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Read Time: 11 minutes
Manual data entry is a significant day-to-day operation for companies across industries like education, medical, legal, architecture, real estate, restaurant, fashion, and many more.
Manual Data Entry is now used in many companies as an automated data entry process.
Let’s dive right in why you need to put an end to Manual Data Entry.
So, What Is Manual data entry?
Manual Data Entry is a centuries-old practice usually done by a data entry operator of documenting data for safekeeping and duplication.
Performing the task is so simple, requiring little effort to implement. However, this task’s repetitive nature is one reason why such positions have high turnover rates. This data entry method is still applied to this date, although many organizations found a way to avoid compromising their productivity in the process. Companies coordinate with outsourcing organizations to deploy data entry specialists that are up for the task.
Data entry outsourcing allows companies to complete tedious tasks without sacrificing the productivity of their workforce.
The average typing speed of a data entry specialist is around 50 to 80 words per minute. This typing speed means that the outsourced data entry companies can type a large volume of data in a short period.
Why Do Companies Still Use Manual Data Entry?
Some companies prefer to use manual data entry services for handwritten documents, old scripts, medical entries, and many more, because professionals do the data entry task, one can expect high-quality outputs.
Let’s see top 3 advantages of using manual data entry
- Perfect for Small business owners who do not always have huge funds.
- Information is protected from the risk of cyber attacks.
- Manual data entry does not require costly software or systems.
Are you looking to automate your Data Entry?
iTech data entry automation team apply OCR, RPA, or Machine Learning to any data entry project and meet any unique need.!
3 Manual Data Entry Problems and Challenges
While Manual Data Entry may appear to be a smart option when it comes to saving money and improving cost-efficiency, it does, however, have several flaws. Before eliminating all the other alternatives, weighing the advantages and disadvantages of the Manual Data Entry process is still critical.
One of the most expensive typos ever was back in 2006 when Alitalia Airlines lost $7.2million because of missing zeros.
Italy’s national carrier announced a promotional offer of $3,900 for business-class flights from Toronto to Cyprus. A significant price reduction considering standard fares in those days. But a manual data entry error made it $39 while entering it into the company’s ticketing system.
Over 2000 customers grabbed the offer before Alitalia noticed the mistake, and the airline had to honor the purchased tickets to protect its reputation.
Such an expensive one-off mistake might grab headlines, but smaller errors can also add up over time.
AT&T found that manual data entry errors in purchase orders and invoices added up to many millions of dollars over time.
Manual Data entry is never fool-proof, but reducing human error is going to save your bottom line. While that sounds like a no-brainer, recognizing the challenges also raises questions surrounding what available solutions exist.
Here’s a quick breakdown of manual data entry problems and how to fix them
So without further ado, let’s see the problems with manual data entry
1. High Data Entry Error Rate
Is the average data entry error rate for your company higher than 1%?
If the answer is “yes’, then your manual data entry team and software processes require a closer audit.
A high error rate could be due to
• Inadequately trained manual data entry staff
• Manual data entry workload and seasonal spikes causing stress
• Scribbled handwritten forms that are not clear
• Documents with unlabelled fields
• Typos or ambiguous data (12/7/2020 in America is ‘December’ and in Europe is ‘August’)
Humans will make mistakes. Inaccurate data collection will snowball into larger issues that will slow down data entry processes and increase operating expenses.
Many organizations prefer to outsource data entry to experienced companies that are well versed in all aspects of data capture. This saves on operational costs, software upgrades, provides a steady source of trained resources, skilled workforce, and allows organizations to focus on their core business.
2. The Cost Of Quality
The 1-10-100 rule is what is called the cost of quality.
It essentially says it is better to invest $1 in prevention, which is cheaper than paying $10 in correction or ending up losing $100 in failure.
The cost of prevention is to get it right at the first stage itself. Whether small, mid-size, or huge conglomerates, all businesses rely on their data – customer data, sales data, invoicing, etc. Healthy data requires the right processes designs to ensure all data adheres to a standard. Verification must happen at the point of data entry. It might take $1 for the company to verify a small record in the overall scheme of things.
