In today's fiercely competitive global environment, companies can create an opportunity for tremendous added value by implementing a master data management (MDM) solution to standardize all their core corporate data elements across the enterprise to put timely, consistent, accurate and actionable information in the hands of management and knowledge workers. However, in the reality of dealing with entrenched corporate culture, the effective implementation of an MDM solution can often be mired in uncertainty and debate.
Interestingly enough, many of the barriers to effective MDM implementation are not of the technical variety; they are rooted in our very human quality of resistance to change. This month, I'm going to discuss some common challenges to MDM implementation, along with strategies to help mitigate them.
Define Business Value
The first challenge of MDM implementation frequently lies in defining the business value of the initiative. People often say, "The business has run for years without this kind of effort, so what is the benefit?" You might also hear, "The benefits of this are really intangible. How do you make a business case for it? Where's the ROI?"
These challenges can often be mitigated by more clearly defining the expectations about the MDM initiative up front. The value of effective MDM lies in its ability to deliver accurate, timely, consistent information for decision-making and corporate performance management (CPM). It is important to stress these benefits, but it is also critical to go further and provide ROI estimates. For example, you could provide an estimate that having more accurate customer data could lead to a 20 percent reduction in customer churn rates. The key is to define concrete goals and benefits up front and to measure results over time.
Appropriate Data Governance
Another challenge that companies often face when implementing an MDM initiative is concern that the structure required to provide ongoing governance of the master data will be too complex or ineffective. There's often a concern that the headcount needed to centralize data governance will reduce ROI. Another concern is that the governance function - if it is virtual - will not be empowered to do its job effectively.
There's no way to get around the fact that appropriate data governance has its costs. However, ineffective governance is much more costly. Data is a valuable asset, just like any other corporate asset. As such, it must be managed effectively, just like any other asset. The benefits of an effective date governance function can easily outweigh the costs. Concerns about virtual data governance can usually be addressed by implementing a dual governance model that relies on local management, which reports to a central function that meets regularly to refine and propagate standards.
The data governance function needed to manage the MDM implementation and enable its continued effectiveness doesn't need to be bureaucratic. To reduce the tendency toward bureaucracy, strive for simplicity in governance standards, policies and procedures. Provide a governance process that is understandable and usable - not some black hole that change requests fall down, never to be heard from again.
The third challenge that often plagues MDM initiatives is simple corporate inertia. Many companies are reluctant to implement MDM because of the perceived bureaucracy it creates. They are also hesitant because of the complexity inherent in rationalizing all redundant data at a reasonable cost, especially when data is often viewed as a conceptual rather than a tangible asset.
To overcome the belief that the MDM project will be too complex to be implemented effectively, practice good project management skills. Prioritize the data standardization process based on underlying business drivers. Data that is most important in driving the company should be standardized first. The process should continue based on an agreed-upon priorities list. It is also a good idea to tie standardization goals to employee performance criteria and compensation.
These are only a few of the challenges you might encounter in your quest to standardize and manage your company's master data. A key to meeting these challenges - and any others - lies in clearly defining expectations, goals, priorities and benefits. If you do that consistently, these challenges (and others) won't seem like insurmountable hurdles, and you can significantly increase your chances of reaping the rewards of effective MDM.
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