Country
Franchisee App for a Multinational Fashion Company
Software supplier
Product
N/A
Other
Technology Stack
- VueJS/NuxtJS
- Kotlin/JVM
- SpringBoot
- Postgresql
- Docker
- Kubernetes
Problem
Franchisee Partners in the fashion industry often face challenges in efficiently managing and planning their product orders for upcoming seasons. The process is typically time-consuming, involves multiple data sources, and requires significant manual effort, especially for compliance checks and order accuracy.
Solution
Software Angels developed a state-of-the-art web application designed to streamline and simplify the order management process for Franchisee Partners. This tool integrates data from various sources to create an initial product order proposal, allowing partners to modify their orders while viewing the total units and costs. The application also generates SAP and Excel outputs necessary for analysis and order placement, significantly reducing manual data handling.
Process
- Data Integration: The application gathers information from diverse sources to compute an initial order proposal for each Franchisee Partner.
- Order Modification: Partners can adjust their orders and instantly see the total units ordered and cost implications.
- Output Generation: Generates SAP and Excel outputs for initial allocation analysis and order placement.
- Efficiency: Reduces manual effort in data handling and legal SOX compliance checks.
Achievements
- In 2023, the application handled over €62,000,000 in orders, demonstrating its robustness and scalability.
- Reduced the workload for data checks related to legal SOX compliance, saving approximately 8 hours per month.
- Improved size accuracy by providing early signals to the supply chain, resulting in estimated savings of €1,400,000 per year.
Target audience
The application is specifically designed for Planners and Franchisee Partners, providing a user-friendly interface and advanced features to visualize and define product orders for upcoming seasons. This enhances decision-making processes and overall performance.
worked on this project
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