Liliendahl on Data Quality

Data is of high quality if they are fit for the purpose of use. This mantra has been around in the data management realm for many years.

In a recent article by Andy Hayler on CIO about MDM at Harrods there is a good example of a piece of data of such a high quality. It is a product description:

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This product description was nicely fit for the purpose of use when Harrods handled their product data in a material master in an ERP system I guess. But when switching from buy-side focus to sell-side focus in a multi-channel world, this product description gives no meaning to the customer.

Such problems with changing purposes of use for product master data is not only a luxury problem at Harrods but a common challenge within retail and distribution. The challenge involve having customer friendly product descriptions, a range of atomized product attributes that varies by product category and having related digital assets that helps the customer.

Organizations around are, as explained by Andy Hayler, tackling this challenge by implementing Master Data Management (MDM) solutions – in this case those ones specialized in Product Information Management (PIM).

MDM is said to be about a single version of the truth. While this in the customer (or rather party) MDM world is much about achieving uniqueness by matching and merging several different representations of the same real world individual or legal entity, the main challenge in product MDM is a bit different. Here completeness is a big issue. This involves gathering several different pieces of the truth from different sources. And a certain level of completeness may be fit for the purpose of use today but not fit enough tomorrow.

So, how can organizations overcome the huge task of gathering so much product data? I think it is much about Sharing Product Master Data.