What is Automated Data Processing? Definition and Real-life Examples

What is Automated Data Processing? Definition and Real-life Examples

In today’s fast-paced digital world, managing business data manually can be time-consuming, error-prone, and inefficient. This is where automated data processing comes into play. It involves using technology to perform data-related tasks, significantly improving efficiency, accuracy, and scalability. In this blog, we will explore the concept of automated data processing, its key components and technologies, and the benefits it offers. We’ll also delve into a real-world example to illustrate how it works in practice.

What is Automated Data Processing?

Automated data processing refers to the use of software and hardware systems to perform tasks such as data collection, extraction, validation, processing, storage, and analysis automatically. This automation can handle large volumes of data quickly and accurately, reducing the need for manual intervention and minimizing the potential for human error.

Key Components and Technologies Involved

Intelligent capture automates content input using OCR and machine learning, which removes unnecessary steps and increases the velocity of routing relevant data to the right users and systems.

Automated Faxing

Automatically receive and send digital faxes to preconfigured numbers based on workflow triggers, without manual interventions

Machine Learning

Users can train the system to continuously learn and improve document capture and processing based on feedback from users

Monitoring and Analytics

Analyze and assess document workflows, based on unread files, pending files, expiring files, number of documents per workflow etc.

Limitless Process Integration

Seamlessly connect with back-end databases, content management systems, EMRs, ERPs, and any other internal systems.

Benefits of Automated Data Processing

  • Speed: Automation can process large volumes of data much faster than manual methods.
  • Accuracy: Automated systems reduce the risk of human error, ensuring more accurate data processing.
  • Scalability: Automated data processing can easily scale to handle increasing volumes of data without a proportional increase in resource requirements.

Real-World Example of Automated Data Processing

Invoice processing is a critical business function, especially in the retail industry, involving the receipt, validation, and recording of invoices from vendors. Manual invoice processing can be labor-intensive and prone to errors, such as data entry mistakes and lost documents. The automation addresses these challenges by streamlining and digitizing the entire workflow.

One notable example is Longo’s, a major player in the Canadian retail sector, which successfully eliminated labor-intensive tasks and significantly enhanced its efficiency in invoice processing through Process Fusion’s PF360 Capture solution.

Longo’s Case Study with Process Fusion’s PF360 Capture

Longo’s, a well-known grocery chain, faced significant challenges with its manual invoice processing system. The process was time-consuming and became increasingly burdensome as Longo’s grew, requiring more staff to manage the escalating volume of invoices. By implementing Process Fusion’s PF360 Capture solution, Longo’s was able to automate the entire invoice processing workflow, from data collection to reporting and analytics. Here’s how they did it:

steps of how automated invoice processing work


Automated data processing is a powerful tool that can transform how businesses handle their data, offering significant benefits in terms of speed, accuracy, and scalability. The example of automated invoice processing illustrates just one of the many applications of this technology. As businesses continue to generate more data, the importance of automation will only grow.

Curious to learn more about how the automation can work in your industry? Book a consultation with our experts today!