Document digitization and automation in supply chain and logistics

    Indice contenuti

  1. Document digitization: why does the logistics industry need to become more digital?
  2. Not the same thing: Digital preservation and Digitization for data entry purposes
  3. Document digitization with automated document reading and data entry
  4. How is Intelligent Document Processing different from the OCR technology?
  5. What kind of logistics documents can automatically be digitized?
  6. Why do supply chain and logistics companies select document automation?
  7. Conclusions
  8. Notes

The logistics industry has traditionally relied heavily on paper-based documentation, from invoices and packing lists to bills of lading and customs declarations. However, as the global supply chain becomes increasingly complex and fast-paced, many companies are realizing the need to transition from paper to digital documentation. This shift towards digitization is driven by a number of factors, including increased efficiency, improved data accuracy and reduced costs – not to mention significant advances in crucial emerging technological areas, such as AI.

Some confusion can emerge in understanding the difference between digital preservation and digitization: while they are often used interchangeably, there is a distinct difference between them. Digital preservation involves ensuring that electronic files are stored securely and can be accessed in the future, while digitization refers to the process of converting physical documents into digital format. In the context of supply chain and logistics, digitization is essential to streamline operations, reduce the risk of data loss, and provide real-time access to information.
One of the key aspects of document digitization is automated document reading and data entry. This involves using specialized software to automatically extract information from paper-based documents and enter it into digital systems.
This eliminates the need for manual data entry, which is time-consuming, prone to errors, and often results in missing or incorrect information.

Companies have different ways to start up their process of document digitization: Intelligent Document Processing (IDP) is an advanced form of document digitization that goes beyond traditional Optical Character Recognition (OCR) technology. While OCR simply recognizes text in an image and converts it into machine-readable text, IDP uses advanced algorithms to analyze and interpret the content of a document, including the structure and context of the information. This enables the software to automatically extract data from more complex documents and to understand the relationships between different data fields.

Of course, there are many types of logistics documents that can be digitized using automated document reading and data entry technologies – invoices, purchase orders, packing lists, bills of lading, customs declarations, pickup requests, airway bill, quality certifications, proof of delivery and so on.
These documents contain a wealth of information that is critical to the smooth operation of the supply chain, such as product details, shipment tracking information, and financial data.

The reason why supply chain and logistics companies increasingly select document automation technologies is because they offer a number of benefits over traditional paper-based processes. These include improved accuracy and efficiency, reduced costs, enhanced visibility into the supply chain, the elimination of repetitive tasks for human workers in favor of more high-added-value ones. With digital documentation, logistics companies can ensure that they have the information they need, when they need it, to make informed decisions and maintain the smooth operation of their supply chain.

Document digitization: why does the logistics industry need to become more digital?

Document digitization has dramatically affected nearly every aspect of the business world. Companies are very much aware of the benefits that digital technologies can provide. However, according to Gartner, more than 50% of organizations have not yet actively started to build a roadmap for supply chain digital transformation¹. The reason can vary from business to business but often companies find themselves struggling to transition from paper-based to digitized operations. 

Document digitization is the process of transforming paper documents into a digital format. In other words, it means creating a digital version of them. This can be done with various tools and techniques like scanning the document and converting it into a PDF, or by using a document management system to create an electronic version of the document using OCR software or intelligent document processing systems (IDP)

To remain highly competitive, businesses must keep pace as the world moves increasingly toward digitalization and automation. This is especially true for supply chain operations where collaboration and end-to-end visibility delivers unparalleled value in production, inventory management and product fulfillment. By updating systems and digitizing your supply chain, you will better equip your business for present needs and future demands. 

Logistics is a paper-heavy and fragmented industry, which means there is a paper trail for every single process, including managing and tracking inventory in warehouses, shipping goods from overseas, and moving from distribution centers to stores. Regardless of the type of operation, there are hundreds of documents confirming a single activity.
While this means everything is traceable, lost or damaged documents can cause serious difficulties.
Papers containing even the smallest errors can be impossible to track, resulting in delayed or canceled shipments or can end up costing thousands even millions of euros for the business². Repetitive tasks like inputting data into systems like ERP, TMS or WMS, are the activities that are open to these kinds of errors. 

