RPA Testing in Logistics and Supply Chain

Business automation tools called Robot Process Automation (RPA), present a new powerful tool for testers and business users doing testing, particularly in the context of implementing a large range of standard systems like Microsoft Dynamics 365, SAP, Salesforce, etc.

While there are other potential tools for web and API testing, the RPA tools are a variety of their own, as RPA tools enable codeless automation macros on the desktop. RPA tools can do some very helpful things. They can be utilized for both test data and regression testing.

Logistics and Supply Chain Management include highly complex processes, which are traditionally conducted out manually. Being labor-intensive and time-consuming, the methods themselves become a significant roadblock to gaining operational scalability. RPA, as an enabler of a digital logistics and supply chain system, can bring along the profits of greater accuracy, productivity, and scalability.  

The main areas in the Logistics and Supply Chain management that RPA Testing can augment are: 

1. Inventory Management: As one of the most important aspects of a seamless supply chain network, inventory administration demands the association of a high number of resources and time. Maintenance of the right levels of inventory, holding track of the changing market need, and stocking the inventory at the best rates are some of the tedious activities included in inventory management that RPA can automate. 
2. Freight Management: Freight management includes keeping a real-time track of a freight from the beginning till the point of destination, across the complete network consisting of different modes of transportation and checkpoints. All the processes among all the involved parties of carriers, distributors, merchants, and shippers need to be coordinated for an unobstructed and timely development, transportation, storage, and retrieval of freight. Automation of freight management allows real-time tracking and coordination during the freight network while reducing the chance of gaps and anomalies. 
3. Invoice Management: Any supply chain and logistics warehouse deals with a large number of shipments on a regular basis. This also needs preparation, printing, and inclusion of several invoices along with the concerning shipments. The extensive amount of data entry, synthesis, and validation in invoice management necessitates high accuracy and efficiency, as incorrect invoicing may delay the processing of a shipment. 

Apparently, the implementation of RPA in logistics and supply chain can end in increased operational performance, productivity, and scalability. However, as the methods are highly complex, traditional RPA is not able of handling them alone and needs the involvement of manual resources. The manual-automation model is better than all-manual methods, but the industry requires something smarter and cognitive. This is where next-gen Robotic Process Automation comes in. By leveraging AI, Machine Learning, and Natural Language Processing, RPA enhances intelligence and capable of taking care of even the complex methods without any manual interference. 

RPA bots that use certain next-gen technologies to offer higher automation coverage than those that do not. Some of those technologies are: 

• Machine Learning: Smart computing of complex business logic and rules. 
• OCRs and ICRs: Intelligent data capture to allow ease of automation of complex data arrangements and formats. 
• Predictive Dashboard: Custom algorithms with precise predictions on BOTS output. 
• RPA Framework: Home-grown framework with services and scheduling mechanism for extensive automation coverage. 
• Natural Language Processing: Transformation of speech and voice tags into texts and actions. 

Why perform RPA testing? 

With the help of an RPA Center of Excellence, logistics and supply chain organizations can: 

• Gain a comprehensive assessment to recognize appropriate business processes for RPA 
• Classify & prioritize the processes based on the complexity, automatability, ROI, etc. using in-house utilities to create scorecards 
• Get an outcome-driven RPA policy and the “Right fit tool” for RPA automation 
• Execute next-gen techniques in BOT design – AI/ML, OCRs/ICRs, NLP, Deep Learning design policies, reusability, modularity, etc. for efficient script development 
• Make processes capable to manage changes post-deployment 
• Report defect and deliver an effective RCA to contain defects 
• Build a robust and effective regression test suite for BOT maintenance and support 

Test automation services for RPA supports enterprises in these industries to develop cycle time & productivity in transaction processing and promote AI & ML capabilities to handle high-volume, repeatable jobs, faster and better. 

Connect with our experts at TestUnity to understand how we can help your organization accomplish the desired benefits with RPA testing implementation. 

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