What Is Document Data Extraction?
Digital transformation saves businesses time and money
Just consider your current document processing workflow. From invoices to customs documents, transport and logistics companies rely on the ability to categorize—and analyze—data from their files. Effective document processing is key to making intelligent decisions.
Now, processing incoming documents once took significant company time and resources—but today it can be automated.
To automate the way that you process those documents, you will need to extract the data from them using automation. This process is known as automated document data extraction.
This article will offer an overview of automated document data extraction and describe the benefits of this process. Be sure to reach out if you have questions (or to schedule your free demo) once you finish reading.
The Meaning of Document Data Extraction
Document data extraction involves retrieving meaningful information known as data from documents. Generally, the data is pulled from unstructured or semi-structured sources for processing and storage.
As we mentioned in our introduction, this process can—and should—be automated. Intelligent document data extraction features the use of advanced artificial intelligence (AI). The idea here is to use AI to pull data from the documents to derive meaning from them, and to use that meaning to make future decisions.
We’ll discuss this in more detail shortly. First, let’s review the concept of document processing.
Document processing generally involves the following steps:
Transforming a document into a digital version (if relevant).
Interpreting the structure of the document.
Identifying the most relevant content in the document.
Determining the category via the document’s defining features.
Extracting the content from the source document.
Leveraging the data from the document to increase productivity.
All of these steps can be automated—more effectively than ever nowadays. Consider image and text recognition, just two of the areas where AI has resulted in serious performance improvements lately. Our clients can’t emphasize enough just how much automated data extraction has improved in the last decade.
Through the use of AI technologies like machine learning and natural language processing, you too can automate your document processing. This will result in a more efficient document data extraction process.
Why Does Document Data Extraction Matter?
Companies looking to automate their back-office activities rely on data extraction. Most documents today can be processed automatically so long as they can be converted into structured data. This makes data extraction quality the biggest roadblock to automated document processing.
In some cases, manual processing is still important. Processes like ensuring VAT compliance, for example, may stay manual because the most important data isn’t necessarily extracted from the documents right off the bat. Down the road, this too can be automated.
The truth is that where automated data extraction is concerned, a high level of quality is well within reach. Automated document data extraction ensures the most critical processes—think payment in the case of an invoice—are taken care of.
So is automated document data extraction worth it?
The answer is a resounding yes. A report from the MIT Initiative on the Digital Economy (MIT-IDE) associated business management practices that involve data collection with higher operational performance. Meanwhile, decision-making based on data extracted from different sources resulted in a productivity spike of 3%.
Not only that, but the market for automated document processing solutions is slated to reach $4.1 billion by 2027.
A report conducted by Allied Market Research explored the data extraction market by component, data type, and industry vertical. It found that the global data extraction market—valued at $2.14 billion in 2019—is expected to exceed $4.9 billion by 2027.
Clearly there’s a great deal of potential here. Verticals like transport and logistics are no exception, as automated document processing and document data extraction enable digital transformation. Companies will save time and money, and work much more efficiently, by using AI in their document processing.
How to Automate Your Document Data Extraction
Many companies are eager to automate their document processing but don’t know where to start. For organizations dealing with dozens or even hundreds of forms each day, automating processes like document data extraction may seem intimidating. Yet it’s imperative.
Starting with an initial project will allow you to pinpoint which documents or processes would benefit most from automated data extraction. This, ideally, will help your team convince corporate leaders to consider using even more AI. Widespread automation, including automated data extraction, can make a real impact on your bottom line.
To get started, focus on high-volume documents first. You’ll want to hone in on metrics such as the:
This can be challenging to estimate. However, the document volume and overall complexity can give you a sense of how much your company is currently spending on document processing. From there, you can highlight the most expensive documents that will likely be worth automating.
Scope of document processing
After extracting the data from your documents, you’ll want to evaluate what your team currently does manually. Take invoices as an example. After extracting the data from your invoices, you’ll find that processes like VAT compliance checks can absolutely be automated afterward.
Availability of data extraction tools
Regardless of the document, there is almost certainly an automated solution you can use to extract the relevant data. Our team works closely with clients to build custom AI and machine learning models—helping teams process their documents with greater efficiency and accuracy.
To automate your data extraction, consider working with a trusted partner like Mely AI. We’ll walk you through all the steps you need to strengthen your document processing using artificial intelligence and other automation solutions.
Alternatives to Automated Document Data Extraction
Manual data extraction is a common alternative to automated extraction. This approach, however, is generally slow, inaccurate, and expensive. It can also be gruelling for back-office personnel, many of whom would much prefer to automate their document processing and focus on other core tasks.
Template-based strategies are yet another option. This approach lets teams create templates that capture data from documents using a specific format. However, due to the range of document formats that exist today, it can be challenging to achieve substantial automation with template-based solutions.
Automated data extraction is likely the best solution when it comes to extracting the most relevant data from your documents.
Automate Your Document Processing with Mely AI
Automating your document processing can help your teams work more productively, reduce employee workload and stress, and increase your bottom line. The benefits for companies are truly expansive.
So automate your document data extraction with our skilled team. We’ll capture data from your documents instantly—decreasing manual effort and turnaround times. Talk about a win-win.
Are you ready to get started? Book your free demo with Mely AI today.