“Papers containing even the smallest errors can end up costing thousands, even millions of euros for the business.”

Therefore, there can be two fundamental reasons for logistics industry to go digital: 

1. Paper alone is not reliable in logistics

In a paper-based supply chain, orders pass through many hands, oftentimes requiring documentation and creating the potential for error with every human touchpoint.
Paper can cause errors. ​It’s just a fact that people will make a few mistakes when transferring data manually. And even a simple mistake – like typing in the wrong number or putting a decimal point – in the wrong place can lead to costly errors. ​A single mistake can cause significant problems for a company, such as shipment delay, lost items, damaged customer relationships, and overspending. In a digitized supply chain, improved data accuracy removes the need for manual re-entering of errors.
Also, it takes a lot of time to input data: the manual processing of paper-based documents such as purchase orders, invoices, and delivery receipts can be time-consuming, leading to slower processing times and delayed shipments. With digitization, companies can reallocate these resources elsewhere and grow faster. 


2. Non-digitized methods are not cost-effective

In a manually managed, non digitized supply chain, the cost of paper alone can be burdensome, not to mention the cost of printing, and storage, which can be significant, especially for large-scale operations. Moreover, manual processing of paper-based documents is more labor-intensive, resulting in higher staffing costs and slower processing times. Also, non digitized systems are more prone to errors, leading to additional costs associated with correcting mistakes, and potential lost revenue due to stockouts or overstocking.
Supply chain digitization reduces these recurring costs by making them obsolete.
Digitizing supply chains also results in more accurate ordering and spending. With the data collected, there is a more precise idea of the quantity of supply needed at any given time. This information allows for a more rapidly moving supply chain which means less capital is tied up in the supply chain.

“Non digitized methods are neither reliable nor cost-effective for supply chain and logistics.”

According to the National Research Council of Turin, annually 1.2 million tons of paper are consumed by Italian companies. This number escalates drastically for the U.S. There are more than 30 billion paper documents that are annually copied and printed by organizations³.
A McKinsey analysis indicates that the bill of lading accounts for between 10-30% of total trade documentation costs. Adopting an electronic bill of lading could save $6.5 billion in direct costs and enable between $30 - $40 billion in new global trade volume while improving supply chain resilience⁴.

Not the same thing: Digital preservation and Digitization for data entry purposes

Dematerialization and digitization of documents: these two terms involve not only the conservation of documents but also the document flows, the ways of creating and communicating / sharing documents. Dematerialization and digitization are two words that are often used, in the context of document management, as synonyms. In reality, they can (almost) not be regarded as equivalent at all.
Digitization is the transformation process which includes dematerialization.
Dematerialization concerns above all paper documents, not the whole process: by dematerialization we mean the process that leads to the creation of a digital document that replaces the original paper. There is no digitalization without dematerialization.  

The purpose of dematerialization is to manage data or business documents (contracts, invoices, claims, custom bills etc.) throughout the company and/or in the context of interactions with partners (customers, suppliers) in a completely dematerialized manner. Meaning all the data and information will be available in a digital format.
The dematerialization of a document flow and its treatment are made around three big steps, which form a process of dematerialization:

  • The digitalization, which involves a scanner but which is also a tool of recognition of fields and characters, in particular for the taking into account of form.

  • The archiving, which is manual or which can be partially automated while being based on the solutions of ADR (Automatic Document Recognition) or on knowledge management solutions, such as category and classification engines.

  • The transmission and evolution of the document requires the implementation of a process management tool.

The objective of this process is to ensure the digitization of all paper documents, to collect the data and then to exploit it for each company (customer, supplier, etc.). The dematerialization is applied to each entry of a document in the company. Logistics and supply chain companies are not exceptions. 

“The dematerialization is applied to each entry of a document in the company. Logistics and supply chain companies are not exceptions.”

Beyond dematerialization and digitization, one should also mention digital preservation. It is not correct to reduce technologies and methods used for digitization to digital preservation because while digitization is the conversion of paper-based documents into digital, preservation includes only the digital archiving part. 
Digital preservation is the conservation of all digital materials⁵, whether they were born digital, such as emails, websites, pdf files, excel files, whether they have been digitized from analog materials like scanned documents or documents processed with intelligent technologies.

