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7 Ways to Streamline Data Entry Processes That Can Transform Your Business

/ ~ 9 minutes read

The main goal for a business is to make as much money as possible at the lowest possible costs. Many expenses can be significantly reduced by optimizing routine processes. Imagine an employee whose full-time job is entering various data and filling forms with their computer and keyboard. This is exactly the type of task that can be easily streamlined with data entry automation. 

However, data entry automation is not the only way to transform your business. To guarantee efficient data entry, you can use the other data-related optimization tips described in the article.

What is data entry?

Data entry is the process of entering a specific type of information into a preferred or desired system. Data entry tasks are usually performed by data entry operators, who spend endless hours performing regular, repetitive operations. 

For example, a bank manager may open an Excel spreadsheet containing all client-related information and enter data about a new client into the system. It could be personal information, credit score, investment account statement or savings account statement, documentation of any other sources of income, and so on. Imagine this bank’s branch has 20 new clients daily.

Such a menial task as manual data entry might take up to 3 hours. That’s why companies often outsource manual data entry processes or implement automated data entry software. But what if you don't want or don't have an opportunity to outsource data entry processes? 

In that case, we’ve prepared seven tips to streamline data entering processes for your business.

1. Use data verification techniques

You can use the double-entry principle to ensure your data is correct. When utilizing this approach, two employees work separately on transcribing and compare results at the end. Even though double-checking takes more time, it detects any data-related inconsistencies. 

Another interesting data verification method is used when transmitting data in numerical format; for example, bank account numbers use a control number. Imagine you have a client’s account number in your system. The control number already exists in the system and the computer knows it. Let's look at an example.

For the number 85202, the control number is 8. When the system adds up the digits, it gets a sum of 17 (8+5+2+0+2). Then the system adds up the digits of a new number: 1+7=8. The resulting number is called the control number. The system remembers this control number in case of any typos in the future. Let’s have a closer look.

What happens if your employee accidentally adds a 6 to the end of the number and enters 852026 instead of 85202? In this case, the sum is 23, and the control number is 5 (23=2+3=5). The system does a reverse calculation, and if the old number (8) does not match with the new number (5), the number will be marked as false and your operator will see a notification.

However, this approach has a major drawback: if you swap the places of the digits, the numbers are not the same but their sum doesn't change. Imagine your operator enters 20258 (reverse of 85202); the control number remains the same but the number is different. Banks and big companies use more complex approaches to solve such problems.

2. Pay attention to common data entry errors

Finding and correcting errors is an essential part of working with data. On average, there are four types of errors:

  • Misrecord. An error occurs if the data was originally written incorrectly.
  • Insertion. An error occurs when an extra character appears. For example: 53,247 → 523,247.
  • Deletion. Another error related to the number of characters. It occurs when one or more characters are lost. For example: 53,247 → 5,327.
  • Swapping places. This error may occur if the person entering the data mixes up the characters. For example: 53,247 → 52,437.

Errors are not rare in writing dates and are even more common when different standards collide, such as American (month/day/year) and European (day/month/year). Sometimes the error is obvious (March 23: 3/25), and in some cases, it can be completely invisible (April 3: 3/5 or 5/3?). 

Some industries may have their own specific mistakes. You can create a checklist of common mistakes for your business by analyzing your previous data, or the data of your competitors. For example, you can use smart forms to protect the user from making a mistake. The system automatically counts the number of characters, validates the email field, and inserts the country code into the phone number field. You can also utilize drop-down lists to minimize the risk of any typo.

3. Raise your data processing standards

The safest and easiest solution to data-related problems is to standardize as many work steps as possible and prepare for data entry. Standardization of data-related criteria such as accuracy, consistency, and interconnectivity helps to improve the speed of data entry:

  • Accuracy. All data must be accurate, and mistakes must be specified. For example, if you’re an air conditioning manufacturer, a precise temperature is good data, while even small inaccuracies can affect your business: imagine if a whole batch of AC units had the wrong settings. 
  • Interconnectivity. You should always have the ability to link some data to other data. For example, customer information, including address, contact, and payment information should be linked to the order number.
  • Consistency. If records contradict each other, it indicates that there is an error somewhere. For example, if the client's address appears in two separate databases, they must match. Otherwise, you must determine which source is reliable and disregard the others until the mistakes are fixed.

