Challenges become a barrier when you want data for deeply analysing and drawing strategic solutions. Fortunately, it is a digital era where various tools are available to tackle inaccuracies, typos, and inconsistencies. But still, these challenges are not going to fade away unless they are treated with expertise.
Here, the role of data entry operators is crucial. Certainly, managing quality is full of worms. Sometimes, its gigantic size interferes and many times, it’s irregularity in monitoring issues with datasets. It’s a rule of thumb to check inaccuracies day-to-day. Perhaps, the pressure of wrapping up quickly overpowers and hence, inaccurate data entries breed.
There is another concern that is related to costing. The cost of data entry work often costs high. It is perhaps one of the most expensive jobs to deal with errors. After all, machine learning algorithms need accurate data for modeling. With them, AI development would be easier because it requires clean data entries, which makes this task expensive.
10 Tips to Overcome Manual Data Entry Errors
Typically, manual data entry has its own plus and minus. But here, we would focus on risks associated with it and how to fix them. Let’s move on to discover how not to do errors.
- Hire Sufficient Staff Proportional to Work
Have you ever seen efficient employees making mistakes? This can happen when they are exhausted. Perhaps, overwork burdens them. This is where the team leaders or managers make a mistake. The stress factor overwhelms data entry operators when their count is less and the target is way higher than their capacity. What they would do in this case?
Certainly, errors would happen because they have become resentful toward their jobs. So, ensure that you have sufficient operators to carry out the workload.
- Ideal Working Environment
The place where you work is important because it should feel like being engaged. They should be comfortable in doing their jobs. Sometimes, honking vehicles, noises, and environmental factors disengage them from what they do, which often end up in typos and errors. Let’s say, if the light is dim or improper, the typing fatigue will stress their eyes. This happening can overtime cause pain in eyes, which may result in accidental mistakes in your data. Besides, the distraction can be there. The employee continues to think about pain, but not the work. This is why breaks between shifts should be there. Like work, health is also important.
- Double-Check the Quality
A thorough checking of data entry tasks is a must to ensure 99.99% accuracy rate. Manually, it’s rock hard to skip mistakes. But, you can fix it with a double-check quality system. It can help you to avoid data entry errors. Although, this is the most critical task and doing it regularly is another challenge. But, if you follow this practice, the errors would be fewer and the need for rework would zero.
- Update Automated Systems
Do you know that automated systems make mistake? Have you seen the extracted table data? It often shows space and alignment issues. This example clearly states that you should not blindly trust automated systems. Irregular or no updates often become a big reason for this mistake. Therefore, automated systems won’t produce accurate results. This can happen because of malware or viruses, which attack due to obsolete version of the data cleansing software or application.
To get rid of these problems, it’s always good to keep your system up-to-date.
- Determine the Source of Errors
The best way to treat inaccuracies is to fix them at the point of entry. During data migration from external sources, inaccuracies creep in. They should be removed instantly before they impact decisions. Also, it’s good to see into data entry locations, such as where these entries are moving from.
In short, there should be a system that can help in verifying and updating data entries. Also, discover the cause of errors, which can be data migration, conversion, or any other one. Once determined, fix and validate them. This way you won’t have to struggle a lot in fixing data entries quickly.
- Set Realistic Goals
Sometimes, people think of getting as-is data from their PDFs after conversion. However, getting digital records can be a goal. But, manual conversion won’t make it possible quickly. This is where scripting comes into play. With a set of codes, the PDF data are extracted and stored in a database. To achieve accuracy goals in reality, you need a tried and tested plan for cleansing. So, you need to set a crystal clear goal here, which is to measure data entry, verify, fix if required, and then, store securely.
- Use Best Fit Tools
By tools, we mean any application or software. For data entry, optical character recognition (OCR) and intelligent character recognition (ICR) can save hundreds of hours in conversion of an image-based data (as of a PDF). These tools are proven to handle the workload of data entry operators. These tools are capable of extracting, recognising, and converting datasets automatically. Automating these tasks reduces typos because you type less.
- Automate Error Reports
There are some software that can report you deeply about accuracy and relevancy rate of your data. These reporting software are able to get deep into the data entry efficiency. You may try the best fit one and leverage its expertise in reducing the number of common mistakes. Let’s say that every zip code has a total of 6 digits in India. The data entry operator is supposed to write the six-digital number there. You may deploy such software that can instantly pop an alert or notification, stating that you have made a mistake during data entry. You have another option here. Multiply data entry benefits for business via outsourcing. Most outsourcing companies often have such software to minimise errors.
- Define Robust Standards for Accuracy
A lot of business process outsourcing companies instinctively know about standards that are must-haves for data entry. You may outsource data entry services to discover these standards. Typically, these are associated with accuracy. The expert companies often predefine such standards, such as data profiling, geolocation coding, linking, matching, normalising, enriching, and regulating monitoring. These standards actually improve the quality of any data.
- Coordinate with the Right Outsourcing Partner
Are you still thinking that you alone can remove errors? Well, if you have resources like modern tools, software, or coding knowledge, this can easily happen. But what if you run a manufacturing unit? Certainly, these all things can never happen. If somehow you manage them all alone, the cost of data entry would be way higher than outsourcing. So, you may outsource these services to an experienced professional. Such are experts in managing the bandwidth to store it and can efficiently manage your requirements.
Moreover, they often keep a scope of increasing or decreasing bandwidth and its costing because they charge as much you use it. However, this is essential for the service provider also to keep these things in mind.
There are many challenges involved in data entry. You may overcome these risks by introducing preventive measures. These can be hiring an outsourcing partner, defining standards, properly regulating verification and validation, treating errors at the point of entry and a lot more.