Although digitization is often seen as preservation, this is not the case
Once an item has been digitized, that new version requires continuous, ongoing maintenance for as long as the record is to be kept. This presents huge cost and time implications for the facility (Sanett, 2013). Additionally, when it comes to digital materials, there is a large difference between storage and preservation: storage is simple, as there is enough space in hard drives or in the cloud for as much material as can be created.
But, even if the stored data is intact, it may not be available or accessible, due to technological changes or human error in naming conventions. Preservation, that is to say keeping the information available and usable for future generations, requires much more complex action.

So, let's sum up: digitization means finding the means to transform a paper-based document into a digitally available data.
Dematerialization is the process that leads to the creation of a digital document that replaces the original paper.
Document preservation is keeping the information available and usable for future generations. Digital preservation solutions like Google Drive, OneCloud or Dropbox will allow you to preserve your digital documents and data and share them with your partners and suppliers.
However, they will not take action by themselves in the very first step and “digitize” the documents: for this we have other technologies.

Document digitization with automated document reading and data entry

Document digitization has become an essential process for businesses across various industries.
With the increasing need to automate data extraction from physical documents, many organizations are turning to innovative technologies to streamline the process. Automated document reading and data entry is one such technology that is revolutionizing the way businesses handle their documents.
There are various methods and tools to perform the document reading and data extraction tasks, among which we can highlight the following: 

  • Manual data extraction

  • Optical Character Recognition (OCR) 

  • Intelligent document processing (IDP)

One of the most traditional methods is manual data extraction: this requires a human to initiate the action and enter the data from a paper-based document or from a digital document into another system. However, this method is time-consuming and largely prone to errors.
Optical Character Recognition (OCR) is another method that has gained popularity in recent years. This technology uses computer algorithms to recognize characters in a document and convert them into digital text. While this method is faster and more accurate than manual data extraction, it still has limitations in handling unstructured or semi-structured documents.
Intelligent Document Processing (IDP) is a more advanced method that combines OCR with Artificial Intelligence (AI) and Machine Learning (ML) techniques to automate data extraction from both structured and unstructured documents. IDP can accurately extract data from complex documents such as invoices, contracts, and purchase orders. It can also learn from past data and improve its accuracy over time.

“Automated document reading and data entry is one such technology that is revolutionizing the way businesses handle their documents.”

Manual data extraction 

Manual data extraction from documents can be a major challenge for supply chain companies, as they deal with a large volume of documents on a daily basis. The manual entry of data can be time-consuming and error-prone, leading to delays in supply chain operations and potentially costly mistakes. Traditional means of document processing depend on staff members to handle data manually. Whether it’s invoices, quotes, orders, packing lists, or any document — everything has to be manually read and keyed in, day in and day out.
It has been found that using OCR and IDP technology for document processing can improve data extraction accuracy exponentially.

It is now clear that manual data extraction from supply chain and logistics documents requires a significant amount of time and effort and is prone to errors, which can lead to inaccurate data and costly mistakes. Also, companies should always take into account that manual data entry is a labor-intensive process that requires a large workforce, which can significantly increase the cost of supply chain operations.
According to a 2018 Goldman Sachs report, the direct and indirect costs of manual data entry amounts to around $2.7 trillion for global businesses⁶.
Finally, manual data entry can lead to inefficiencies in supply chain operations, as it can be difficult to track and manage large volumes of data manually.

Document digitization tools can help users extract data from documents like invoices, transportation documents or custom bills and insert data like order number, client’s name, container number into your management system (ERP, TMS, WMS). 
This extraction process can be automated with the help of technology. Two most commonly used methods for automated document reading and data entry are the Optical Character Recognition (OCR) and Intelligent document processing (IDP). These methods do not require someone to read and extract data but can automatically make the data entry. Let’s see how these technologies help save time and reduce errors in these repetitive tasks. 

