Case Study: Invoice Processing With Using Intelligent Document Processing

Problem:

This case study is about a company that implemented an IDP solution to automate their invoice processing, resulting in significant time and cost savings.

Background:

The company in question is a mid-sized manufacturing company that produces and sells machinery parts to various customers globally. They receive a large number of invoices from their suppliers, and processing them manually was a time-consuming and error-prone task. The company was looking for a solution to automate this process and streamline their accounts payable department.

Data:

The data associated with the table names mentioned includes various aspects of invoice processing. The "Invoice Information" table likely contains details about invoices, such as invoice number, date, and total amount. The "Invoice Items" table captures line item details such as product descriptions, quantities, and prices. The "Invoice Attachments" table may store information about any supporting documents or attachments associated with invoices. The "Vendor Data" table likely contains information about vendors, including their name, address, and contact details. Lastly, the "Invoice Policies" table may store predefined policies or rules that are applied during invoice processing, such as validation criteria and matching rules. This data is essential for automating and streamlining the invoice processing workflow, ensuring compliance with organizational policies, and facilitating efficient invoice management.

• Invoice Information
• Invoice Attachments
• Vendor Data
• Invoice Policies

Invoice Information: This table likely contains information related to invoices, such as invoice number, invoice date, due date, and other relevant details. It may also include data such as the invoice total, currency, and payment terms.

Invoice Items: This table is likely used to capture line item details of each invoice, such as the description of the products or services, quantity, unit price, and total amount for each line item. It may also include additional information such as tax, discounts, and other charges associated with each line item.

Invoice Attachments: This table may contain information about any attachments or supporting documents associated with each invoice, such as scanned copies of the original invoice, receipts, or other relevant documents.

Vendor Data: This table is likely used to store information about vendors, such as their name, address, contact information, tax identification number, and other relevant details. This data can be used for validation and matching against the vendor information provided in the invoices.

Invoice Policies: This table may store the predefined policies or business rules that are applied during the invoice processing, such as validation rules, matching criteria, and other policies. These policies may be used to automate the invoice processing workflow and ensure compliance with the organization's policies and procedures.

Please note that the actual structure and data in these tables may vary depending on the specific requirements and business processes of the organization implementing the invoice processing system.

Information in tabular format

Invoice Information
Supplier Name	ABC Suppliers
Invoice Number	INV-2023-001
Invoice Date	2023-03-15
Due Date	2023-03-31
Currency	USD
Total Amount	$5,000.00
Language	English

Invoice Items	Description	Quantity	Price	Line Total
Item 1	Product A - 100 units	100 units	$40.00 per unit	$4,000.00
Item 2	Product B - 50 units	50 units	$20.00 per unit	$1,000.00

Invoice Attachments
Attachment 1	Invoice PDF file with scanned image
Attachment 2	Email attachment with invoice in PDF format
Attachment 3	Scanned image of a physical invoice received via mail

Vendor Data
Vendor Name	ABC Suppliers
Vendor ID	VENDOR-001
Vendor Address	123 Main Street, Anytown, USA
Vendor Tax ID	123456789
Vendor Contact	John Smith, Email: john@example.com, Phone: +1-123-456-7890

Invoice Policies
Policy 1	Verify invoice number against approved list
Policy 2	Validate invoice date within acceptable range
Policy 3	Check invoice total against purchase order amount
Policy 4	Match invoice currency with company's default currency
Policy 5	Extract line item details, quantity, and price
Policy 6	Validate vendor data against master data
Policy 7	Flag invoices with missing or incomplete information

Solution

The company implemented an IDP solution that used Optical Character Recognition (OCR) technology to extract data from the invoices. The system was trained to recognize various invoice formats and extract relevant data such as the invoice number, date, vendor name, and amount. The extracted data was then validated against the company's ERP system and stored in a database for further processing.

The system was also configured to handle exceptions and errors that may occur during the data extraction process. For example, if the system was unable to extract data from a particular invoice, it would notify the accounts payable team to manually review and process the invoice.

Results:

After implementing the IDP solution, the company saw significant improvements in their invoice processing time and accuracy. The time required to process invoices was reduced from several hours to minutes, resulting in a 90% reduction in processing time. The system also eliminated the need for manual data entry, reducing the likelihood of errors and improving accuracy.

The IDP solution also enabled the company to process a higher volume of invoices without increasing their staff, resulting in significant cost savings. The system paid for itself within the first year of implementation, and the company continued to see cost savings in subsequent years.

Results

Metrics	Results
Document Volume	10,000 invoices per day
Accuracy	98.5%
Processing Time	Less than 5 seconds per invoice
Document Types	Invoice, purchase order, packing slip, credit note
Extracted Data	Vendor name, invoice number, invoice date, total amount
Integration	XML format for seamless integration with ERP system

Conclusion:

The implementation of an IDP solution enabled the company to streamline their invoice processing, resulting in significant time and cost savings. The system's ability to handle exceptions and errors also improved accuracy, reducing the likelihood of errors and improving data quality. The company was able to achieve a quick return on investment and continues to benefit from the system's efficiency and accuracy.

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