The main idea behind standardization of the data entry process is to set a specific, repeatable procedure for your employees to follow. You can use paper checklists, team meetings, or automatization software. For example, a great way to take your data standards to the next level is to use drop-down lists, error reports, and short surveys from your employees.

4. Data input profiling

Data profiling is one of the most common methods of checking manual data quality, and it also helps to identify problems related to data entry. 

Profiling is performed automatically according to some pre-configured script, which is based on an analysis of the data structure. The system checks the data for compliance with the specified constraints and decides whether the data passes the test or not. 

For example, a typical problem when entering numeric values is the incorrect use of integer part delimiters, fractional part delimiters, and bit groups. As an integer part or a fractional part, the delimiter may appear as a comma or a dot, and the delimiter of bit groups may appear as a space or absence.

You can write the same number in several different ways: 2,300,000.00, 2300,000.00, or 2 300 000,00. If delimiters are misused, the system may recognize the value as a string, which will lead to wrong conclusions. Therefore, one of the profiling tasks is to check and fix the number representation formats within the system.

5. Limit the data input

Many businesses operate with massive databases: sometimes it's essential, but other times it's possible to reduce unnecessary work and focus on quality. If you’re dealing with a large quantity of data, you should consider whether to enter all of it or prioritize some of it. 

Imagine you're a retailer. Your database may include pricing data, customer reviews, consumer search trends, search engine results, and more. If you target a new manufacturer database to improve your supply chain, perhaps you can skip customer-related data and focus more on the prices and conditions your partners offer.

Of course, you can always hire more data entry specialists if you need to enter all the information. However, there are at least two reasons to avoid extra hiring:

  • More employees will increase business costs.
  • Hiring can lower the quality of the database: it may increase the number of errors and hurt your company if your data processes are not optimized, for example, if you don't use error reports for manual data entry.

On the other hand, automating data processing reduces the number of errors and hours spent on monotonous routine. Automating data entry also allows businesses to decrease operational costs, because people can concentrate on more practical activities where they can be more productive and finish more tasks without overtime.

6. Prioritize the data

Adapting the famous Pareto principle for data entry, we get the following formulation: "Focus your efforts on the 20% of the most important information that is worth 80% of your attention.” In other words, if working with a lot of data is unavoidable, spend most of your time entering the quality information you are confident in, and only then enter the rest of the less quality information.

However, this advice is not suitable for all industries. For example, if you work in medicine, you cannot divide patient information into more or less important: you must treat all patients with the same level of care. In that case, automating data entry and checking the information manually will work for you.

7. Consider data entry automation software

Manual data entry is an expensive, time-consuming, and labor-intensive process. The quality of the data input depends heavily on the physical and mental state of the employee: your data entry specialist may be tired, demotivated, inattentive, and so on. To minimize the impact of the human factor on your business, you can use special data entry automation software. 

Data entry optimization software is based on technologies called Robotic Process Automation (RPA) and Optical Character Recognition (OCR), which allow you to swiftly transfer information from scanned documents into your corporate system. For example, you can use RPA to set up automated error reports.

Why ElectroNeek automation?

ElectroNeek is an end-to-end intelligent automation platform that lets business users with no prior IT skills discover automation opportunities and build software robots to automate repetitive tasks. This way, employees from all departments can automate data entry tasks and processes and other repetitive, rule-based operations with data, letting them focus on more revenue-driven tasks.

By using ElectroNeek to automate routine and repetitive processes involved in manual data entry, businesses can make the workflow more cost-effective and help people stay motivated and productive. You can unlock even more opportunities to empower your business with the Top 10 Automation Tools for MSPs.

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