Optical Character Recognition (OCR) 

OCR (Optical Character Recognition) is the use of technology to identify printed or handwritten text characters inside digital images of physical documents, such as a scanned paper document. The basic process of OCR involves examining the text of a document and translating the characters into code that can be used for data processing. This technology sometimes can be referred to as text recognition⁷. Usually, OCR technologies have two components: hardware for the digitalization of the document and software for converting documents into machine-readable texts. The software can leverage AI technologies. 

OCR is a part of Computer Vision, which is a field of Artificial Intelligence that enables computers to interpret and understand visual data from the world around them: in short, computer vision technologies work much the same as human vision. It involves using algorithms to process and analyze images, videos, and other visual data to extract meaningful information. When trained, these systems can inspect or analyze thousands of images, noticing issues imperceptible to human eyes.
OCR is a specific technology within Computer Vision that involves identifying and converting printed or handwritten text in images or documents into machine-readable text. OCR is an important tool for digitizing physical documents and making them searchable and editable in digital formats. By leveraging Computer Vision and OCR technologies, businesses can automate and optimize many processes, including document management and data extraction.

Intelligent Document Processing (IDP)

Intelligent Document Processing (IDP) refers to the extraction of information from paper-based and electronic documents and the utilization of this information to enable the end-to-end automation of document-centric processes. It leverages Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP) and advanced OCR engines. 

IDP solutions capture, extract, categorize and analyze information from different types and formats and allow users to seamlessly integrate the output data into workflow automations. An IDP solution includes the following core capabilities⁸: 

In conclusion, Intelligent Document Processing (IDP) has revolutionized the way businesses handle document-centric processes. With its advanced capabilities such as AI, ML, NLP, and OCR, IDP solutions enable the end-to-end automation of document-centric processes. By capturing, extracting, categorizing, and analyzing data from different types and formats of documents, IDP solutions provide a seamless integration of output data into workflow automations. Overall, IDP offers a powerful and efficient solution for businesses to manage their document processing needs while increasing productivity and reducing costs.

“Intelligent Document Processing (IDP) has revolutionized the way businesses handle document-centric processes.”

For a supply chain company, IDP can provide significant benefits such as reduced processing times, increased data accuracy, and improved productivity. By automating document-centric processes, IDP can free up time and resources, allowing supply chain companies to focus on core business activities, resulting in improved efficiency and cost savings.

How is Intelligent Document Processing different from the OCR technology?

In today's fast-paced supply chain industry, the ability to quickly and accurately process large amounts of documentation is crucial. While optical character recognition (OCR) technology has been used for many years to digitize paper documents, a newer technology has emerged: Intelligent Document Processing (IDP). Unlike OCR, which simply extracts text from images of documents, Intelligent Document Processing uses Machine Learning algorithms to understand the meaning and context of the text. This allows for more advanced features such as automatic classification, data extraction, and even the ability to understand handwriting.
Since IDP and OCR are both data extraction technologies, they are often used interchangeably, and sometimes IDP is considered just another repackaged version of traditional OCR.
As a business decision maker, it’s important for you to understand the difference between the two to figure out which one is better suited for your business requirements.

“Intelligent Document Processing uses Machine Learning to enable automatic classification, data extraction, and even the ability to understand handwriting.”

Traditional OCR costs less than IDP but works only with template based standard documents, whereas IDP solutions are able to offer you the flexibility to work with semi-structured or unstructured documents with increased accuracy using AI, Machine Learning, Deep Learning and OCR. 
OCR is nothing new to document capture but has a few advanced years under its belt.
Traditional OCR, simply put, converts an image of text into machine-readable text. This process can be valuable for simple document digitization but leaves a lot to be desired beyond that.
Some of the main issues with traditional OCR are

  • Template-based only: traditional OCR is based on a template, i.e. documents to be processed must be formatted according to certain rules, otherwise, OCR cannot do anything with the documents;

  • Limited accuracy: traditional OCR technology is limited in its ability to accurately recognize and extract text from documents. It struggles to recognize characters that are distorted, skewed, or blurred, which is common in many real-world scenarios. This results in errors in the extracted text, leading to downstream issues with data quality and processing;

  • Inability to understand context: OCR technology is focused solely on extracting text from images and does not take into account the context of the document, and thus automated end-to-end processes are not possible. For example, it may not be able to distinguish between a product code and an order number, leading to incorrect data being extracted and processed;

  • Limited functionality: OCR technology is primarily focused on converting physical documents into digital form. While it can extract text from images, it does not have advanced features such as automatic classification or data extraction. This means that it cannot provide the level of automation and efficiency needed in today's supply chain industry.

