How poor data governance killed a $5B retailer: A cautionary tale of supply chain mismanagement 

How poor data governance killed a $5B retailer: A cautionary tale of supply chain mismanagement

In the fast-paced world of retail, where staying ahead of the competition is crucial, making the right technology choices can be the difference between success and failure. Target, the U.S. retail giant, learned this lesson the hard way when its ambitious expansion into Canada turned into a catastrophic failure due to poor data governance in its implementation of SAP, a widely acclaimed enterprise software solution. 

The SAP Quandary 

Target’s decision to implement SAP in its Canadian operations was driven by the desire to streamline processes, align with the U.S. operations, and leverage the latest technology for retail management. SAP is often considered the gold standard in retail, used by companies globally for its ability to store vast amounts of data related to products and integrate with other critical systems such as demand forecasting and distribution center management. 

However, SAP is not without its challenges. The intricate nature of SAP, coupled with its complexity, demands meticulous planning and execution. Unfortunately for Target, the implementation timeline was unrealistically tight – an attempt to set up and run SAP in approximately two years, a feat considered impossible by many. 

The unraveling began in 2012 

 The problems surfaced when strange incidents started occurring in 2012 during the ordering process for the impending launch of Target’s Canadian stores. Products faced delays due to issues like improper dimensions, missing tariff codes, and incomplete product descriptions. 

  Investigations revealed an alarming number of errors, with data accuracy estimated at a mere 30% compared to the 98-99% in the U.S. 

Moreover, Target Canada lacked a safety net in SAP, as the system couldn’t notify users about data entry errors. The company faced a crisis that demanded drastic measures – shutting down the entire merchandising division for a week to manually verify every piece of data in the system. This episode revealed the extent of errors, prompting Target to realize the critical importance of accurate data. 

 Supply chain mismanagement 

 As Target Canada launched its stores, the problems multiplied. Empty shelves, issues with the distribution centers, and a surplus of inventory in some areas while shortages in others created a chaotic supply chain. The forecasting system, relying on optimistic projections and unfamiliarity with the Canadian market, further added to the woes. 

 The situation led to a severe bottleneck in the distribution centers, with overflowing goods and idling tractor-trailers. The decision to rent additional storage facilities became necessary, but the process was haphazard, resembling a “massive black hole.” 

The Human factor 

 Adding to the complexity were issues with the point-of-sale system, causing incorrect change, slow terminals, and transaction failures. Human error, misjudgments in inventory, and a lack of understanding of the new technology plagued the operations.  

Tony Fisher, appointed to lead Target Canada, faced an uphill battle. His background in merchandising proved insufficient to tackle the severe operational and technological challenges. The unrelenting pace and constant setbacks took a toll on Fisher, who ultimately left the company after the disastrous launch.   

A failed attempt at redemption  

Mark Schindele took over as head of Target Canada, bringing renewed energy and a no-nonsense approach. The company implemented critical improvements, focusing on basics like in-stock essentials. Learning from its mistakes, Target Canada slowly improved its operations, but it was too late. 

In January 2015, Target Canada filed for bankruptcy protection, marking the end of a $7 billion expansion that had gone horribly wrong. All 133 stores closed, and the aftermath left employees devastated and the company licking its wounds. 

How better data governance could have helped

The post mortem revealed critical operational missteps. Also, SAP is notorious for a difficult rollout. The industry is rife with botched implementations. Target Canada believed that a greenfield implementation (new input information) would not be as glitchy as the brownfield implementations (data migrated from existing systems). But this was a crucial, critical error.  

Merchandisers were under pressure to enter information into 75K different products into SAP, but the manual entry process was rife with errors.

The company hadn’t built a safety net into SAP at this point; the system couldn’t notify users about data entry errors. The investigative team estimated information in the system was accurate about 30% of the time. In the U.S., it’s between 98% and 99% – “The Last Days of Target”, by Joe Castaldo

All these issues illuminate the reason why we launched DataVapte, a SAP add-on that works exclusively on S/4 HANA rollouts (greenfield AND brownfield) to validate data.