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Many organizations seem to be confused in how to implement a master data management (MDM) program. The MDM program is complex given that it truly is an enterprise level program especially if you are considering customer data. Not that product data is not a great challenge, however, customer data has greater touch points culturally, organizationally, externally, and application environments. While as an industry, we have been implementing MDM programs for over 2 decades, if you are just starting one in your company it can be a daunting and risky effort.
Over the last few months I have been asked a disturbing question by a few companies. “Which project do you recommend we do first, master data management (MDM) or data governance?” “We have pressure to do both.” My answer in all cases has been “why do you believe you need to choose. You should do both as one project.” The reality is that while you can implement a data governance program without doing an MDM project, you cannot implement MDM without doing a significant bit of data governance. The two efforts are not mutually exclusive. All business programs require good data, and all data needs governance.
I hope my answer has not surprised you. One of the most significant business use cases for data governance is the implementation of an MDM program. We see MDM used in two different types of business use case approaches to justify data governance. MDM can be a business offensive approach (to generate greater sales) or as an efficiency approach (to reduce the cost of operations). We often see the efficiency use case discussed and hence the Technology team is put in charge. Yet, to be successful business data governance activities must be included in the implementation. Let’s explore both use case approaches and how data governance can be leveraged for MDM success.
My first business glossary implementation was in support of an MDM “offensive” revenue generating business case. These use cases may include clarifying and consolidating the customer base, identifying customer touch points and customer interactions. Often this includes defining what each business unit considers to be a customer or prospect yet the objective is to identify, define and implement the data, people and processes that can generate additional revenue. This approach is generally driven by a business executive or even the CEO.
MDM can also be implemented to reduce the systems and cost of creating and maintaining product, reference or customer data. This is often the use case where an organization has gone through many mergers and acquisitions (M&A) over the years. The same customer may have the same data in many siloed applications that have point-to-point interfaces to share that data and metadata. About four years ago, I worked with an organization that had 72 separate applications that created and maintained customer data. Multiple applications performed the same business functions with what seemed like the same customer data but not necessarily with the same rules. We often see this use case driven by the technology organization as this use case is seen as a technology problem. Hidden in this use case is often a large problem with reporting and analytics quality and consistency.
So why should we consider the above MDM implementation cases as data governance use cases? Why MUST one do a bit of data governance in every MDM project? Let’s look at what resources, processes, data and metadata is needed to make the MDM project successful. And, of that what should be provided by your data governance processes and resources.
Simply an MDM implementation requires the following data governance activities:
Hopefully, I’ve made my point. There should not be a question of doing an MDM project or doing data governance. It is not a question of which but a question of when do we start the MDM project so we can further the adoption of data governance. It is not two efforts but just one that has significant benefits and value to the organization. Yes, MDM is more than data governance and data governance is more than MDM. But the MDM program should be considered as an implementation of both practices. And as always, stay calm and allow your data governance program to prosper.
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