From spreadsheets to the cloud: How to transition from manual to automated data capture

If your company is dealing with lost documents, complaining vendors or customers, duplicate payments, and errors, you may want to re-evaluate your manual data capture system. You can do so much with automated data capture, such as extract data from images.

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How to extract data from images

Years ago, all incoming documents for a business would be processed manually by data entry clerks. However, just because this is how it used to work does not mean that this process was efficient. Manually processing hundreds and thousands of invoices is extremely time-consuming, tiresome, and frequently prone to errors. As technology advances, there have been improvements to this traditional system. In today’s society, many businesses are using technology solutions that help them more quickly and accurately process incoming documents. 

Most of these solutions utilize optical character recognition (OCR) technology. Essentially, this technology extracts the important data from a document, such as a PDF invoice or payment receipt. Template-based solutions that use OCR technology require rules and guides to function effectively. These solutions help to accurately extract text from an image online or extract other data from incoming invoices or payment documents. And while these solutions can be beneficial, they are still prone to errors when the rules do not apply to a new document format.

People ran into issues with this implementation of OCR technology. When you interact with a new vendor or one of your current vendors changes their document layouts, you have to create new rules and templates for the OCR technology to function correctly. When it is not properly able to read and process the information on the document, it can lead to errors in the data you are collecting. In accounts payable or other financial processes, this can be incredibly costly. 

If technology has been continually advancing, what is the next solution after OCR technology and template-based data capture? As technology evolves and businesses delve further into the use of artificial intelligence (AI) technology, we get our next and most recent solution. When collecting data without templates, intelligence is often the best course of action. 

While human intelligence is a great way to avoid issues with the layout of a document and focus on simply the important information in it, humans are also quite error-prone. In order to make the best use of intelligence and technology, businesses can utilize cognitive data capture solutions. These solutions use AI technology to extract text from an image or otherwise collect important information from a document without taking breaks or getting distracted. This technology helps extract tables from images and extract tables from a PDF to Excel. 

Extract data from an image graph

When retrieving data from documents, it can be difficult to find a solution that does not come extremely expensively. Because of this (in addition to reluctance to embrace a digital solution), many businesses still employ manual data entry. And while this method was used in the past, with the increase in digital invoices and other important documents coming in each day, it can take way too long for a team of employees to manually process all of that information and manually retype the data from those documents. 

When it comes to how to extract a table from a PDF both quickly and accurately, manual data entry is not going to be the best solution. You don’t have to extract table data from a PDF to Excel manually or extract tables from an image to Excel manually. Rather than having your accounts payable employees spend hours of their days manually re-entering data from one document to another — which can be extremely draining and demoralizing work for many employees — it may be better to instead utilize a software solution to extract a table from a PDF programmatically.

Two main technological advancements can help you to extract data from the documents that are coming into your business each day. The first of these technologies is called template-based data capture. This method consists of optical character recognition (OCR) technology that can recognize text in a document or image and automatically “rewrite” that data in a more standardized location where you keep all of your data. 

For example, if you want to extract a table image to Excel where you may store all of your data, using OCR technology can help you with this. Image to Excel OCR technology can be more efficient and accurate than manual data extraction. However, it is important to note that as “template-based” data capture, software solutions using OCR technology are not 100% foolproof. 

The issue that businesses can run into with these technologies is that unless the incoming document is in a format that you have made rules and templates for, you will need to put extra work into creating new rules and guides for the technology. And over time, this can be time-consuming and costly. Cognitive data capture is the second technological advancement that can help you to process invoices and other important document data more effectively (and quickly).

This is essentially artificial intelligence that can help you to more accurately and quickly process your documents with up to 98% accuracy and up to 6x faster than traditional manual data entry. The AI can extract a table from a PDF to Excel or convert a graph to data in Excel without needing to take breaks or getting distracted by anything so you can easily process more data each day than you would be able to with human data processors.

