Retail & E-Commerce

Advanced Model Case of Digital Transformation: Automa RPA Reduces the Reconciliation Cycle by 97%

Forest Cabin used Automa RPA to automate online reconciliation and logistics order splitting, cutting the reconciliation cycle by 97%, reaching near-100% accuracy, saving 3,900+ person-days, and scaling to 100+ retail scenarios.

100+Business scenarios covered
3,900+Man-hours saved per day
97%Improvement in financial reconciliation efficiency
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"In multi-channel sales scenarios, with the massive and overlapping volumes of product and user data, we leverage RPA to handle repetitive tasks, freeing employees from mechanical work."

Killian Smith·Deputy Manager of Financial Center at Forest Cabin

About Forest Cabin

Founded in 2003, Forest Cabin is a premium skincare brand. It pioneered the Red Camellia skincare series, combining modern technology with the unique Red Camellia plant, and has been the sales leader in the essence oil skincare market for nine consecutive years.

By 2022, Forest Cabin had opened nearly 400 stores in renowned commercial districts and shopping centers. While providing exceptional in-store service, the brand has actively advanced digitalization, building smart digital stores in the beauty industry and expanding omnichannel online sales, thus forming consumer-centric online and offline business capabilities.

Forest Cabin chose Automa RPA as an important part of its digital transformation, leveraging automation technology to handle tedious and repetitive tasks in the online channel reconciliation process. This enabled efficient and accurate reconciliation, greatly improving the company's operational efficiency.

Operational Statistics:

  • Over 100 applications developed

  • Applications have operated for more than 6,000 hours

  • Saved over 3,900 person-days of labor

Covered Teams:

Finance Department, with plans to gradually expand to additional departments.

Covered Scenarios:

  1. Regular login to relevant merchant accounts, categorization and processing of billing information, and downloading of statements

  2. Automated bill reconciliation and reconciliation report notifications

  3. Automation of logistics order splitting, online return processing, and payment receipt generation

Achieved Results :

  1. Automated Online Reconciliation:

    1. Reduced the reconciliation cycle by 97%, significantly improving efficiency.

    2. Eliminated manual errors such as missed deductions and incorrect entries, reducing the human error rate and achieving near-100% accuracy.

    3. Enabled 24/7 automated reconciliation, greatly enhancing the timeliness and accuracy of corporate reconciliation.

  2. Automated Logistics Order Splitting: RPA automatically retrieves logistics order splitting and shipment information from the system, matches it with the corresponding consumers, and delivers notifications, eliminating the need for cross-organizational.

Challenge 1

Multiple platforms with repetitive and tedious operations: In addition to major e-commerce platforms, there are emerging channels such as live-streaming sales. Each channel requires repeated actions like logging in, querying, and downloading, which are time-consuming and labor-intensive.

Solution 1

RPA robots can follow preset rules to automatically and regularly log into the backends of merchant accounts such as TikTok, retrieve billing information, categorize and organize the data, and complete reconciliation automatically. 1. Download bills from TikTok.

Challenge 2

Large volume of reconciliation data makes verification extremely time-consuming: With hundreds of thousands of orders per month, the number of bills generated can reach millions, requiring a significant amount of manual work.

Solution 2

By developing an RPA-powered online multi-channel automatic reconciliation system, tedious and repetitive tasks in the reconciliation process are automated, achieving efficient and accurate reconciliation. 1. Bill reconciliation. 2. Reconciliation report notifications.

Challenge 3

High requirements for data accuracy and consistency: Errors, delays, or inconsistencies in order data input may lead to incorrect order-splitting decisions, affecting customer satisfaction.

Solution 3

RPA automatically retrieves logistics order-splitting and shipping information from the system, matches it with the corresponding customers, and sends notifications, eliminating cross-organizational communication and confirmation. This reduces labor costs by one full-time employee per month. 1. Automation of logistics order-splitting information.

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