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Data Management Transformation in Retail: A Case Study of IJsvogel Retail
Technology Category
- Analytics & Modeling - Real Time Analytics
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Consumer Goods
- Retail
Applicable Functions
- Quality Assurance
Use Cases
- Retail Store Automation
- Theft Detection
Services
- Testing & Certification
The Challenge
IJsvogel Retail, a Dutch pet and garden products chain with a history of nearly 130 years, was grappling with the challenge of managing and leveraging its vast and disparate data. With over 180 stores, more than 1,600 employees, and over 800 wholesale customers, the company was generating a significant amount of data. However, this data was not being effectively utilized to inform business decisions. Instead, old data and log files were often discarded rather than compiled and analyzed. The company's small IT department found it difficult to promote the adoption of new applications across the company. The lack of a unified, reliable, and stable data source was hindering the company's ability to make informed business decisions.
About The Customer
IJsvogel Retail is a Dutch pet and garden products retail chain with nearly 130 years of experience. The company started with one brand, Boerenbond, which focused on supplying garden, home, and outdoor life products. Forty years ago, the company expanded to provide pet supplies under the brand Pets Place, which is now the largest of its kind in the Netherlands. IJsvogel Retail has more than 1,600 employees serving 180 stores and over 800 wholesale customers. The company relies on an omnichannel strategy and is planning to use its improved data picture to extend customer reach and focus on building loyalty programs.
The Solution
IJsvogel Retail turned to Fivetran to address its data management challenges. Fivetran enabled the company to consolidate all its data into a single data warehouse, creating a single source of truth for all operations and customer behaviors. This standardized, real-time data provided the company with reliable information, enabling it to plan its operations more effectively. The implementation of Fivetran not only simplified the job of the IT department but also accelerated the time to market. The introduction of managed, automated data flows saved weeks of the engineering team's time, allowing them to focus on the bigger picture rather than maintaining pipelines. The new data architecture focused on actionability, positively impacting risk management, business planning, operational efficiency, and infrastructure management. The democratization of data enabled all business units to use the same information for their own exploration and utilize it more proactively and creatively.
Operational Impact
Quantitative Benefit
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