5 of the Worst Practices in MDM

5 of the Worst Practices in MDM

Today, businesses use data to derive insights that help them reduce costs, improve business process execution, increase competitiveness, and grow the bottom line. To keep pace with changes in the business environment and make informed decisions, these organizations need accurate data. That is why master data management (MDM) is critical to the tactical and strategic needs of a company. MDM, which comprises technologies and processes for streamlining data management across multiple systems, is a key cornerstone for trusted data.

But the route to successful MDM implementation is not always straightforward; it is full of dead ends and detours. As business risks and uncertainties continue to evolve, so should how we manage data. Each year, industry leaders, which include guest experts, Gartner analysts, and peers, come together through the Gartner MDM conferences to discuss issues concerning data and analytics. One of the things discussed in these conferences is best practices in MDM.

To design a successful MDM program, you must know where mistakes can happen. Some experts suggest that the key to successful master data management is focusing on the best version of the truth. In this article, we will discuss the five worst practices in MDM and how to avoid them.

1. Omitting the business case

For MDM to work, it must consider the business value and needs as well as the business users and other stakeholders the program affects. If you do not identify these critical elements while designing a business case for your MDM initiative, you will never get buy-in. Your business case needs to answer the most common question, ‘Why are we doing this?’ and how will the master data management tackle major problems?” By talking to business users, you will know where the needs and major problems are, and how to measure the value of MDM. If you can solve critical issues through the initiative, you will simplify MDM expansion. Linking MDM projects with organizational goals and strategies will become easier.

2. Failure to identify a champion

Some businesses start their MDM initiative without first identifying the sponsor. For MDM to be successful, your organization needs to identify a senior executive who will spearhead the process. Most people tend to assume that an MDM program is best handled by IT. Sure, IT is a critical partner that takes care of the infrastructure needs, but leaving it to lead the process will most likely derail the project. MDM touches on many practices and business processes that cut across different departments. In most cases, the change is disruptive, so a direct involvement of a top executive is necessary to gain buy-in and preserve the momentum. As you know, mid and lower-level staff may not have the political standing or clout to institute major organizational change over a long period.

3. Failure to take into consideration the organizational and cultural change

The unavoidable corporate politics together with organizational and cultural changes that stem from MDM initiative can either make or break the project. The nature of MDM means you will reduce data silos by merging them into a standardized master file. This will involve scrutinizing data ownership and cross-functional processes, which will most likely introduce interdepartmental challenges. Given that resistance to change is part of human nature, marketing and communicating to various constituents and stakeholders is crucial for successful implementation of the MDM project. Identify potential influencers among the various categories of users who will support you.

4. Adopting a one-dimensional approach to MDM

For master data to transform your business, you need to take a balanced approach to MDM. Where most people get it wrong is focusing on technological improvements at the expense of processes and people. A successful MDM initiative takes into account the processes and politics, understanding the people, practices, and technology as they relate to the MDM project.

5. Failure to establish strong data governance

One of the best practices that have been identified by the Gartner MDM conference team is having an effective governance structure. Lack of proper data governance will, therefore, impedes the success of an MDM initiative. You need to establish data governance practices, responsibilities, and processes.

Proper planning and consultation are important when designing an MDM program; it is important to know that its success will be affected by the goodwill of your stakeholders. Even as your implement, watch out for the worst practices in MDM highlighted in this article.

Author Bio: Douglas Pitassi is a freelance writer and small business blogger.

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