The Target Corporation, based in Minneapolis, MN, serves guests at 1,755 stores in 49 states and at Target.com, and also operates 37 distribution centers nationally.
As a publicly-owned, global corporation, Target has a global presence with a secondary headquarters in India and sourcing offices around the world. Target also has more than 350,000 team members worldwide and is consistently recognized as an employer of choice. With such a recognizable brand, it’s only natural that Target would want to protect its customers and its revenues with theft- and fraud-prevention technologies that could scale to meet the challenges posed by a worldwide retail network. The key to understanding and reducing theft was in knowing where it was most likely to happen and which products were most likely to be stolen.
Theft-related information was available from several unconnected sources, but without a central database or tools to analyze, Target’s management feared they might not be making the most of their data. The team tasked with finding a solution identified three major goals:
- Since organizing and aggregating data from various locations drained time and ate up the data team’s resources, Target’s business intelligence solution would have to reduce the workload associated with pulling theft data from multiple sources.
- Far more theft-related data was available than the team really needed, so simplifying the information after it had been aggregated in one place was the next step. Theft-prevention measures were designed around very basic information: what is being stolen, and where is the theft occurring?
- Theft prevention is a company-wide challenge, not one the data team would try to solve by itself. Because multiple departments in different locations would use theft information at various points, the team needed a solution that could standardize data consolidation, analysis, and distribution.
Fed up with the complexity of multiple channels, wasted resources, and indecipherable reports, Target’s team started looking into business intelligence options that fit their needs and goals. After initial research, four solutions were evaluated for long-term implementation: Tableau, QlikView, MicroStrategy, and SiSense Prism.
Prism offered the Elasticube Manager, which gave Target’s data scientists the ability to compile data from multiple sources quickly and easily--a major advantage over other BI solutions. This eliminated concerns about data structure and made implementation a snap--a handful of Target’s staff were able to set up Prism with minimal support from the corporate technical team.
Since installation, Target’s Assets Protection teams have created standardized reports and dashboards to monitor theft information, reducing reaction time. Thanks to improved data extraction and analysis, theft-related data is housed in a single location, making data manipulation a snap. The team spends less time configuring data and more time using it to reduce theft.
Download a PDF version