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Streamlining Inventory Management and Operational Efficiency through RPA and SAP Integration: A Case Study with a Global Fashion Retailer Client Overview

Client Overview

A renowned leader in the fashion retail industry,  is synonymous with luxury and lifestyle, offering high-quality apparel, accessories, and home furnishings.

Industry: Fashion Retail

Size & Scope

As a multinational corporation with operations in over 80 countries,  serves a global market. Its diverse channels include retail stores, wholesale partners, and a thriving e-commerce presence.

The scale of operations involves a complex network of suppliers, distribution centers, and retail locations that require seamless data synchronization and efficiency.

Process Overview

Price Change for Materials

Price Adjustment Initiation (Merchandising Planning Team) :
  • Price modification request (AMF - likely an Authorization for Modification Form) is raised in SAP due to price variations for certain brands.
Data Analysis & Reconciliation (Business Operations Team)
  • Compares before and after price data in SAP to ensure accuracy.
  • Identifies discrepancies in price updates.
Validation & Error Resolution (Pricing Team)
  • Validates incorrect price changes and resolves discrepancies.
Reporting & Compliance (Stakeholder Communication)
  • Weekly consolidated reports on price changes are shared with multiple regional stakeholders for oversight
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Automated the process of comparing multiple before and after price data. Extract material data from SAP and perform structured Excel manipulations to generate a consolidated report highlighting price changes and discrepancies in the latest dataset and then inform business for the same through email.
  • Reduce manual effort in updating AMF in SAP and analyzing price changes.
  • Consolidate weekly Price Change files automatically for distribution to regional stakeholders.
  • Decrease processing time per item by 80% and improve overall activity monitoring through robotic logs.
This process operates daily and is designed to minimize human intervention while ensuring accuracy and efficiency in price list comparison and reporting.

Debit Note Processing

Debit notes play a crucial role in correcting pricing discrepancies, returning defective goods, or making adjustments to previously issued invoices. However, the manual processing of debit notes can be time-consuming, error-prone, and lead to financial discrepancies. By automating the debit note process in SAP, fashion houses can streamline financial operations, ensure accuracy, and improve vendor relationships.
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Process Overview

  • Debit notes are received via email from predefined contacts
  • The saved debit note is matched with SAP records based on the debit note number and total amount
  • If validated, a dispute case is created in SAP.
  • The appropriate reason code (e.g., Price Discrepancy, Return, Sales Allowance) is assigned.
  • The debit note document is attached to the dispute case in SAP.

Challenges in Manual Debit Note Processing

Time-Consuming Data Entry

Manually entering data increases the chances of human errors and slows down processing.

Invoice Reconciliation Issues

Matching debit notes with corresponding invoices often leads to discrepancies.

Delayed Approvals

Manual workflows cause bottlenecks in approval cycles, delaying settlements.

Lack of Visibility

Without real-time tracking, finance teams struggle to monitor outstanding debit notes

Automation Benefits

  • 90% Reduction in Manual Effort – No need for human intervention in repetitive tasks.
  • Error-Free Debit Note Processing – Eliminates human errors in data entry and validation.
  • Faster Dispute Resolution – Automated processing significantly reduces turnaround time
  • Seamless SAP Integration – RPA bots work natively within SAP without altering existing workflows.
  • Improved Compliance & Tracking – Exception handling ensures accurate financial reporting and vendor communication.

Solution

Technologies Employed: To address these challenges, we deployed a custom solution integrating SAP, UiPath (RPA), Excel, and UiPath Orchestrator.

Assessment and Strategy Development

  • We began by assessing ’s existing workflows. This included identifying bottlenecks in their inventory management and analysing how data was shared between SAP, Excel, and other systems.

Technology Stack

  • UiPath RPA was chosen for its ease of integration with both SAP and Excel, enabling the automation of routine tasks.
  • UiPath Orchestrator provided centralized control and management of all RPA bots, allowing ’s team to monitor and adjust workflows as necessary.

Customization and Workflow Design

  • Automated Data Reconciliation: RPA bots were configured to periodically extract and validate data from SAP, Excel, and other sources, eliminating inconsistencies.
  • Error-checking Mechanisms We implemented checks to ensure data integrity before updates. If inconsistencies were detected, alerts were sent to the relevant teams, reducing manual oversight requirements

Collaboration with Client’s Team

  • To ensure a smooth transition, our team worked closely with ’s operations and IT teams, defining key performance indicators (KPIs) and building workflows that aligned with the company’s operational needs.

Implementation

The project was executed in a series of structured phases over a six-month period, involving planning, development, testing, and deployment.

Planning

  • Developed a roadmap with defined timelines and set KPIs to measure progress.
  • Identified areas that would benefit most from automation, including inventory reconciliation and order fulfilment

Development

  • Our team built and tested customized RPA workflows to handle data extraction, data synchronization between SAP and Excel, and error-checking.
  • Additionally, we designed a user interface within UiPath Orchestrator, giving ’s team visibility over each automation bot’s status and performance.

Testing

  • Conducted both unit and system tests to verify data accuracy, speed, and resilience of the automation workflows.
  • Simulated real-world scenarios to test bot performance under varying loads and conditions.

Deployment

  • Deployed the solution in phases, initially focusing on a pilot store and scaling up to the entire network as issues were addressed.
  • Incorporated client feedback to fine-tune workflows and resolve minor inconsistencies encountered in early deployments.

Training and Support

  • Provided comprehensive training for ’s IT and operations teams, enabling them to monitor and troubleshoot the RPA system independently.
  • Set up a support team to provide assistance during and after deployment, ensuring a smooth transition to automated processes.
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Client
Testimonial

Implementing RPA in our operations has made a substantial difference. We’ve seen a marked improvement in our inventory management efficiency, and the reduction in manual tasks allows our team to focus on higher-value activities.

This solution has not only saved us time and costs but has also given us real-time, accurate data for better decision-making.
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- Operations Manager

Key Takeaways

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Automation as a Cost-Effective Solution

Automating repetitive tasks leads to considerable savings in both time and operational expenses

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Increased Accuracy in Data Management

Automating data transfer and reconciliation processes reduces the risk of human error, ensuring consistent data across systems.

Scalability for Growth

RPA offers flexibility and scalability, allowing retailers to adapt to evolving demands and expanding operations.

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Improved Customer Experience

With faster and more reliable inventory updates,  can fulfil customer orders more efficiently, enhancing satisfaction

Want to optimize your inventory management and streamline operations?

Contact us today to learn how we can implement a customized automation solution to meet your business needs!

[email protected]
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Auxiliobits is a global Software Consulting and Artificial Intelligence advisory company. Auxiliobits drives digital transformation by reinventing enterprise operations through hyper-automation and AI enabled applications.

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