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Will Data Content Managers Displace IT in MDM?

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For as long as I can remember, master data management (MDM) has been a task for the IT function of an enterprise. Typically, MDM has been assigned to the data management specialization within IT. However, there are now indications that another specialized area is on the rise in a wide array of enterprises, and this area seems to be set to take the leading role in MDM.

I call this emerging area data content management (DCM), after a suggestion made to me earlier this year by Professor Allan Grody. DCM is a competency that is not merely interested in the functionality required to manage master data, but is also deeply concerned with and knowledgeable about the physical data values within master data and the relationship of these values to the process and informational needs of the enterprise. This enables DCM to perform a number of important tasks for the enterprise that IT cannot.

One of the critical problems of MDM is that it has complex changes that cannot be automated within any computerized application, but rather require human intervention. For instance, when the Euro was introduced, it had to be updated manually in currency tables.

Such updates require a professional staff that is aware of the changes going on in the general environment, can understand them in business terms and can translate them into updates in the MDM applications available. IT, including data management, is incapable of performing these tasks. Nor would it want to, because IT would see these tasks as belonging to “the business” and clearly out of its scope. After all, IT does not update “business data.”

The domains of data that comprise master data require special knowledge. It cannot be expected that an individual can move from processing client data, including hierarchies and linkages to corporate accounts, to handling the product lifecycle or to managing corporate actions that affect financial instruments. Each of these master data subject areas has its own structures, rules, taxonomies, constraints and peculiarities that must be learned. Each one of them will also require different handling within the (often inadequate) MDM applications available in an enterprise. It is these needs that DCM staff can now meet.

Another important trend is that data is being bought and sold, or otherwise exchanged among enterprises. Data has become a business. Companies such as Reuters, Bloomberg, Dun & Bradstreet, Standard & Poor’s and a host of others generate revenues by directly selling data - much of which is master data. Because money is being paid for data, there are contracts that govern the use of the data in the enterprises.

These contracts limit ways in which the data purchased by an enterprise can be distributed, published and generally used within the enterprise. Someone has to take responsibility for managing the contractual arrangements and monitoring compliance with them. Again, this is falling to DCM staff. They “know” the data, and they know who is using it - or at least they try to find out. One of the things they would like to know is what data flows exist in the enterprise that might carry the data governed by contractual arrangements. IT, having implemented these flows, would be expected to have this knowledge, but it does not.

The contracts also have to be renegotiated periodically, and renegotiations must be based on the value the enterprise obtains from them. Understanding the value of physical data to the enterprise is thus a vital task for DCM, because it has to determine a number for each contract. This is hardly a traditional area for IT.

Data quality is a difficult area for IT. It is often defined as “fitness for use,” which is an extremely vague definition. IT is fine with certain categories of data quality that derive from technical aspects of data management, such as data ranges and referential integrity. However, there are much deeper issues in overall data management that are well beyond anything that can be represented in a data model. For instance, establishing the provenance and enabling the curation of data sets in exploration and research departments of many enterprises often requires creating and enforcing important business processes. Without these processes, data quality will be at risk. Yet, the design and implementation of these processes is not the same as building technical infrastructure (though some may be involved).Therefore, DCM professionals tend to take the lead.

Maturity of DCM

Fortunately for IT, DCM is not yet aware of itself as a general function within an enterprise. DCM staff appears to see themselves as aligned to the particular master data subject areas they are working with. However, if the problems of data continue to gain visibility, senior management will make the connection at some point. If there are any potential synergies across the management of the master data subject areas, senior management will become very interested indeed. IT is always going to view its role in terms of building technical architecture that delivers functionality of some kind to manage data without any need for IT staff to understand the data content. Ultimately, this limits what IT can do for the enterprise. Data content management, by virtue of knowing the data, will always stand closer to the business users than IT can. As MDM evolves, therefore, any clash between DCM and IT will likely be decided in favor of the former.

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