by Angela Guess
Andy Hayler, keynote speaker at last year’s Data Governance Conference, recently wrote an article on basic guidelines that any company can follow in order to create an effective master data strategy: “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.”
Seeing this problem Hayler’s organization, The Information Difference, along with a few partners conducted a survey of the data governance practices of 134 companies. The results showed (among other findings enumerated in the article) that, “Only a little over half (55%) of the organisations had a written statement setting out the objectives of their data governance programme… Data governance programmes required a mean of four (median two) dedicated staff, supported by an average of nine (median three) part-time staff… A scary 58% of organisations confessed to not having any form of risk register, with only six per cent having an effective register in place.”
Hayler and his fellow surveyors concluded that the companies with the most successful data governance programs had: “A data governance mission statement, a clear and documented process for resolving disputes about data, policies for controlling access to data, a proper register of business risks, effective logical data models for key business data domains, well documented business processes, regular data quality assessments, a documented business case for data governance, established a link between programme objectives and team or personal
objectives, [and] a comprehensive program of data governance training.”
