Self-service technologies are growing particularly to provide business users with access to more of the data that is essential for many activities in an organization. There is real risk associated with such self-service data platforms that must be addressed through centralized IT management and governance, which need to be in place to prevent piecemeal and poorly managed efforts scattered throughout the organization. Cloud-based self-service solutions are well-positioned for governance that maps into organizational data governance practices and policies.
|High Level Categories of Potential Users for MDM Technologies
Business User Access and Pervasive Master Data Management
Master data management appears to be on the threshold of becoming a pervasive platform. ‘Platform’ refers to both a key go-to initiative for data-smart organizations and to the integrated technologies that underpin master data management. Making MDM pervasive comes from a technology solution base that equips organizations to handle any data-driven scenario and support any business case, where business and technical roles take on innumerable data-related tasks. It’s a mindset of business and technology teams working together to use data to improve business results and competitive edge. This is aided by increased access, as appropriate, for less technical business users and for line-of-business developers who don’t have deep MDM expertise.
More MDM software vendors are recognizing that different user roles, especially business roles, comprise a major sustaining driver for the future of master data management. When vendors create role-based UIs and capabilities focused on less-technical users, the work they do also benefits the UIs and capabilities for the more technically adept. Organizations benefit greatly from better software design and the push to expand what MDM technologies can accomplish for diverse MDM activities, and for the people involved in completing them.
Of course, it takes very sophisticated technologies behind the scenes to deliver “simple” UIs that give everyday business users access to MDM and data governance capabilities. A lot of work must be done especially to build in safeguards to keep less technical business users out of trouble. To ensure that everyday business users do the work correctly and avoid serious missteps, each category of MDM activity has to be specifically defined, with straightforward guidance at every step.
If an MDM solution doesn’t provide pre-built objects, IT teams should take on the development of appropriate (and reusable) workflows, and other objects to enable business user participation, while building in safeguards. IT teams also have the responsibility to develop guidelines for business users, and then monitor and assist these users as needed.
Well-structured MDM initiatives can actually move certain tasks, like exploratory analysis, from technical teams to business roles. Business domain experts can take on responsibility for managing and validating business rules and data hierarchies that operate optimally for business needs. The right business roles can also create, validate and enhance approval workflows.
Drivers of New Age MDM
Tremendous potential exists for the increased participation of business people in MDM and data governance activities. Opportunities are opening up for business users to utilize powerful MDM software capabilities to explore, manipulate and access data without constant IT involvement. There is obvious advantage to organizations that fully support and empower business users to work more directly in many aspects of data management. When technical and business teams cooperate to engender improved collaboration, many MDM activities can be performed quickly and effectively, while ensuring that data governance practices and policies are upheld.
Organizations would be wise to develop management plans to assure that business users are empowered but also protected when working with MDM platforms. Cooperative action is also needed from technical and business teams to ensure that business user “protection” doesn’t inhibit necessary access and use of capabilities.
Executives in many organizations understand the value of trustworthy and relevant data for improved operations, productivity, competitiveness, and overall decision-making. But these executives still struggle with creating the strategies and organizational transformations that put usable data in the hands of many more business users. With data as a clear strategic must-have, organizations are obligated to do more to build out a comprehensive plan for business user participation and then actively work with teams to execute it.
Image source: Native American Weaving
Julie Hunt is the editor of Hub Designs Magazine and co-founder of the Hub Designs MDM Think Tank. Her “day job” is as an independent B2B software industry solution strategist and analyst. She provides consulting services for vendors to help develop successful strategies for buyers, customer and user experiences, solutions, go-to-market, and future direction.
Filed under: Best Practices, Big Data, Data Governance, Data Quality, Master Data Management, MDM, Politics, Strategy Tagged: Best Practices, featured, Master Data Management, MDM, Strategy