Data holds immense importance in today’s digital era. It plays a crucial role in decision-making, progress tracking, and enhancing efficiency across all business functions. Nonetheless, one aspect that should always be a top priority is data accuracy. Inaccurate data entry can create a domino effect, causing expensive errors, missed prospects, and legal liabilities. Therefore, accuracy is crucial in manual data entry, whether it involves customer data, financial information, or medical records. You can learn how to improve data entry accuracy by referring to our article.
The role of accurate data entry in business
Business data quality can be evaluated based on several factors, such as accuracy, relevance, readability, accessibility, completeness, and timeliness. While all these factors are essential, the accuracy aspect is often considered the most crucial one to achieve.
Manual business data entry is inputting data into a computer system or database by hand, using a keyboard. Data entry work is often used for data processing from paper copies (orders and receipts) and document information from various sources such as surveys, forms, and invoices. This is a crucial aspect of business operations as it helps you maintain records and ensure the smooth functioning of various business processes.
Entering business data manually can be a tedious and time-consuming task prone to errors, given that humans are more susceptible to mistakes than computers. As a result, the accuracy of the entered data can be low and lead to a wide range of negative consequences for businesses.
Consequences of inaccurate data entry
Even a tiny error in data profiling can have significant repercussions, such as missed deliveries, lost sales, and incorrect billing, damaging the business’s reputation and customer trust. Here are the top three negative outcomes of inaccurate data entry:
- Errors in decision-making. A business might make incorrect decisions based on inaccurate sales data due to errors in data entry, leading to poor sales forecasting, missed opportunities, and potential financial losses.
- Wasted time and money. If customer data is entered incorrectly, this can result in delays in shipping products, customer complaints, and additional costs associated with resending the correct product.
- Reputational damage. If an airline’s reservation system has inaccurate passenger data due to data entry errors, it can lead to delayed flights, angry customers, and damage to its reputation.
One of the most costly mistakes due to a typographical error occurred in the business world in 2006. Alitalia Airlines lost $7.2 million because of a typo that resulted in missing zeros. The Italian national carrier announced a promotional offer of $3,900 for business-class flights from Toronto to Cyprus. However, due to an error in data entry, the price was mistakenly listed as $39.
Manual data entry errors can have significant consequences for businesses, even if unintentional and seemingly minor.
Why it is important to improve the accuracy of data entry
The accuracy of data entry is imperative:
- It helps maintain data integrity, making it reliable for decisions, progress tracking, and process improvement.
- It can save time and resources, reducing the need for error correction and re-entry and allowing teams to focus on other essential tasks.
- It helps you build a reputation for reliability, which is critical in attracting and retaining customers and partners.
- It is crucial in training artificial intelligence (AI) models and effectively leveraging machine learning techniques.
Therefore, it is essential to prioritize accuracy in data entry to ensure reliable data that can support effective problem-solving.
What your business needs to improve data entry accuracy
Let’s check out what business tools and methods you require to implement an efficient data entry process with a high level of data accuracy:
- Data entry and data validation software for error checking. This can help you identify discrepancies and other inconsistencies in the data, making it easier to catch errors before they become a problem. The software can highlight duplicate entries or entries that do not match pre-set formatting requirements.
- Data verification and review processes. This can be particularly useful for critical data such as financial information or customer data.
- Regular data cleaning. Regularly cleaning the data helps eliminate duplicates, inconsistencies, and other errors. This can be done using software tools or manual checks.
- Implementing standardization protocols. This can help reduce the potential for human error.
How to ensure accuracy in your data entry
The best way to ensure accurate data entry is to implement practices such as data cleansing, using standard data entry formats, and maintaining consistent data entry protocols.
- Data cleansing involves reviewing and updating data to remove duplicate, incomplete, or inaccurate information.
- Standard data entry formats help you eliminate errors caused by inconsistent data entry, such as misspelled words or incorrect formatting.
- Consistent data entry protocols help you ensure that all employees follow the same data entry procedures.
According to Anaconda’s State of Data Science Report 2022, data professionals spend about 16% of their time on data cleansing. This fact highlights the importance of having clean and accurate information in data-driven decision-making.
For manual business data entry, this means that it is crucial to improve data entry accuracy, to minimize the amount of time and effort required for data cleansing later on.
Best practices to constitute accurate data entry
Companies can use several universal and practical tips to improve data entry accuracy. Consider the following suggestions:
Use data entry software
Detecting and eliminating duplicate entries in a large company’s database can be daunting without advanced techniques. To address this issue, an organization can leverage intelligent technologies to identify and remove duplicates. Data entry tools can help you automate the workflow, alleviate the increasing staff workload, and maintain data accuracy. So, instead of manually inputting data in your spreadsheet, which is usually associated with errors, you can automate data entry in Google Sheets and avoid mistakes. Although routine tasks will be automated, it is still the responsibility of data entry agents to verify the correctness and precision of all data.
Evaluate the possibilities of ETL and data entry services with their extra features. For example, using Coupler.io, you can merge compatible data into one destination file effortlessly. If you oversee multiple entities and need to extract a specific report from the accounting software you use for each one, Coupler.io can automatically stitch all that data for you.
Additionally, Coupler.io makes it effortless to locate the latest version of a file when data is being updated from various sources at different intervals. This is particularly useful when accessing information during ongoing updates. A cloud-based digital database provides real-time updates and schedule options, streamlining the process. This eliminates the need for manual copy-and-paste tasks across multiple accounts and allows you to view the data seamlessly.
