Every customer expects a quick response to their orders, but not every business can meet that expectation. Manual processing of sales order documents is what causes most of the delays. Staff need to manually receive and input purchase requests into the sales system, which takes up a lot of time. With OCR (Optical Character Recognition), sales order entry doesn’t have to be that tedious. OCR does the heavy lifting by automating data extraction from bukti pemesanan (purchase order)s or order forms, freeing you the hassle of manual work.
This article explores how OCR can be so beneficial for streamlining sales order document processing, including strategic ways to implement it in your business.
How OCR Automates Order Entry
OCR is a tool to capture data from documents and convert it into a format that is processable through computers. Information in purchase forms, such as customer names, item descriptions, and quantities, can be extracted and transferred into your system automatically with OCR. AI is now advancing OCR to be smarter in reading data from varying document designs, making it more reliable for businesses dealing with different formats of purchase orders.
Here’s how OCR enables automated order entry:
1. Data ingestion
OCR begins by scanning and parsing customer order forms, pulling out important details like customer names, shipping addresses, product SKUs, quantities, pricing, and additional requests if any.
2. Data review
Once the extraction process is complete, you can review the data and check the accuracy rate, ensuring it’s all correct before it moves further into your order-entry workflow.
2. Data entry
Finalized data is then pushed directly into your ERP or order-management systems, enabling seamless routing, approvals, and fulfillment without manual input.
The Benefits of OCR for Order Entry
OCR turns hours of manual work into an automated, seamless process of data extraction. Adding OCR to your sales order document processing workflow can bring various benefits, such as:
Reduce data input mistakes
OCR lowers human errors by automating data capture from documents while maintaining a high accuracy rate along the process. It reads and transfers information from sales orders, ensuring more consistent records and fewer manual corrections.
Speed up order cycle
With quick data extraction by OCR, managing each incoming order becomes more seamless. Reduce bottlenecks that could delay order fulfillment, resulting in a more efficient end-to-end cycle and faster SLA to your customers.
Efficient for large-scale processing
OCR equips your business with scalable capabilities that grow with your operations, ensuring efficiency in handling an increasing volume of orders during peak season or expansion.
OCR Implementation for Order Entry
Effective OCR implementation in order entry requires several important considerations and steps. From choosing the most suitable OCR provider to ongoing maintenance to ensure consistent performance over time.
Prior Implementation
- Select AI-powered OCR that is capable of processing varying inputs from order forms.
- Test prospective OCR using a sample document your business usually processes.
Implementation
- Ensure deployment and integration work smoothly with your business tech infrastructure.
- Configure specific field extraction to match your existing order data entry template.
Post Implementation
- Monitor extraction accuracy regularly to ensure the OCR continues to perform reliably.
- Update data-capture settings with any changes or new requirements in your order entry process.
Final Thoughts
Automating order entry with OCR-based data extraction improves operational speed by eliminating inefficiencies like human error and time delays. However, selecting the right OCR solution is important to ensure that your data is processed accurately and handled with the highest level of security. Powered by AI, Fintelite’s OCR is designed to meet real business needs by extracting data from complex and varying order documents, delivering clean data results to be inputted automatically in your system.
