Data entry specialists need to process an enormous amount of information daily. Thus, they remain under constant pressure, resulting in an increased possibility of errors.
Firms plan their goals, create strategies, and make vital decisions based on the big data generated throughout the organization. Surprisingly, even automated data entry consists of inaccuracies. Such errors prove to be extremely expensive for small and large businesses. Companies find it challenging to reduce inaccuracies in spite of automation. Let’s take a look at some of the most common data entry mistakes and ways to reduce the same.
There are several types of errors, but, being familiar with the following four can help you audit and fix them as soon as you notice them.
Such inaccuracies are found in datasets that consist of words rather than numerical data. It includes human errors like deletion, repetition, or typographical mistakes caused during data entry.
Agents often press the wrong key, alter a word incorrectly, or the auto-correct feature on the system ends up changing the word.
These types of mistakes are mostly seen in data that consists of numbers. The agent handling information ends up changing the characters unintentionally. For example, the person enters 154 instead of the intended 145 in the system and fails to notice the same.
If the organization lacks human resources for auditing, it is advisable to outsource such tasks to companies that handle accounting outsourcing in India.
The issue is one of the commonly reported ones where automated data entry systems or software are in place. The data gets entered into the wrong columns/fields or gets processed inappropriately even in spite of entering the same in the correct field.
Misinterpretation of information
Such errors occur when words are unintentionally mixed with numbers in the wrong sequence. These can even happen in an individual’s day-to-day life while inputting passwords or codes. The best example of misinterpretation is agent entering o (letter) instead of number 0 while handling data.
Here’re tips that can assist in reducing inaccuracies in the data
Identifying the source
Besides inputting incorrect values, and data migration, there are several other reasons that can result in erroneous data. In some cases, the information in the database becomes inaccurate due to time-bound, external issues like change in the consumer’s address, marital status, phone number, etc. Thus, it is crucial to identify if the inaccuracies are due to external or internal reasons.
Detecting the source for errors can help in fixing it using the best possible method and ensure the database consists of good quality, reliable information. The procedure is time-consuming and may need an additional human resource with ample experience in handling data entry software.
Setting data entry accuracy standards
Implementing a set of predefined data handling standards can help in improving data processing quality to a great extent. Including post-processing reports, program edits, field validation, double-key data entry verification, linking and data profiling, data monitoring, geocoding, etc. can help in improving the overall quality of the data.
Besides the above features, firms can also set practices like randomly double-checking files, reviewing the entered data daily. Several companies have a dedicated team of data entry experts to identify and rectify errors that may make it in the database in spite of several data accuracy measures in place.
Leveraging error identification features from the software solutions
Several software solutions have built-in automated error reporting features that can be enabled to help the data entry staff in identifying potential problems. Error identification features help in considerably reducing mistakes. For example, administrators can design software to ensure the social security number entered by the agent has nine digits. If the associate enters a number that has less than nine digits, the software would show a pop-up suggesting the agent check and re-enter the number due to a missing digit. The same can be done with zip-code, telephone numbers, insurance policy numbers, vehicle numbers, etc.
Comfortable working environment
Data processing jobs require a lot of speed and focus. Both can be achieved if the work environment has minimum distraction and comfortable working conditions. Such an environment can ensure the associate working on the information can input the same in the database with maximum accuracy.
Amiable work culture and ergonomic office furniture can help in creating a healthy environment resulting in high employee morale and improved productivity.
Time constraints and overburden of work
Remember, accuracy should be the priority and not the quantity or completion of daily targets. Companies set high, almost unachievable data processing targets for associates. Employees working with such unrealistic targets often work at a higher pace to complete the assigned work within a specified time. Putting such a burden increases the work stress that staff faces daily. More work and lesser time often result in a large number of errors in work. It is advisable to ensure the data processing, and analytics team has sufficient manpower.
Software solutions like Optical Character Recognition (OCR), Intelligent Character Recognition (ICR) can prove to be a helping hand for the associates handling data.
Even if you are outsourcing the work, it is advisable to ensure the firm has sufficient manpower allotted for the process. There are several outsourcing firms that make tall claims about accuracy. But, use the same old trick of getting a large amount of work done from a small team to maximize profits. It is advisable to not to outsource your work to such firms just because they quote lesser rates as the processed data would be full of errors anyway.
If the data to be handled is concerning bookkeeping, financial reporting, accounts receivable, you should consider working with a firm that specializes in outsourced accounting services.