Innovation with Style: How Zalando Enhances Procurement with ML-powered Suggestions
Company Size
1,000+
Region
- Europe
Country
- Germany
Product
- Celonis
Tech Stack
- Process Mining
- Machine Learning
- Automation
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Machine Learning
- Application Infrastructure & Middleware - Data Exchange & Integration
- Functional Applications - Enterprise Resource Planning Systems (ERP)
Applicable Industries
- E-Commerce
- Retail
Applicable Functions
- Business Operation
- Procurement
Use Cases
- Predictive Replenishment
- Process Control & Optimization
Services
- Software Design & Engineering Services
- System Integration
About The Customer
Zalando is a leading European e-commerce company specializing in fashion and lifestyle products. With a strong focus on customer centricity and data-driven decision-making, Zalando aims to solve important challenges in the retail industry. The company operates across multiple countries in Europe and has a large workforce dedicated to providing a seamless shopping experience for its customers. Zalando's commitment to innovation and efficiency drives its continuous efforts to enhance various aspects of its operations, including procurement.
The Challenge
Zalando faced challenges in optimizing their procurement processes, which included issues like maverick ordering and deviations from standard procedures. The company needed a solution to streamline these processes, reduce operational tasks, and improve overall efficiency. Additionally, they aimed to enhance supplier analytics to better understand supplier billing behavior and payment terms, ultimately improving working capital management.
The Solution
To address these challenges, Zalando implemented Celonis for process mining and automation. This solution enabled the company to optimize procurement processes by identifying inefficiencies and automating tasks such as eInvoicing and eCatalogues. The Machine Learning Action Engine provided guided buying recommendations, reducing operational tasks and improving decision-making. Additionally, Celonis' supplier analytics capabilities allowed Zalando to gain insights into supplier billing behavior and payment terms, enhancing working capital management. The implementation of process governance measures helped mitigate maverick ordering and deviations from standard procedures, ensuring compliance and consistency.
Operational Impact
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