On January 15, 2015, Target Canada shocked the business world by filing for bankruptcy protection. The retail giant’s Canadian stores had been open for less than two years, their operation marred by high profile failures: delayed openings, empty shelves, and annual losses that added up to 2.1 billion USD. Analysts, reporters, and Target’s own employees unanimously identified the culprit – bad data in SAP.Exclusive: Target Canada’s supply chain gridlock: how Barbie SUVs snarled traffic
This in and of itself was not a new story; the two largest food retailers in Canada – Loblaws and Sobeys – had both had significant issues with their SAP implementations. Target believed that flawed data conversions had caused these implementations to stumble. Target believed the problems other retailers faced were due to error in data conversion. To avoid this issue, Target decided to fill the Canada SAP systems with entirely new data rather than converting data from their US databases. Unfortunately for Target, this strategy did not pay off and led to many of the well-publicized failings that shuttered its Canadian stores for good.
Why was Target Canada so afraid of data conversion?
Done correctly, conversion allows for a smoother cutover between old and new systems – no telling customers they must remake their online order accounts, for example – and saves countless labor hours that would otherwise be spent populating data by hand. For many companies, especially in retail, conversion is the only sensible choice. But despite best laid plans, many implementations face uncertainty in the data conversion process. Late changes to functional requirements, large data volumes, and complicated data dependencies all present opportunities for data headaches leading up to and beyond go-live. And with the critical role data plays in modern business processes, a small conversion flaw can have a […]