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A packing slip is a document that accompanies an article that has been purchased and provides details of the items included in the package, along with its quantity, dimensions, etc., the details of the seller, and if applicable, the details of the buyer. As a company grows in size and its inventory management gets digitized, it becomes important to digitize the packing slip as well. The importance of data extraction from packing slips and the use of packing slip OCR are described in the following sections.


The differences between packing slip, invoice, delivery note (or docket) and purchase order

Among the four documents that are associated with the purchase of a product by an individual or an organization – purchase order, invoice, delivery note and packing slip – the last two are perhaps the most closely related. Delivery note (or docket) and packing slip are essentially the same in that they contain details of the products in the package or shipment, without referencing the price aspects of it. The difference is that a delivery note often requires the recipient’s signature and is returned to the seller for their records while the packing slip is retained by the buyer as a record of the contents of the package.

The purchase order is issued by the buyer and is a request to the seller to sell the product at the price and quantity specified. The invoice is a financial document of the order, issued by the seller and contains information such as price, payment mode, payment due date, etc. in addition to product details.

While the purchase order and invoice are to be retained by both buyer and supplier, the packing slip becomes the sole property of the buyer and is used to check for the correctness of the delivery. It is thus important to extract data from the packing slip at both ends - the buyer and the seller.


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The need to extract data from packing slips

Packing slips are important for both sellers and buyers. For the seller, it is a final check before items are shipped out and could ensure reliability and customer satisfaction. For sellers, data extraction from packing slips is important because,

  • The slip is retained by the buyer. While it is indeed a practice for the seller to have a copy of the packing slip, having paper copies in an increasingly digital world is unwieldy and illogical. Digitization of the packing slip data is a good way to archive data.
  • Data extraction from packing slips and storage of data in a company-wide repository helps in better access to the data by all stakeholders in the business and helps with auditing and inventory management.
  • The extraction and storage of data from packing slips can help in assessing the performance of the company and the number of goods sold over time so that course corrections can be made to maximize profit and quality.

Data extraction from packing slips is important for the buyer in the following ways:

  • It allows automated checks for discrepancies, especially when crosschecked digitally with the purchase order and/or invoice.
  • The data extracted from the packing slip can be cross-checked with the inventory list of the company to prevent shortages and associated delays.
  • The extraction and storage of data from packing slips can help in assessing the performance of the company and the number of goods bought over time so that course corrections can be made to maximize profit and quality.

In addition, data extraction from packing slip can serve the following purposes:

  • Ensure that everything is in the shipment, especially in e-commerce transactions.
  • Tracking all items in the order easily; data extracted from a physical packing slip before dispatch is easy to be shared with the recipient, and also with any intermediaries such as the shipping company so that the order can be traced easily.
  • Easing security checks: data extracted from packing slips can be shared with customs officials easily for more efficient checks before border crossings.

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Perils of manual data extraction from packing slips

The extraction of data from packing slips and their entry into a database or software, when performed manually, is associated with problems of inefficiency. Three tasks associated with manual data entry have been reported to be killers of productivity and employee morale.

Data Collection

Collection, uploading, and syncing data is the least productive task of manual data entry and consumes too much dead time that the employee would rather spend on productive tasks.

Getting Approvals

Once the data is entered, checking it, and getting approvals, sign offs, and confirmations can consume time and effort.

Providing Updates

Managing status updates and other information takes time off other productive work.

As companies diversify and expand, the number of packing slips may also increase and the amount of data that they deal with also increases exponentially. In such cases, manual data capture simply cannot keep up with the processing demands resulting in a “choke point.” This disruption is not a temporary or a one-time problem that would go away with time, because it would be persistent and repetitive, and can adversely affect the scale-up of the organization.

In short, manual data entry is costly, inaccurate, and demoralizing. These issues can lead to a loss of focus on the core or strategic tasks. Thus, manual data entry cannot support the strategic, sustainable growth of an organization.


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OCR for data extraction from packing slips

Smart Optical Recognition Software such as Nanonets can extract printed data from scanned packing slips into digital text. OCR-based data extraction from packing slips involves identifying the table rows that constitute the line item and then applying OCR to extract data from the table’s cells. In a typical OCR, data extraction as tables could be brought about by the following steps:

  • Detection of the line segments through the application of horizontal and vertical contours.
  • Detecting the line intersections as a function of the intensity of the pixels of all lines.
  • Determination of the edges of the tables again through the intensity of pixels of intersected lines at the boundaries.
  • Translation of the image analyses into PDF coordinates to determine the cells, followed by assignment of the text to the cell based on the geometric coordinates
  • Application of OCR to extract text from the coordinates

Artificial Intelligence (AI) and Machine Learning (ML) technology such as those used in Nanonets can overcome the shortcomings of traditional OCRs. AI-based OCRs can intelligently capture relevant data with minimal errors due to the continuous learning processes of the AI tool. The feature of continuous learning in AI systems allows the reading software to adjust to all formats of packing slips and gives it a universality across the company’s platforms.


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Nanonets OCR for data extraction from Packing Slips

The Nanonets API can perform the following tasks, which makes it suitable for data extraction from packing slips:

  • Accurate detection of the table structure of a line item containing documents like packing slips and the titles and fields in it for better line item detection.
  • All entries that are present in the packing slip like buyer details, seller details, product, quality, quantity, delivery date, etc can be extracted as JSON output that can enable the building of customized apps and platforms.

While offering a great API & documentation for developers, Nanonets is also ideal for organizations with no in-house team of developers as it is a truly no-code tool. Some specific advantages that make Nanonets ideal for data capture from packing slips are:

  • Nanonets can be integrated with most CRM, ERP, content services, or RPA software.
  • Multiple language processing: Nanonets OCR can recognize handwritten text, images of text in multiple languages at once, images with low resolution, images with new or cursive fonts and varying sizes, images with shadowy text, tilted text, random unstructured text, image noise, blurred images and more. This is, as can be understood, particularly relevant to deliveries between different countries or must transport goods between regions that use different languages.
  • Independence from formats: Nanonets are not bound by the template of documents.
  • Many data entry tools like Nanonets, come with a robust technical assistance team that can help overcome the challenges and harness the full potential of automated data entry operations.

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Take away

Data extraction from packing slips can be a laborious process when performed manually. AI-driven OCR software like Nanonets can help automate the process and remove the redundancy and dreariness from the activity. The use of AI-OCR in the final step of the Purchase-to-Pay functionalities provides time and cost savings, streamlined data management, and ultimately better bottom lines.


Nanonets online OCR & OCR API have many interesting use cases that could optimize your business performance, save costs and boost growth. Find out how Nanonets' use cases can apply to your product.