Use a data entry template
A template can help you to format your data consistently. Companies should regularly verify their results using sight verification, double-key data capture verification, field validation, program adjustments, and post-processing reports. Operators responsible for collecting data should clearly understand what constitutes an error, and when the error should be flagged, including application interpretation, field, and keystroke errors.
Establishing clear procedures within your organization for who can change data is essential as well. This step can significantly limit the chances of information being edited incorrectly and ultimately protect your company’s valuable intellectual property. You should outline specific guidelines and protocols for a real-time data processing, clearly defining who is authorized to make changes and ensuring that they are appropriately trained and informed of the risks involved. By implementing these measures, you can enhance the security of your company’s data management system.
Double-check the work
A straightforward approach businesses can adopt is to enhance the frequency and quality of their quality checks. This approach is grounded in the notion that the quality of data will deteriorate unless quality checks are carried out in the future.
Businesses can reap substantial benefits by increasing the frequency and quantity of checks. Clients appreciate the assurance that their new business systems will not be tainted by incorrect values, even if the outcome consists of no records. It’s better to measure twice and cut once.
Additionally, regular data audits can be beneficial to your data management strategy. It enables you to identify and rectify erroneous information while also highlighting areas in need of improvement in your data entry procedures. This approach to auditing data can aid in preventing security and compliance problems.
Common data entry accuracy errors
Let’s examine the common causes of data inaccuracy. In this section, by classifying data entry errors, we will summarize targeted recommendations to prevent them.
Transcription errors
Transcription errors refer to mistakes made while transferring or transcribing data from one source to another, such as copying information from a physical document to a digital format. Typical examples of transcription errors include typographical mistakes, repetition, deletion, the substitution of characters, etc. Such errors can arise from carelessness, fatigue, failure to cross-check the entered data, or an inadequate keyboard or input device.
Transcription errors can lead to serious consequences; therefore, it is essential to prevent them by using reliable data entry tools, performing regular quality checks, and providing sufficient training and supervision for data managers. They should also be encouraged to take frequent breaks to prevent fatigue and improve their accuracy in data entry tasks.
Transposition error
Transposition errors occur when the positions of letters or numbers are accidentally swapped, leading to incorrect sequences. Such mistakes can happen unintentionally and without the knowledge of the data entry operator. However, it is always important to double-check all inputted data before proceeding to another task to guarantee data entry accuracy.
Transposition errors can be particularly problematic when dealing with important financial information. These sources of data inaccuracy can significantly impact business processes, especially if it goes unnoticed. This can lead to misinterpreted results and wrong business decisions.
Using software with built-in data validation checks can partly help to identify such errors and minimize their impact.
Wrong data formatting
Incorrect data formatting is a common human error that can occur with automated processes. Despite the advanced capabilities of data entry automation software, it is still vulnerable to mistakes in data formatting, which can result in confusing reports and misaligned values.
One typical example of incorrect data formatting is when an entry specialist batch imports a data file, and the incorrect details are entered into the wrong column. These errors are more likely to occur than most people think. In addition, inputting unnecessary information is possible, which the automation tools may be unable to sort out. This can lead to confusion and unnecessary clutter in the data collection, making it harder to analyze and draw conclusions.
To prevent inaccurate data formatting, it is essential to establish effective quality control procedures, provide proper training for inputters, and use reliable data entry software with advanced error-checking capabilities. Regular quality checks and audits can also help detect and correct errors before they have serious consequences.
Representation/unit inconsistencies
These errors refer to inconsistencies in time, date, addresses, measurement formats, or units. For example, a person may enter a date in one format in one entry and a different format in another entry. Similarly, they may enter a measurement in metric units in one entry and imperial units in another entry. Representation or unit inconsistencies can result in inaccurate data.
Establishing clear guidelines and protocols for accurate data entry is essential to prevent representation or unit inconsistencies. These guidelines should include standardized formats for dates, times, addresses, and measurement units. By taking these steps, businesses can reduce risk, improve the work environment and ensure that their data is reliable.
Data misinterpretation
One of the most common errors is unrecognizable data entry patterns or data misinterpretation, which happens when numbers are unintentionally mixed in with words or characters that are misread or misunderstood. For instance, when recording passwords or codes, a simple letter “O” may be perceived as the number “0,” leading to incorrect data entry. Similarly, a misplaced decimal point can have significant implications in financial calculations.
Businesses use automated tools to verify data entries and implement double-entry systems. Additionally, companies can use validation checks to ensure that the data is entered in the correct format and is within a reasonable range. For instance, in financial calculations, businesses can implement validation checks to ensure that the numbers are within an affordable range and that the decimal point is correct.
Is it important to train employees on how to enter data accurately and efficiently?
While implementing the above-mentioned best practices and tools can help improve data entry accuracy, training employees to enter data accurately is equally essential. Proper training can help the data entry team understand the importance of data accuracy and develop the skills necessary to enter data accurately and efficiently.
Some other benefits are improved efficiency, understanding the importance of data accuracy, enhanced data quality, improved customer satisfaction, and reduced costs associated with correcting errors, such as reprinting documents or conducting follow-up research. By providing training, companies can ensure their employees have the skills and knowledge to enter data accurately, efficiently, and confidently.
By proactively preventing data entry errors, data management processes can operate seamlessly. Therefore, organizations should implement the tips discussed earlier to enhance their data processes.
Remember, accurate data is the foundation for informed decision-making and can ultimately make all the difference in the success of your business. So keep striving for excellence and never underestimate the power of a well-executed data entry strategy.