How to convert an image to text in Excel

As society continues to push towards a more digital world, it is incredibly important that businesses can keep up with the advancing technology. Artificial intelligence (AI) and optical character recognition (OCR) software are some examples of new technology. Not keeping up risks falling behind competitors when it comes to customers and suppliers. Oftentimes invoices, payments, receipts, claims, and more are all done digitally today, but just doing something “digitally” is not enough. 

Since there are many different types of digital documents, you must ensure that anyone who needs to access a document can do so. This is why many businesses will use PDFs for these types of documents because no matter what system or device you are using you can open and view a PDF. However, while PDFs are great for sharing information across platforms, devices, and systems, they are oftentimes not the easiest to digitally extract data from.

Think about it like this. Have you ever tried to copy-paste something from a PDF — to edit it, use it as a quote, add it to a presentation, or anything else — and when you press “paste” on your document, presentation, or other space it comes out as a jumbled collection of words that you need to go through and re-format? 

This is exactly what can happen with data as well. So, whether you are trying to extract data from an image in Excel or convert a picture to Excel, simply trying to copy-paste will likely just result in a lot of wasted time spent cleaning it up. This is why there are many different approaches to how to best get information from a PDF. 

There are many technology (like OCR) solutions available today to help businesses address this issue. With OCR solutions, there is an entire wealth of knowledge that can be accessed with a simple web search that can provide additional guidance. For example, if you are trying to figure out how to convert an image to text in Excel or an image to a table in Excel, all you need to do is a simple Google (or another search engine) search and you’ll likely find a simple answer.

Extract text from an image

If you are trying to extract text from an image you are likely to run into the same, or a similar, issue as if you are trying to extract data from an image. The problem with trying to simply extract information by using copy-paste features is that in a flat file, like an image, the data is not formatted in a complex way. When you copy something from a more complex file, things like layout and formatting can be copied. In an image or PDF, however, there is no intrinsic “layout” or formatting information to make that copied text retain its layout in the PDF or PDF image.

Because of this, if you want to avoid inefficiencies in your processing of flat files, like images, you need to ensure that you have the right tools and processes. Rossum AI is one example of a document processing software that can give you those tools. The Intelligent Document Processing (IDP) solutions are specifically designed to transform semi-structured and unstructured information into usable data. Essentially, these solutions can help you to more effectively and efficiently extract valuable information from PDFs and other flat files.

Rossum’s IDP solutions can help businesses access the business data stored in emails, images, business documents, and PDFs so that they can more accurately understand what is going on in their businesses. These unstructured or semi-structured documents house about 80% of a company’s business data. Without the tools to effectively process these documents, a business could be missing out on an incredible amount of its overall data.

The best image to Excel converter

Since so many businesses utilize PDFs as their preferred method of sending documents, it is vital that you ensure that your business has an effective method for processing the data from these notoriously difficult to process files. You can use any number of methods to extract text from an image Google result or another flat image file. Businesses can use four main strategies to convert the data from these file types, and many companies find themselves wondering which is the best image to Excel converter

The first of these methods is manual data capture. In general, manual data extraction is not the most efficient method because it is very time-consuming and quite error-prone. Unfortunately, this method is also not very scalable and can result in some extremely costly mistakes along the way as well.

The second method is PDF to Excel conversion software solutions. Essentially, these software solutions help to more accurately and quickly extract data from your invoices or other documents and transfer that information to your Excel spreadsheet for analysis and logging. These solutions can be more effective than manual methods, but they also depend on the layout of documents. They can also require manual tweaking, which is time-consuming.

The third method is quite similar to the second one. This method is called template-based PDF to OCR (optical character recognition). This software can quickly and accurately transfer data from the invoice PDF to an Excel spreadsheet like the previous method. Additionally, its effectiveness and speed are dependent on the number of different formats of invoices you are receiving. The last method is cognitive PDF to OCR. Essentially, you are using artificial intelligence software rather than using software similar to the PDF to Excel converter software. Over time, this software will get more accurate and intuitive as it learns to recognize data fields from your type of document and layout, and it will lessen the amount of time needed to spend tweaking it. The longer you use it, the less time you need to spend editing the data it processes.

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