Dataiku Case Studies Action's Journey: Leveraging Data Analytics for Efficient Business Operations
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Action's Journey: Leveraging Data Analytics for Efficient Business Operations

Dataiku
Analytics & Modeling - Big Data Analytics
Analytics & Modeling - Data-as-a-Service
Buildings
Cement
Logistics & Transportation
Sales & Marketing
Demand Planning & Forecasting
Visual Quality Detection
Data Science Services
System Integration
Action, Europe’s fastest growing non-food discount retailer, faced a significant challenge in managing the vast inflow of data from its over 2,300 stores across 11 countries. The company needed to track various aspects such as consumption patterns, product placement, and supply chain disruptions, which varied according to local, national, and international trends. The existing architecture was not sufficient to handle the data efficiently and provide accurate forecasting models for demand and sales in new and existing markets. The company also faced issues with data access and quality, costly and complex processes, lack of visibility and control, and operationalization and business impact. The use of Excel for gathering, sorting, manipulating, and modeling data was proving to be a bottleneck for the speedy and efficient deployment of data analytics and models.
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Founded in 1993, Action has grown to become Europe’s fastest growing non-food discount retailer in just 30 years. The company has spread its roots from the Dutch city of Enkhuizen, where it began, to 11 countries and over 2,300 stores across the continent. Action offers its customers a vast and constantly changing assortment of products at the lowest possible price. The company has over 60,000 employees and made €8.9 billion in net sales in 2022. Action's mission for over 30 years has been to enable the company to make decisions based on data, rather than on intuition, to support its ongoing growth with a focus on opening stores in existing and new markets.
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Action partnered with Capgemini and Dataiku to build the right architecture and toolset to leverage the company’s data with greater efficiency. The company developed a data lake to centralize the vast inflow of data and regularize its access. The data lake became a reservoir from which pipelines could be built into the platforms on the team’s tech stack, including Dataiku. The company also worked with Dataiku and Capgemini on a proof of concept to demonstrate the value of a robust and collaborative data platform. They matured a proof of concept black box of code into a more easily explainable and understandable visual diagram of the data journey. The company also addressed the issue of visibility and control by implementing a robust AI Governance system with Dataiku. The platform allowed user-owners to view and control access to the team’s models and processes, from inception to deployment to feedback-aligned redeployment.
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The implementation of the new data architecture and toolset has resulted in significant operational benefits for Action. The company has been able to develop more accurate forecasting models with greater speed, enabling it to make data-driven decisions rather than relying on intuition. The use of Dataiku's platform has allowed for easier cross-team collaboration, a reliable data pipeline, and a clear view on existing processes, empowering business units to operationalize the model-generated forecasts to make real-time decisions. The company has also seen the benefits of a robust AI Governance system, which has improved visibility and control over the model building, changing, realigning, and usage processes. The move toward decentralization has allowed for the growth of a community of experts and free communication across the organization.
900% improvement on forecast runtime
88% accuracy on a 52-week forecast
Reduced the runtime of each forecast to between 6 and 9 hours
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