Creating Collaborative Partnerships

One thing to know up front is that for all the recognized end-state benefits and expectations associated with implementing effective MDM practices, achieving this can be a slow and deliberate process that needs to build on itself and will require some out-of-the-box thinking.

Can Your Current IT and Business Model Effectively Support MDM?

Data management initiatives, just like many other IT and business initiatives, have historically been subject to the imbalance between expectation and delivery—or what we all can relate to as an oversold but under-delivered project. Too often, we see that after the expectations are set and the go forward decisions have been made, there seems to be that reoccurring dynamic where the project becomes short on the expected resources and timely deliverables needed to achieve the end-state solution. We then start to see compromising that results in cutting or back logging of key pieces of the project, often causing ill will to emerge between the business and IT involved roles. While this scenario can occur across many types of business initiatives, delay or failure to deliver key aspects of a Master Data Management initiative can be particularly impacting because of the pervasive nature of master data across the business model.

This reoccurring dynamic is rooted in the inherent nature and ebb and flow associated with a traditionally stiff model between IT and the business. That said, we also recognize that this model has a clear purpose and serves a vital role in a company. For many reasons, there absolutely needs to be a strong charter for IT with clear distinctions and jurisdictions from the business organizations. However, there is a tendency to repeatedly overstuff this model to a point that neither the business nor IT can address many important initiatives that are pervasive and time sensitive. We have probably all seen where some initiatives and business practices won't or can't survive if constrained by this traditional model. For these cases, it's imperative that the business and IT can move away from the constraints inherent in this traditional model. MDM, and particularly the Customer MDM focus, is a poster child for this movement.

With just a bit more flexibility injected into the business and IT dynamic, a well-implemented Customer MDM initiative can be achieved that will definitely begin to stand on its own merits as a valued ongoing enterprise practice. Treat this initiative as an emerging business practice that needs nurturing. This is why we do not recommend that an MDM initiative be launched as an IT project bound by fixed time and delivery expectations. As we have been alluding to, a Customer MDM initiative is very likely to require some initial cultural and political changes to enable the cross-functional collaboration and investment required for this model. In general, implementing MDM is not just about implementing policies, tools, and processes; it also requires understanding and recognition of the softer and more intangible elements of a company's ecosystem.

The Acceptance Factor

Those who are familiar with the Change Acceleration Process (CAP) equation “Quality × Acceptance = Effectiveness”¹ will appreciate the Acceptance factor. In other words, a quality improvement strategy, in combination with a cultural and organizational adoption strategy, is critical to the success and effectiveness of an MDM implementation. As Tony Fisher, president and CEO of DataFlux, points out, “Data Quality and data governance should never be considered a one-time project. A quality culture must be established as an ongoing, continuous process.”²

A well-targeted MDM practice also needs to be a well-grounded, ongoing discipline positioned broadly enough to capture the notion of Master Data Management. Getting the acceptance and focus needed for this is the first challenge. Then, expect that maintaining MDM practices will be an ongoing exercise in creating and building collaborative partnerships in the enterprise data space. Even though the phrase collaborative partnerships may sound redundant, often in cross-functional initiatives teams are thrown together as business partners, but they still maintain a level of resistance and self-interest that can impede breaking down the organizational or political barriers that work against MDM practices.

To the extent that with this book we offer guidance, experience, and techniques for implementing MDM practices, we also know that an MDM initiative will have factors and challenges unique to a company's business model and line of business dynamics. A large part of MDM success lies in understanding that uniqueness and finding creative and collaborative approaches to address it.

Business Access to Data

A key ingredient in a successful MDM partnership is to recognize the need for appropriate business role access to data. In Chapters 4 and 5 we elaborate further on this topic, but early on, when the concepts and agreements around ownership and partnership are forming, the positioning of the data steward role needs to also be positioned within the MDM model. Consider how and where data stewards will operate, what authority they should have, what they can have access to, and how they are formally recognized in the company. There may already be some semblance and recognition of data steward functions as part of other business or IT job roles, but this can be fuzzy and these data steward functions are often just a secondary responsibility, which can easily be subjugated when attention is required for the primary job responsibilities.

MDM focus will suffer if the work and responsibilities are just tacked on to existing job roles that are already loaded with other responsibilities. If the data steward functions will be incorporated into other existing job families and roles, just be sure to fully recognize the time and skill sets needed to address the MDM needs, and ensure this work can be regularly performed by the individuals. Ideally, a clear and distinct data steward job family should be created in the business that is not competing with IT or viewed negatively as shadow IT. The business-oriented data steward role is a necessary complement to the IT roles in the overall MDM model. Not recognizing and sufficiently enabling this type of data steward role will significantly hinder the execution of the MDM practices by forcing too much expectation for MDM solutioning and delivery through the IT process or with other business roles that are not adequately skilled, resourced, or empowered.

Consider two general observations that most everyone can relate to:

This backlog or lowering of priority translates to the project sitting in a queue and probably means eventual loss of momentum and business interest, or possibly forcing the project to be directed into a more expensive path using consultants or contractors. This is not to suggest that you should try to circumvent the IT engagement path for the implementation of Customer MDM tools, infrastructure, or solutions that should require IT to review, design, and deliver. But there are many aspects of implementing Customer MDM that we discuss throughout this book that can fully or at least largely be handled on the business side by skilled data steward roles and teams who are well versed in the business process areas and have authorized and controlled access to certain data.

Coordination of MDM Roles and Responsibilities

Value and purpose of the MDM roles and responsibilities needs to be recognized early on during the data ownership and partnership discussions. Spelling this out and planning for how these roles will coordinate with other business and IT roles will take any conflicts or jurisdictional issues out of the debate and enable the data steward functions to more formally thrive in a company's ecosystem and play a vital role in the MDM process and governance model. Figure 2.2 illustrates how these roles and relationships become the partnerships and executing dynamic of data ownership.

Figure 2.2 Customer MDM Roles and Responsibilities

A well-defined and coordinated set of roles and responsibilities between the data governance and data steward roles becomes the focus point for the sponsorship and ongoing execution of MDM process. This data steward team will not only become the subject matter experts who have sufficient tools, skills, and responsibility to manage the MDM process across the enterprise, but also can work with specific functions to assist with many types of data analysis, standardization, or cleanup initiatives that are important to the LOB area along with benefiting many other customer data stakeholders.

For example, if addressed correctly, the reduction or elimination of data duplication can have a very positive cross-functional benefit, but it needs to be carefully planned and executed due to the widespread sensitivity around eliminating customer records, with the merging of these records and the associated data, or with the linkage of this data with other data such as contracts, install base, service data, hierarchies, and so on, which all can be affected in the process. The planning and execution of de-duplication and record merge activity is much more than simple matching logic and backend clean-up actions. It will require not only a thorough study and testing of the inherent functionality and configurable rules available for actually performing duplication cleanup and record merging, but also will require the creation of a surrounding business process that addresses the various business rules, constraints, exceptions, manual research, timing, and support that are all elements of implementing a cross-functional data management process.

Getting this type of a data management process right and ensuring that all the stakeholders are appropriately engaged is what will create the underpinning needed to drive a common view of the customer and where the source of truth concept is actually rooted. We'll address these subjects in much more detail in the subsequent chapters, but it's important to recognize that it's through this type of collaboration and partnership that the LOB executives will appreciate the enabling value that the MDM practice and its core team bring. This becomes the bond for how the top-down and bottom-up approach to data management stays together.