Data entry and processing mistakes have a huge impact on organizations. Accurate data is the foundation of all decision making. They can affect a business’s integrity and financial gains while creating an air of uncertainty among staff and clients. These mistakes are all too common.
Whether it’s an error, omission, or duplication of information, even the smallest data entry slip-up can have big consequences. The trouble is that organizations have a hard time grasping how to manage the risk associated with data entry and indexing. In today’s environment, data is captured from source documents using manual data entry, Optical Character Recognition (OCR), artificial intelligence (AI), or robotic process automation. Regardless of how the information is captured, it is often up to humans to review and validate data that technology cannot, with 100%, accurately capture.
Small mistakes may affect everything from your productivity to customer satisfaction and your profit line. Read on to find out the causes of data entry errors and the steps your business can take to minimize errors.
Causes of Data Entry Errors
The importance of accurate data cannot be overstated. However, when data entry specialists are reviewing and entering data and keying characters all day, it’s easy for them to transpose numbers or input data inaccurately.
Data entry processes must be regularly evaluated and modified to reduce mistakes. The focus should be on the data itself, the people performing the work, their process, and the technology used to achieve the end result.
These are some common types of data entry errors:
- Issues with the source data
- Inaccurate data entry or transposition error
- Data conversion flaws
- Translation and transcription errors
- Data cleansing
- Human error
- Low OCR, AI confidence
10 Ways to Minimize Data Entry Errors
The causes of data entry errors can be complex and this is why a business needs to take a multifaceted approach to reduce mistakes. ILM offers a comprehensive range of services that can improve data entry and information systems for commercial businesses, non-profit organizations, and government agencies.
We also recommend adhering to the standard industry practices mentioned below in order to find solutions for every type of error:
1. Support the Staff
Data entry specialists should understand the data, as well as the specific guidelines, requirements, and best practices for improving quality. Performing repetitive tasks oftentimes results in inattention. Providing excellent training using detailed samples and handling is one critical way to reduce errors.
The working environment is also important. Staff members need comfortable workspaces and timely breaks. Proper lighting, temperature, seating and desk height all contribute to a safer and happier employee. Focusing on people and providing a productive and efficient work setting goes a long way.
2. Implement Policies and Processes
Information and data governance policies and processes are critical to reducing errors and increasing productivity. Data entry specialists may understand the data, but mistakes still happen if your business lacks the right framework and structure mistakes. Best practices training and feasible deadlines create accountability and quality work in the long term.
3. Take Advantage of Technological Developments
Technology largely impacts the quality of data entry. Depending on the format of the data, conversion software and other data processing tools lessen the likelihood of errors, omissions, and incorrect data.
Technology is what forms the foundation for scalability, which in turn improves the quality of data. Common tools for extracting data include AI (Artificial Intelligence) and OCR (Optical Character Recognition).
4. Validate Your Data
It’s essential to validate the data whenever your company receives external data from your customers or data suppliers. Data validation involves checking for accuracy and assessing integrity standards. Data integration and batch processing are two ways to validate data and detect any incomplete data as it enters your system.
5. Double-Check Manual Data Entries
It may not always be feasible to double-check every data point. However, it is best practice to have a system in place to double-check data that your staff has manually entered and data that does not meet the accuracy confidence level thresholds set by your OCR or AI engines. 6. Reduce Data Redundancy
Redundant data increases the chances of errors occurring in a system. To reduce redundancy, it is recommended you regularly revise forms and documents and remove unnecessary or obsolete fields. Regular reviews of your entire information flow will minimize the likelihood of data entry errors from both staff and customers.
7. Automate Certain Tasks
As mentioned previously, human errors are a likely cause of data entry errors. The task of data entry is often time-consuming and monotonous, which is why it is a prime candidate for automation. For example, many businesses are choosing to automate Accounts Payable by using outsourced data entry.
Your business may automate the data entry process using AI and OCR systems in addition to other data entry software tools. Human staff may then serve as quality assurance officers or perform another valuable role.
8. Use Data Profiling Tools
Data profiling programs can help find mistakes in data by detecting any values that do not match established patterns or fall inside essential parameters. The program may identify incorrect values, restrict the data, and flag it for review. The next step will be to identify the source of the errors.
9. Identify the Source of Errors
Every process and step in an information system should be double-checked, verified, or analyzed so that you can easily pinpoint the source of an error when it occurs. Checks should start when the data moves between different databases and special attention should be paid to any scheduled updates.
Thorough checks will help identify the internal or external source of any data errors because it will be relatively simple to trace the error back through the information flow.
10. Update Systems Often
This last point may seem obvious, but it is worth reminding all staff to keep software and programs updated. That way, a business can take advantage of the latest developments and security protocols available. This will reduce the chance of bugs forming in the system that may lead to data entry errors.
The Cost of Data Entry Errors
The following is a case study of how ILM Corp transformed a client’s record-keeping system and solved a major customer service issue. The issue was causing a significant loss of revenue as customers turned to competitors that could deliver goods faster.
The Problem
Our client, ABB, manufactures and installs industrial power plants such as boilers and steam generators.
- The client was experiencing a long turnaround time to research the correct replacement parts for its customers, which meant a loss of revenue and clients.
- The list of replacement parts was kept on a paper bill of material (BOM).
- Some BOMs were 60 years old, and they were recorded in over 100 formats.
- When a client called for a replacement part, a service representative had to sort through warehouse files looking for the correct BOM.
- This took 7 to 10 days and caused clients to buy replacement parts from competitors.
The Solution
ILM designed a system to categorize the BOMs by their different formats.
- Many different types of documents were scanned, including documents that were handwritten and on various types of paper stock and color.
- The images were enhanced for greater viewing ability.
- The handwritten line item data was converted into a searchable index.
Results
The client could quickly provide customers with the replacement parts they needed.
- The benefits of automated vs. manual indexing increased revenue by millions of dollars.
- Turnaround time was reduced from seven days to 20 minutes.
- Client satisfaction significantly increased.
ILM Can Help Your Business Reduce Data Entry Errors
ILM can transform all your records and information systems into accurate digital data.
To find out about ILM’s unique process for reducing data entry mistakes and improving data quality, contact us today.
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