Gauging data governance

For several years now there have been efforts to improve the consistency and quality of master data — the customer, product, asset and location information that is shared around an organisation.

Without consistent data, large firms struggle to measure their business performance properly, as no one can agree on what the correct numbers should be.

An enterprise software market has sprung up to support these initiatives, though they are inherently large-scale, lengthy projects. But it is clear that it is exceedingly difficult for such projects to be driven from the IT department.

By its nature, master data stretches across business domains, and so at some point hard questions have to be asked about which is really the definitive product code classification, or materials master, or list of strategic suppliers.

IT simply does not have the authority to make business departments change their way of doing things, so getting the business to take back ownership of their data is crucial. The name given to the activities associated with business ownership of data is data governance.

Data governance is not a technology, but, according to the Data Governance Institute, is “the exercise of decision-making and authority for data-related matters”.

It involves business people sitting around a table and agreeing who will be the ultimate authority for disputes about the definitions of key business data, and who will be responsible for ensuring its quality and its uniformity throughout an organisation.

Unfortunately, there is precious little hard data available about what people are actually doing with such initiatives: how big are they, do they work and what causes success and failure?

Late last year my organisation, The Information Difference, with the Data Governance Institute and a panel of global companies, carried out a project to help improve this state of affairs.

We defined a structure of data governance activities and asked firms to share their experiences and data within this framework.

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