Who is the fastest for data entry process – Human
or AI?

To prove how inefficient and costly the manual data entry process is, we decided to pit the manual approach against an AI-powered solution. This should settle who the real champion of data capture is once and for all.

Data entry process: opportunities and shortcomings

Businesses of all sizes and industries today are getting more incoming information to process. 

This trend is not looking like it will slow down anytime soon. As more businesses are joining the digital marketplace, advertising to their target audiences, gaining more customers, and gathering data to create more personalized marketing campaigns, it is no surprise that many of them are swimming in the amount of information they need to process each day. 

Even for small businesses, it can be challenging to keep track of and accurately process all of the information that is coming in. Because of this, there has been a rise in software solutions that improve and streamline the data entry process. We will discuss these solutions later on.

Unfortunately, not all data entry methods are created equal, and many companies still utilize manual data entry as their primary data capturing method. First, let’s talk about manual data capture because this system is used to process 90% of invoices globally today.

Manual data entry may seem like the best solution because you do not need to pay any upfront costs (such as the cost of a software system and training to use that system). With manual data entry, you can simply give many different employees a stack of data to manually enter. 

However, manual data entry is incredibly error-prone, and using this process can lead to costly mistakes that could have your business paying a lot of money to solve a simple mistake that causes problems down the line. 

According to the 1-10-100 rule, you spend less on error prevention than you do fixing mistakes that were made by relying on manual data entry. The rule is as follows: error prevention will cost $1, and error correction will cost $10, but an unchecked error that causes a problem or failure in your system or processes down the line will cost $100. When you consider that manual data entry is highly error-prone, those hundreds of dollars can add up.

What is the data entry process?

Before we get into some of the other, more effective, data entry systems available today, we need to establish what data entry is and how to learn data entry. So, what exactly is data entry? 

Data entry is clerical work that collects data from one location and copies it into another — more easily analyzed — location for further action. In other words, data entry is how people transition their available data from various formats and locations into one single, centralized location that can be easily accessed, organized, and analyzed. 

Now, as we addressed earlier, many businesses use manual data entry methods because they can seem like the cheapest way to process the vast amounts of incoming data businesses are getting each day. 

However, as we also learned, manual data entry can be highly time-consuming and error-prone and can lead to higher costs down the road. This is why other data capturing solutions available for businesses today can help to simplify and optimize the data entry process. 

These solutions use optical character recognition (OCR) technology. There are two different types of OCR solutions: template-based and cognitive.

Template-based OCR solutions read documents and capture the data in them by using a predefined set of templates and rules. The downside of these systems is that you will need to constantly set up new rules for them to accurately be able to process information that comes in a different format or new document layout. 

Cognitive OCR solutions use artificial intelligence (AI) technology — like machine learning and natural language processing — to understand the information it captures. These systems do not need to be continuously maintained, and they get more effective with regular use — just like a human would — because they are constantly learning and applying new knowledge.

How to create your own data entry process

Many businesses may continue to use manual data entry because of the wide variety of document formats and semi- or unstructured data sources. It can be challenging to keep up with the constant maintenance of a template-based OCR system

In other words, it is much easier to trust a human’s data entry skills and abilities over a software solution that extracts data based on templates and rules. 

There is a new contender that businesses can use to improve their data entry processes greatly. This is the artificial intelligence (AI) solution to data capture — the cognitive OCR software. This system uses machine learning, natural language processing, and deep learning to understand the information it is entering and gets more efficient over time. 

In a data entry skills test we performed at Rossum, it took Adam (a data entry specialist) 8x longer to process the same number of invoices as Julie (an AI associate). Julie used Rossum’s AI-powered data entry solution to more efficiently process the data coming in. 

This way, Julie was able to beat Adam — even with all of the data entry skills that he gained from being a data entry specialist. Now, you could think that maybe the right solution for you is to figure out how to improve data entry skills and techniques for your data entry specialists. 

The most effective way to help better your data entry system is to utilize an AI-powered tool like Julie did in the Data Entry Championship. Luckily, you can use the same technology that Julie used to quickly and easily transform your manual data entry processes into more effective automated processes.

The key is to transition your current data entry clerks into AI associates and train them to use a powerful AI solution.

Data entry process training: tips and tricks

With the incredible evolution of technology and software solutions in society today, it is surprising that around 90% of invoices are still processed using traditional manual data entry methods. Even with a highly trained and efficient data entry specialist, processing a single invoice can take minutes rather than seconds

Considering all the information coming in each day, it is no surprise that data entry specialists spend their long and monotonous workdays in a state of boredom and stress, leading to attrition and greater opportunities for errors in your AP process. 

Data entry training online is not as easy as it may have been in the past. Years ago, data entry training and placement meant learning to copy information from one format to another with accuracy. If you could do that, you would be able to get a data entry certification. 

Because of this, many businesses simply add data entry tasks to their employees’ workload — resulting in about 30% of their time manually entering data. However, this process is highly time-consuming and prone to mistakes that can be costly down the line.

Despite the advancements in technology offering a new and more efficient way to enter data using artificial intelligence technology, there are still data entry jobs available on the market. 

Businesses continue to hire data entry specialists to manually capture the incredible amounts of data they need to process. Companies should, however, be focusing the time that they spend manually entering data on other more value-added tasks. With an AI-powered solution like Rossum, you can more effectively and quickly process invoices (or other documents) and make time for other tasks. 

Rather than taking minutes to process each invoice, with the help of AI, your employees can spend just seconds reviewing any captured data with low confidence scores and making corrections. 

So, rather than taking the time to put your employees through complicated data entry training, it can be more beneficial for your company overall to invest instead in training your employees to be AI associates

Onboarding with Rossum takes only 10 minutes, and you can go from processing less than one document per minute to processing multiple documents per minute.

Best software to enhance the data entry process

When selecting a data entry software solution for your business, you likely want to ensure that you choose the right one. This can be challenging because there are so many options available on the market.

Still, if you know which type of data entry software you are looking for, it can be much easier to ensure you pick the right solution for your company.

There are two main types of data capturing software options that are available for businesses. These are template-based OCR solutions and cognitive OCR solutions. Both systems use optical character recognition (OCR), and there are many different data entry software examples available online for both types of software systems.

Template-based OCR technology uses predefined rules and templates to capture data in documents. This can be very useful for businesses that only use a few document layouts. 

Unfortunately, in today’s society, these types of companies are not very common. Because of this, template-based solutions can add a lot of manual work to a system because they will need new rules for every new document layout they are processing. 

Cognitive OCR technology uses artificial intelligence to process information from documents. This system works a lot like a human does — without the need for bathroom or coffee breaks and with way fewer data entry errors. Because cognitive OCR does not rely on templates or rules, it can be much more effective in processing information without as much need for manual tasks.

Whether you are looking for a template-based or a cognitive OCR software solution, there are many options available, and you can find a great place to start by looking for a list of data entry software solutions. 

This list can help you to identify some of the top software options available today, and then you can compare the tools and features each software offers and select the one that will best benefit your business.

Making a change to your documentation process
can start today

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