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These days everybody talks about cost cutting, increasing revenue, how the depression, recession affecting company margins and how the job losses are imminent and so on and so forth.  All this is true and real and no doubt everybody is looking at new avenues to struggle with the numbers. Though there is no magic recipe to alter the scenario overnight, lot of people, lot of companies are failing to see optimization chances within the organization and chance of increasing revenue – data in their own systems. What data – everything – right from suppliers, customers, materials. What to look for – Data Quality.

The surveys done by few companies in the area estimated that the by managing the data quality one can increase revenue by 66%. Now let’s take that as marketing gimmick on the face, but then assume its half of that – still there is a chance of revenue increase of 33% – do you want to believe that? I do.

My experience with large global enterprises in the data area points me to believe in that. There are these multiple locations, multiple plants, and multiple systems having too many suppliers, too many material getting procured – direct or indirect. All this creates big quality issues in the data – same supplier calling by different names, IBM, I B M, I.B.M, …….favorite example of quality industry, not having linkages among suppliers in system.  So this issue prevents to get visibility of suppliers – subsidiaries and vendors relationship. If you have that visibility there are greater chances of negotiations with parent suppliers and thereby affecting the bottom line. End of the day this is one supplier but as your data is too scattered its difficult for you to get visibility. E.g.  You are happy to have contract with doubletree hotel, another with embassy suites and likewise but if you have linkages in your system correctly maintained, you will know that they are all “Blackstone group” and if you have negotiated contract with Blackstone then probably your saving is much much more.

That’s just one example of supplier data. Same applies to materials. A simple example is matching attribute values for materials. As the data doesn’t contain attribute values at the detailed down the hierarchy level – you cannot compare same or similar materials using your systems. If you have that probably you can use material available in plant A rather than procuring it right away. So data quality saves you there.

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