OCR may be the solution in a few cases, such as when there is only one rule-based form. However, the reality in terms of the variation of documents that an organization works with on a daily basis is significantly different. Some fundamental issues for businesses cannot be solved with traditional OCR:

  • As soon as semi-structured, unstructured, and handwritten documents have to be processed, traditional OCR is no longer suitable; the creation and maintenance of templates for all formats is far too time-consuming and expensive

  • This makes traditional OCR unsuitable for large-scale implementation and scaling

Intelligent Document Processing (IDP) overcomes all these limitations with the additional help of AI, ML, and Deep Learning technologies, and it offers several benefits over OCR for supply chain management.
While OCR has nothing on IDP, IDP continues to use OCR as part of a powerful combination. OCR converts an image of text into readable text, and intelligent and advanced AI technologies, including Machine Learning and Deep Learning, do the rest. On the one hand, this makes IDP capable of mimicking cognitive abilities, i.e., capturing documents correctly, classifying them correctly, and extracting all relevant data from them. In addition, this relevant data can then be automatically fed into the correct workflows for further processing.

“Intelligent Document Processing overcomes OCR’s limitations with the additional help of AI, ML, and Deep Learning technologies.”

If compared with traditional OCR, Intelligent Document Processing is a more advanced technology in several respects:

  • Improved accuracy: IDP uses advanced Machine Learning algorithms to analyze and understand the text in a document, allowing it to recognize and extract text accurately, even if the text is distorted or skewed. This results in fewer errors and higher data quality, which is crucial for supply chain operations.

  • Contextual understanding: IDP can understand the context of the document, allowing it to identify the type of document, the key fields and data points within the document, and even the relationships between different data points. This allows for more advanced features such as automatic classification and data extraction, which significantly reduces the time and effort required for manual data entry and processing.

  • Greater functionality: IDP goes beyond OCR and offers a range of advanced features that can improve supply chain management. For example, it can automatically classify documents, extract key data points, and even understand handwriting. These features allow for greater automation and efficiency, enabling businesses to process documents faster and more accurately.

In conclusion, while traditional OCR technology has been useful in digitizing paper documents, IDP is a more advanced and powerful technology that offers significant benefits for supply chain management. With its improved accuracy, contextual understanding, and greater functionality, IDP is better equipped to meet the demands of modern supply chain operations, providing greater efficiency, automation, and accuracy⁹.

What kind of logistics documents can automatically be digitized?

As supply chain operations become increasingly complex, digitizing logistics documents has become essential for businesses looking to streamline their processes and remain competitive. Fortunately, there are no technical limitations to which logistics documents can be digitized, allowing companies to automate and optimize virtually any task. In this paragraph, we will explore the types of logistics documents that can be automatically digitized, including warehouse and shipping documents such as proof of deliveries and bill of ladings, as well as customer-facing paperwork such as invoices, statements, and receipts.
By identifying the most time-consuming tasks and related documents, businesses can leverage automation and digitization to improve their operational efficiency and reduce costs.
There are several logistics documents that can be automatically digitized to improve supply chain efficiency and reduce manual data entry errors¹⁰. These include:

  • Proof of Delivery (POD): POD documents provide evidence that a shipment has been delivered and are essential for billing and customer service purposes. Digitizing PODs can help speed up the billing process and allow for real-time visibility into delivery status;

  • Bill of Lading (BOL): A BOL is a legal document that details the type, quantity, and destination of goods being transported. Digitizing BOLs can help automate carrier selection and routing, and improve the accuracy and speed of invoicing and payment processes;

  • Instructions for the Bill of Lading: Many companies offering transportation services receive specific instructions from their clients regarding which information to include in the bill of lading. Often this is one of the most time-consuming activities for who is responsible to create the BOL. Therefore, digitizing and automating this activity can accelerate the overall BOL creation process; 

