Manual data entry is often a necessary part of the business process—a reliable yet tedious task that keeps things moving forward. 

Many companies still stick to these processes because:

• They want to manually verify the data
• They want to make sure they capture context accurately 
• They want to store the data in a specific format in specific tools

That said, it’s also a matter of comfort. Maybe you feel like automated processes are risky or tedious to implement. The opportunity cost though? It’s far worse.

In this article, we’ll explore how manual data entry is actually impacting your business and what you can do about it.

How is manual data entry negatively impacting your business?

With manual data entry, you’re always adding information into a system by hand—either through typing or scanning. The goal is to digitize your documents and store them in a database or spreadsheet.

But it’s also costing your business time, money, and resources in the long run. Here are a few ways it’s doing that and how you can solve it:

1. Increased document processing time

In our experience, we’ve seen manufacturing and logistics companies hire entire teams of data entry clerks and field sales partners to manually enter data from handwritten documents and even digital copies they receive via email. And we understand why they do it.

When you’re dealing with sensitive documents like invoices and bills of lading (BOLs), you can’t afford to make mistakes.

But, this manual process leads to an increased turnaround time. A recent Trullion survey found that 59% of auditors manually extract data from unstructured documents—costing them more than 5 hours per week. As a result, they spend anywhere between 5 to 20 hours just on reconciliations because of manually extracting data for audit documentation.

Instead, if they used an automated document processing software, every auditor would save up to 20 hours a month. This adds up across the entire team, allowing them to focus on compliance and regulatory monitoring, risk assessment, and anti-fraud measures. 

Companies like FinlyWealth have already seen a 90% reduction in time spent on manual data entry, thanks to document processing tools.

2. Increased labor costs

When you're relying on manual data entry, you need to expand your team to keep up with the growing data volumes and extract data on time. This can increase labor costs such as:

• Salaries
• Benefits
• Overtime pay
• Training
• Recruitment

For instance, imagine you’re processing 1000 purchase orders per week. Each order requires 15 to 20 minutes of manual data entry (adding payment amount, bank account number, and more manually) by your team member. 

• Time per order: 15 minutes 
• Total time for 1000 order per week: 15 minutes × 1000 = 15,000 minutes (approximately 250 hours)

If your team member is working at an average rate of $20 per hour, it would cost nearly $5000 per week. 

But with document processing or automation tools, that’s not the case. You can scale up and down because you have a set workflow in place. It’s just a matter of the number of task runs—not the number of employees.

In fact, Ashok Leyland, one of India's leading commercial vehicle manufacturers, uses AI and automation to process nearly thousands of invoices on a daily basis. They’ve already achieved a four-fold reduction in invoice processing costs.

3. Higher error rates

When your teams enter data manually, there’s a high likelihood of making costly errors. Here are a few examples:

• Data duplication across files
• Inconsistencies in formats
• Incorrect values due to misinterpreted data
• Swapping or misplacing financial numbers 
• Leaving blank spaces
• Reversing characters

Afterall, to err is human. But the effects of these human errors can trickle across your entire organization. In fact, simple data entry and transposition errors led to a US state overreporting retirement contributions by $718 billion in 2023.

This is why you should consider automating a portion of the process. If you use an intelligent document processing solution that’s trained on your document formats, the platform extracts the data and verifies them automatically. And if you prefer doing it yourself, there’s always the option of using Human-in-the-Loop (HITL) automation.

4. Higher likelihood of redundancies

Your team might make typographical errors or format documents inconsistently, leading to the same data getting repeated across multiple documents. This creates unnecessary repetition—and an under/overestimation in your final audit.

For example, imagine you're manually entering invoice data into your system. You receive an invoice from a supplier for $500, with invoice number #12345. 

While entering it, you might accidentally type the invoice number as #12345 the first time, and then type it again as #12355 the next time. Both entries look similar at first glance but when you take a close look, you’ll see that you have two records for the same invoice. You might overpay your vendor and have difficulty reconciling your accounts later on.

