MDM still has the potential to meet many critical needs in this data-rich environment, but only if it can keep up with changing times.
Let’s start with the obvious: We’re already drowning in data, and it just keeps coming. We need to gather, store, collate and analyze it, because we know it contains intelligence that can guide ongoing and future initiatives. One invaluable tool in that effort is Master Data Management (MDM): It brings together different policies, standards, mandates, processes and even technologies underpinning the core data to provide a single point of reference. That makes it ideal for companies submerged in data and looking to make better use of it.
So why isn’t that happening? Why does MDM seem like a legacy discipline? And what can we do about it?
One obstacle is the sheer dynamism of the industry. Exciting as it is, the constant emergence of new technologies, each enabling more data in different formats, makes it inevitable that some traditional technologies and processes supporting MDM just can’t keep pace. It can actually have the opposite effect: It devours IT resources and hurts other business initiatives. That’s one reason why many organizations have deployed multiple MDM programs, leading to exactly the kind of information silos that this advance was intended to eliminate.
Meanwhile, the data (and the number of data formats) keeps mounting, which means the critical task of developing actionable intelligence from different data sources—such as, for example, identifying key relationships between different customer subsets—gets more difficult each passing day.
Here’s a different perspective on the problem, and perhaps a path forward.
MDM originated in the enterprise arena, with extensions for different verticals, like life sciences. This is a world where untangling relationships between healthcare professionals and organizations—each with a complex web of plans and players—can provide a significant competitive advantage. However, mastering that massive dataset to gain a single view of the customer or product just isn’t enough: It requires comprehensive access to data from all the different areas of the organization, and a holistic view of the entire business to support multi-channel or omni-channel strategies. Meanwhile, there are other complications. We’ve got regulatory mandates to worry about, and data assets represent a potential revenue stream, to name two.
This is just one reason why so many MDM-only tools can’t do the job. They need to be supplemented with software programs that better enable data quality, enable governance, ensure self-service BI and analytics, etc. All that is so enterprise, but now consider the consumer angle. It’s easy to dismiss any similarity between the relative trivia of, say, LinkedIn or Facebook and the complexity inherent in industry-specific MDM systems, but that’s really the point.
Those services and others like them provide effortless access to—and management of—all types, not just master data, in the form of profile information, as well as transaction, interaction, and social data, all within the same application.
In fact, they uncover rich relationships and connections across people, products, and organizations, while using the information to predict and recommend the best course of action.;