  • Packing Lists: Packing lists provide a detailed summary of the contents of a shipment and are important for ensuring that the right items are delivered to the right destination. Digitizing packing lists can help automate the picking and packing process, and reduce the risk of errors;

  • Transport document: The transport document, or delivery note, is a document which must be issued by companies to justify or prove the transfer from one place to another of goods, raw materials, subject to a commercial transaction, even in the case of two plants of the same company. The digitalization of the transport document improves the logistic processes in general. Choosing the digitalization of transport documents means definitively abandoning paper to simplify processes and improve them. In fact, the Italian legislation of the transport sector provides that transport documents can either travel physically with the products or be sent electronically;

  • Invoices: Invoices are an essential part of the billing and payment process, and digitizing them can help speed up payment cycles, reduce errors, and improve visibility into outstanding payments;

  • Pickup requests: Whether a company receives pickup requests via email or pdf files (or in other formats), often this information is elaborated by a person in order to put this request in motion, so as to create a shipment on the company’s transportation management system. This activity can easily be automated in order to speed up operations; 

  • Airway bill: The air waybill (AWB), also known as an air consignment note, is the most important document issued by an air carrier either directly or through its authorized agent. It is a non-negotiable transport document that covers the transport of cargo from airport to airport. By accepting a shipment, an IATA cargo agent is acting on behalf of the carrier whose air waybill is issued. Digitizing and automating AWB can indeed contribute positively to the elaboration of this document without any errors; 

  • Spot offers request: For many companies this can be an overwhelming back office activity since it is crucial to read and answer rapidly to spot offer requests in order to engage the potential client. Managing spot offer requests – even when they are sent over via email with a colloquial email text – with automated and digitized methods can directly influence the number of requests elaborated and the clients engaged; 

  • VGM: Verified Gross Mass (VGM), another important document for the logistics and transportation companies, describes the weight of the cargo including dunnage and bracing plus the tare weight of the container carrying this cargo. It is provided by the shipper to the ocean carriers and/or port terminal representatives prior to the load list cut-off date. Being able to extract this information in an automatic way can be crucial for some transportation operations; 

  • Cargo Manifest: A cargo manifest, a consolidated list of all the cargo that is on board a cargo vessel, will appear under the vessel name and identification marks of the vessel. Typically, a cargo manifest would list all the bills of ladings along with the above details and the total number of goods being transported, shown per bill of lading. Therefore, just like the BOL, it is very much important for companies to digitize and automate cargo manifest elaboration to improve the accuracy and speed of back office activities. 

Generally speaking, by digitizing these and other logistics documents, businesses can improve supply chain efficiency, reduce manual data entry errors, and gain real-time visibility into their operations.
Let’s dive deep into some use cases of logistics documents automation that you can set up with the help of Wenda’s Intelligent Document Processing technology: 

Invoice/Customs Bill/PL/Email/BoL = Container tracking

Translate multiple, different documents into Bill of Lading instructions, up to container or air cargo track&trace, and upload any logistics document to the Wenda platform.
Wenda's AI identifies and extracts relevant data, which is then automatically uploaded to the platform for container tracking.

Transport document = Goods Entry into WMS

With this automation you can transform pdf delivery note data into tracking and input data on the WMS, and you can later display the data on the Wenda Platform or BI.
The delivery note is uploaded to the platform, Wenda's AI identifies and extracts relevant data, and finally the data is uploaded to the WMS and can also be viewed on the Wenda Platform.

EASA + Air Waybill (AWB) + Invoice = Sharing in ERP

Automate the sharing of airline business administrative and compliance data with shipper and consignee. You can select any logistics document and upload it to the Wenda Platform.
Wenda's AI identifies it and extracts the relevant data, which is then uploaded to the TMS and shared with the supply chain network.

“By digitizing these and other logistics documents, businesses can improve supply chain efficiency, reduce manual data entry errors, and gain real-time visibility into their operations.”

