Download PDF
Case Studies > Innovation with Style: How Zalando Enhances Procurement with ML-powered Suggestions

Innovation with Style: How Zalando Enhances Procurement with ML-powered Suggestions

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
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.
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 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
  • The implementation of Celonis led to significant improvements in procurement efficiency and speed, allowing Zalando to focus more on value creation.
  • The use of machine learning and automation reduced the burden of operational tasks, enabling employees to concentrate on strategic activities.
  • Enhanced supplier analytics provided valuable insights into supplier behavior, leading to better negotiation of payment terms and improved working capital management.

Related Case Studies.

Contact us

Let's talk!

* Required
* Required
* Required
* Invalid email address
By submitting this form, you agree that IoT ONE may contact you with insights and marketing messaging.
No thanks, I don't want to receive any marketing emails from IoT ONE.
Submit

Thank you for your message!
We will contact you soon.