With the best will in the world, it is difficult to ensure that data validation rules and information update policies are applied consistently across any complex landscape. Put all this together, and these are the reasons why customer data quality tends to drift downwards over time. Then, of course, fixing it in any particular system becomes quite a significant undertaking, so with limited resources and competing priorities in more urgent or glamorous areas, it continually gets deferred.
If any or all of this sounds familiar, then we encourage you to read this paper. There is another way of thinking about and tackling the problem that allows data quality to be sustained on an ongoing basis.
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