Data Quality is so retro darling
Mark Smith (CEO of research company Ventana) writes about data governance as an important area for companies. He rightly points out that technology solutions are only part of the answer, and that organizational issues are at least as important. Strikingly, just 26% of large companies include master data management in their data governance initiatives. Perhaps some of this gap is in terminology, but this is somewhat disturbing since it raises the question: exactly what numbers are most companies using to make their decisions?
From my recollection of working in two of the largest companies in the world, it was best not to dig too deeply into the management information figures much of the time; data quality was a perennial problem, as was the endless "my figures are different to your figures" discussions. As Mark Smith points out, a lot of the issue is getting the ownership of data firmly with the business. Shell carried out an excellent initiative in the late 1990s in defining a common business model (at least down to a certain level of detail) and getting some business ownership of this business model, but even after this it was still a major challenge. It is certain that other large companies have the same issues. What is clear is that data quality and ownership of definitions cannot be an IT issue; it is critical that the business people step up and take control over their data, since they are the ones best placed to understand inconsistencies and problems that someone who has an IT background may overlook.
A good thing about the emerging interest in master data management is that it highlights previously neglected issues in the "data quality" field, that was previously a tough sell internally. Hands up all those volunteers for a data quality project? It was never what you might term a fashionable subject. Yet a lot of issues in MDM are actually related to data quality, so perhaps now that MDM is trendy we can dust off some of those old data quality books and make some better progress than occurred in the 1990s.
From my recollection of working in two of the largest companies in the world, it was best not to dig too deeply into the management information figures much of the time; data quality was a perennial problem, as was the endless "my figures are different to your figures" discussions. As Mark Smith points out, a lot of the issue is getting the ownership of data firmly with the business. Shell carried out an excellent initiative in the late 1990s in defining a common business model (at least down to a certain level of detail) and getting some business ownership of this business model, but even after this it was still a major challenge. It is certain that other large companies have the same issues. What is clear is that data quality and ownership of definitions cannot be an IT issue; it is critical that the business people step up and take control over their data, since they are the ones best placed to understand inconsistencies and problems that someone who has an IT background may overlook.
A good thing about the emerging interest in master data management is that it highlights previously neglected issues in the "data quality" field, that was previously a tough sell internally. Hands up all those volunteers for a data quality project? It was never what you might term a fashionable subject. Yet a lot of issues in MDM are actually related to data quality, so perhaps now that MDM is trendy we can dust off some of those old data quality books and make some better progress than occurred in the 1990s.
posted by Andy Hayler at 1/31/2006 07:14:00 AM
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