Data quality savings gone missing

One thing that continues to surprise me is how little developed the business case for data quality and master data management is.  When I look at data quality vendors speaking at conferences I can sit through whole sessions which do not mention the amount of actual dollars their clients saved by using their technology. In the case of MDM there is some excuse for this, since MDM as a term only recently became mainsteam, and so few vendors have real projects that are in production with clients.  Indeed just 4% of companies have completed an MDM project, according to a recent survey by Ventana (though 37% claim to have initiated a project).  However in the highly related field of data quality there are no such excuses: tools have been around for years, and yet trying to find examples of well justified projects with a hard dollar payback is like pulling teeth.

While data quality has remained something of a backwater (the largest data quality vendor does around USD 50M in revenue) it is surely one of the things that should be relatively easy to produce a cost benefit case for.  After all the tools will enable you to detect the proporton of bad data in a given application or enterprise, and it should not be beyond the wit of man to be able to assign a cost of poor data quality.  Even ignoring tricky things like customer satisfaction, poor data causes very real things: deliveries going to wrong places, misplaced inventory, incorrect payments, problems in manufacturing.  In certain industries it can be worse: drilling an oil well in the wrong place is an expensive affair, for example.  An 2003 AT Kearney study showed that USD 4 was saved for every dollar spent on data cleansing activity. 

By going back and looking at completed projects and carrying out cost/benefit analysis the data quality (and MDM) vendors will be doing themselves a favour, since by quantifying the savings these projects bring they can not only make it easier to justify new projects, but they beging to justify the price of their products: indeed they may be able to gain improved pricing if they can demonstrate that their products bring sufficient value to customers. It is a mystery to me as to why vendors have made such a poor show of doing so.


One thought on “Data quality savings gone missing”

  1. Dear Andy,

    Interesting article, especially for us, being a pure European DQ Vendor (Human Inference) However, we did develop some strong business cases where we could show the ROI of using/implementing our DQ Software suite. If you would be interested in learning more, please do not hesitate to contact.

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