This article will discuss 7 of the most common mistakes that are made by data entry service providers and show you how to avoid them.

Seven Mistakes to Avoid While Doing Data Entry for a Business

Even though we live in the age of automation, there are still records that must be entered manually. There will always be a demand for having data entry outsourced, so if you want to maximize your value, then the best way is to provide error-free work for businesses. Follow the best practices in data entry, and companies are likely to keep coming back to use your services.

However, the problems come when data is entered incorrectly. Businesses struggle with bad data every day, and most of the time it comes from errors in data entry. These mistakes are too costly to ignore. Businesses will not tolerate them because errors impact their profits. So, it’s important to implement the best practices in data entry so that you can guarantee error-free work.

With that said, let’s look at 7 of the most common mistakes that are made by data entry service providers and show you how to avoid them.

#1

Ambiguous Errors

This one is quite common because businesses will have a very specific format that they use in their records. For example, if Mary’s birthday is on March 10, 1970, then they might have the date listed as 03/10/1970. However, another business might use an entirely different format. For instance, 10/03/1970 is the same date in European format. As you can see, this is easy to mess up and so the only way to avoid it is to verify the format in advance. Don’t risk entering the records incorrectly. Remember that values are not correct if the user cannot properly identify it.

#2

Errors Due to Value Representation Consistency

This one is a bit tricky because values can technically be correct, but undefined. It creates problems when the records are being viewed. Word Press and WordPress are both technically the same, but the second iteration is the correct form. If you were to enter the first, then it would be inaccurate and could cause problems when users try to query the data.

#3

Lack of Organization

One of the biggest problems that those new to data entry face is that they don’t possess the right organizational skills to perform the task efficiently. In a lot of cases, the entire data entry process being used is disorganized. The first step would be to start using digital folders to separate the documents into specific categories rather than dumping them all into one folder. Learning proper organizational skills is one of the best practices in data entry. The fact is that if your work environment is disorganized, then errors are going to be made.

#4

Choosing Speed over Accuracy

Speed is not necessarily a bad thing since it makes the workflow more efficient, but the mistake comes when accuracy is sacrificed. Rushing tasks is going to lead to mistakes, and when it comes to data entry, these mistakes will have a big impact on businesses. Set reasonable deadlines for every project, and if you feel rushed to meet that deadline, then don’t panic. Learn and adapt so that you can set better goals in the future. Your primary focus should be on accuracy first.

#5

Lack of Skills

Sometimes a lack of proper training leads to mistakes. For example, one of the biggest mistakes that we see when getting data entry outsourced is in the formatting. Companies want their data to be formatted in a specific way, so it’s important to learn proper data entry formats. If not, then you could potentially waste countless hours in revisions. This costs everyone time and money, so be sure that you learn everything you need.

#6

Change-Induced Inconsistencies can Cause Problems

Let me start this off by giving you an example of what we’re talking about here. Assume that a car company had previously only used four colors for their cars. Their records would have a field that is designed to accept records in those four colors specifically. But several years later, they updated their manufacturing options to include ten colors. However, since older records are not updated, the entire system would become inconsistent. In short, the older records would eventually cross with newer ones, creating inconsistent data representation. This gets even more complicated with larger businesses that implement changes on different timelines.

#7

Lack of Focus

Focusing on large strings of data will eventually cause people to zone out, so it’s important that data entry specialists develop ways to keep themselves fully engaged. The problem with being on autopilot is that there is a high chance of errors. You might read information incorrectly, which will lead to errors. As we all know, errors lead to much larger problems including revisions and a loss of trust.

7 Mistakes to Avoid While Doing Data Entry for a Business

Improve the Accuracy of Data Entry

Manual data entry is a high demand service, so it’s essential that it be accurate. All the company’s business intelligence practices hinge on it. So, make sure you are doing everything in your power to stay free of errors. While it’s almost impossible to eliminate errors completely (we are human after all), there are several steps that you can take to significantly limit mistakes. Here are a few tips:

Use Automated Data Entry When Possible

It saves time and keeps you from feeling rushed. That doesn’t mean that automated work should not be double-checked for accuracy, but it’s much more time-efficient to check transcripts than it is to manually put in every line. With that said, it’s impossible to automate all data entry.

Focus on Accuracy

There’s no argument here. Accuracy is one of the best practices in data entry. Again, this boils down to setting realistic deadline so that you’re not rushed. It also means that you need to make patience your primary virtue.

Streamline Data Entry Processes Where Possible

Always use the same process to enter data. That way, you can focus on accuracy and don’t have to worry about format. Humans thrive on repetition.

Having data entry outsourced is one of the most common practices for businesses because it helps them reduce their overhead costs. But they still need providers that can deliver accurate data, otherwise it can have a negative impact on their bottom line. Avoid the common pitfalls when doing data entry for an organization to build trust and long-lasting relationships.

(Visited 12 times, 1 visits today)