by Angela Guess
Russ Hill recently wrote about the data governance troubles facing retail companies. Hill writes, “When managers think about a business, they do so in terms of data: sales volume, inventory, margin, product turn, operational overhead, and other metrics. Data is the language of business. It’s the basis of functional control and, above all, of decision-making. Our ability to figure out where to go next depends almost entirely on our ability to understand where we are now. All other things being equal, then, the better our data, the better our decision-making. Unfortunately, business managers often find themselves in the position of having to make decisions based on data that is inaccurate, incomplete, out of date, or all three together.”
The first retail data problem Hill addresses is complexity: “In retail, many problems stem from the sheer complexity of the data. Retailers deal with customer data, product data, and data from their own internal business processes. And the complexity is further increased by retailers’ drive to define and differentiate themselves from their competition. Business process data is fairly straightforward, but customer and product data tends to be extremely complex. The data on a single inventory item may include SKU, package quantity, size, tie/high, cube, color, weight, price, safety characteristics (e.g. flammability), environmental characteristics (e.g. recyclability), sentiment, and several hundred other attributes. And the data on a single customer can be just as extensive.”
Read more problems facing retail data governance here.