With document automation, you can avoid these issues. Just set up rules to validate the data and automate that process if needed.

5. Increased training burden

With manual data entry, you’ll need to get employees up to speed on:

• Document processes
• Type of documents
• Document formatting guidelines
• Software training (for ERPs and similar tools)

You’ll have to plan for the extra time spent on training—and time lost on non-value-added activities.

Let’s say you’re processing more BOLs. Your team has to spend days teaching new hires how to:

• Enter shipment details accurately
• Match shipping information to the right records
• Avoid common errors like entering the wrong address

When you switch to document automation tools, you can reduce this burden significantly. You’ll still need to train employees on how to use the tool but the best systems? They’re intuitive and use no-code workflows that even non-technical users can use. Any time there’s a regulatory change, you just have to reconfigure your workflow to account for the changes and that’s the end of it. The platform will handle the rest.

6. Lack of process standardization

When there's no standard process for manual data entry, things can get messy. Everyone’s doing things differently, eventually just slowing the entire organization down. 

Sure, training employees can solve the problem. But even with training, it's tough to get everyone on the same page. Standardizing everything takes time and resources—and when you’re scaling, that’s something companies are always short of.

Let’s say you’re processing more BOLs. One person records tariff codes numerically while another uses alphanumeric codes. These discrepancies can lead to incorrect filings. This results in delayed customs clearances, potential fines, and longer shipping times.

An artificial intelligence (AI) based document processing helps with standardization without the excessive need for resources. This means you can reduce manual errors and process data consistently.

7. Inability to allocate resources effectively

Manual data entry can take up a lot of your employees time and energy, pulling them away from more important tasks. A Truillion survey found that many auditors spend over 5 hours a week extracting data from unstructured PDFs, with 59% facing this challenge.

If your finance team is busy entering and verifying data, they won’t have enough time to:

• Report finances accurately
• Budget for future quarters
• Forecast future spend
• Optimize finance spend

When you automate data entry processes, the tool does the heavy lifting for you—completing data extraction, validation, and export without human intervention. So, you can free up your team's time and focus on tasks that require more strategic thinking such as budgeting and forecasting. 

8. Inability to scale your business

As your company expands, you can’t rely only on human input for every document workflow. Let’s say you receive at least 50 bills of lading (BOLs) a day and as you expand, that volume increases to 225 BOLs per day. It’s not realistic to just start hiring more people or ask existing employees to work overtime.

Plus, even with more employees, you run the risk of higher data entry errors and burnout. Add the cost of training, resource allocation, and process standardization and now you can’t keep up with the increase in business.

That’s why you need to consider adding an automation layer to tackle scalability in the long run.

The result? You won't be overwhelmed as volume increases and can scale your business effectively without hitting bottlenecks. 

9. Increased employee burnout and dissatisfaction 

Another problem with manual data entry is that it can become repetitive. Soon, your employees disengage and start feeling undervalued. It’s easy to lose motivation and as a result, performance and productivity.

In fact, DataRail’s survey shows 81% of CFOs believe their role requires the most intensive manual work compared to any other in the C-suite. They feel this reduces their time with family and friends and fuels boredom and stress at work. Now, think about how this trickles down through the organizational chain.

Consider automating routine document processes and letting the tool take care of all those repetitive tasks. Your employees don’t need to dot every I and cross every T. They need to come in when the data is ready for them to review and use.

Move away from manual processes that are a drag on your organization with automated document processing

There’s a certain sense of comfort in using manual data entry processes. You’ve hired a reliable team and they’ve been doing the job well for years. However, there’s an opportunity cost to continuing down this line.

Your teams will continue to waste time and effort on mundane tasks that could be automated. As a result, you’ll see decreased productivity, a constant strain on your profits, and an inability to scale efficiently when the time comes.

If you want to improve your data entry processes and access actionable data faster, it’s time to move on to automated document processing solutions.