Here follows almost a full list of logistics documents that Wenda can process, automatically digitize and set up to fit in an automated workflow:

  • Spot quote request 

  • Pickup requests (LTL or FTL)

  • Packing lists

  • Bill of lading

  • Packing bill / Delivery note

  • Cargo manifest

  • VGM

  • Custom bills

  • Airway bills

  • Proof of delivery (POD)

  • EASA certificate

  • Certificate of origin

  • Certificate of compliance

  • Advanced shipment notices (ASN) 

  • Declarations

  • Claims

  • Invoices

Why do supply chain and logistics companies select document automation?

As you know too well, the logistics and supply chain industry is notoriously complex and relies heavily on manual processes, including paper-based communication and manual data entry. With so much communication taking place among various stakeholders, including customers, suppliers, freight forwarders, and carriers, there is a high risk of errors and delays, leading to inefficiencies and increased costs.

1. Increase productivity, reduce errors

A significant amount of information necessary for critical supply chain and logistics operations is still manually extracted from various data sources, including emails, spreadsheets, and existing systems such as ERP, TMS, and WMS.
As we saw before, problems with manual document processing include time-consuming tasks, data entry errors, and the high risk of lost or misplaced documents. Additionally, manually extracting data from documents is a tedious and error-prone process that can lead to inaccuracies and inefficiencies.
To address these challenges, many supply chain and logistics companies are turning to document automation solutions to streamline their processes, reduce manual data entry errors, and improve operational efficiency.

2. Reach more clients with less effort

For logistics and supply chain companies, document automation solutions will have a direct impact on how they serve and respond to their clients. Automating time-consuming manual methods will allow customer service personnel to respond rapidly to requests and resolve problems. Moreover, this will help customer service to free their valuable time and use it to serve more clients during the working hours.
Document automation technologies do not require pauses and rest. This will assure a 24/7 availability and service guarantee for the customers. Even when the customer service is based in Italy but the client herself/himself is based in China. Automation and automated data entry will guarantee the continuity of the service while the staff enjoy their well-deserved pauses, weekends, free times and holidays.
Document automation is a way to do more by doing less. 

3. Keep up with digital transformation

Automated document generation adoption rates keep growing. By 2025, the global document management system market will reach $10.17 billion with a 13% CAGR¹¹. While software vendors launch more advanced systems, businesses readily implement the offered innovations. They shift from cumbersome paper document management to fully automated document generation.
Also, companies plan to spend more on automating their business processes and innovations. By 2026, global digital transformation spending is forecast to reach $3.4 trillion¹².
The growing demand for automation solutions gives a boost to document automation, since automated document management is an essential part of the digital transformation of any system and one of the first steps to take.


Automated document processing solutions can significantly improve supply chain and logistics operations. By automating document processing, businesses can streamline workflows, reduce manual errors, and gain real-time visibility into their supply chain operations. Automated document processing can also help eliminate the need for manual data entry, which reduces the risk of errors and frees up employees to focus on more strategic tasks.
Another benefit of using automated document processing solutions is improved data accuracy. By automating the document processing and data extraction process, businesses can ensure that the data captured is accurate and complete, leading to more reliable and timely decision-making.
Finally, automated document processing can help improve collaboration and communication among stakeholders by providing real-time access to critical supply chain data. This can help reduce the risk of delays, errors, and miscommunications, leading to improved supply chain efficiency and customer satisfaction.

Now is the time to start digitizing your logistics documents and fully automating your supply chain workflows!


1. Gartner, Supply chain digital transformation

2. According to The Data Warehouse Institute, upwards of $600 billion every year can be attributed to data entry errors in the supply chain, data procurement, and other vital areas, exposing organizations to compliance risks in addition to a large amount of wasted money and resources. More info in the following articles: [1], [2], [3]

3. Omdia, Market Landscape: Intelligent Document Processing

4. The multi-billion-dollar paper jam

5. See S. Routhier Perry, Digitization and Digital Preservation: A Review of the Literature, School of Information Student Research Journal, San Jose State University, 2014, here

6. Goldman Sachs, How the next payments frontier will unleash small business, 2018

7. TechTarget - OCR

8. TrustRadius- Intelligent Processing Systems

9. See here for a general discussion of the differences between OCR and IDP

10. Check this article for a more detailed list

11. See here

12. See the report by Statista called Digital transformation - Statistics & Facts

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