Once the data gets into the system, the decay begins.
For example, personal data verified in January 2016 might no longer be accurate in 2020. Names, addresses, phone numbers, and jobs change over the years. Sales data formats often change, invalidating older data. The cost of correction for data quality cleaning will take ten times the effort and ten times more resources, but it is an essential part of data maintenance.
However, if data is not cleansed, the cost of failure for a business is 100 times the initial cost. Data errors can cause a ripple effect through a company affecting decision-makers, data scientists, managers, line workers, and others. Over time, it can increase dissatisfied customers as well as acquisition rates.
Action plans to improve data quality must include continual improvements and maintenance. It cannot be a one-time thing – done and then forgotten. Ignorance of your business’ data quality is too high a price to pay.
3. Slow Turnaround Time
Manual data entry is time consuming.
The expected manual keystrokes for text documents data entry ranges from 10,000 to 15,000 strokes per hour. The keystrokes may be even higher for capturing text from images. With this as the benchmark, anything less than this range indicates that your company’s manual data entry process needs to be better optimized.
Humans are not machines. They cannot work at the same speed consistently for long periods. Fluctuations in productivity are part of the human factor, and so is the boredom that repetitive work can induce. And of course, they will be periods when no manual data entry work will be done – such as breaks and after business hours.
Disadvantages Of Outsourcing Manual Data Entry
While outsourcing for this role seems like the best decision, there are still several disadvantages of outsourcing data entry, that organizations must consider beforehand:
- Data Vulnerability
- Divided Attention
- Work with inconsistent quality
- Cultural differences
- Data Security
1. Data Vulnerability:
There is always a risk involved when you let confidential data be accessed by a third-party.
When you outsource even the simplistic data entry tasks within the company, this still means that these employees can gain access to your business processes such as HR, recruitment, accounts and finance, payroll processing, and claims processing. Businesses must coordinate with data entry outsourcings companies that adhere to strict security policies and measures that prevent leakage of sensitive information.
2. Divided Attention:
Like any other third-party provider, outsourced data entry specialists deal with multiple clients with different needs. Although they possess great expertise in the field, there can be a conflict if you are looking for someone with complete focus on your tasks. Looking for outsourced vendors that set quality standards can be the solution for this predicament. It is integral that companies know the other party’s priorities before making any transactions with them.
3. Work With Inconsistent Quality:
One of the most common dilemmas that most organizations encounter with outsourcing is inconsistent output.
As previously mentioned, these data entry specialists often handle multiple clients, which can be the reason for reduced quality work, delays in deliverables, authorizing inappropriate responsibilities, and more. For this reason, companies must hire outsourced employees that stick to the imposed schedule. Give them a specific timeframe and the quality metric to understand what they need to do to accomplish quality output.
4. Cultural Differences:
More often than not, your outsourced employees are on the other side of the world. You may have different cultures, which can indicate that there can be difficulty meeting halfway. When either party refuses to study one another’s culture and location, this leads to poor communication and plummeting productivity. Therefore, businesses need to explore data entry outsourcing companies that have a reputation in the industry working for people in the same culture as yours. It can also help if companies arrange a trial period to see if the outsourced data entry employee is a good fit for them in the long run.
In comparison to automated data entry, here are different ways how outsourcing data entry specialist might not be a good idea:
● Since outsourced employees rely on manual intervention, human error is always a possibility.
● Outsourced employees handle multiple clients at a given time, which means that the turnaround times for specific tasks are subject to change.
● Outsourcing a data entry specialist is more expensive than implementing an automated program that captures data.
Overall, manual data entry is efficient for handling a few documents and can afford designated employees for it. Otherwise, data capture might be the better choice.
Read below on why you need to automate data entry.
Are you looking to automate your Data Entry?
iTech data entry automation team apply OCR, RPA, or Machine Learning to any data entry project and meet any unique need.!
So, What is Automated Data Entry?
Machine learning data capture leverages machine learning to automate data entry processes.
Machine learning (ML) is the extension of artificial intelligence (AI) that takes advantage of algorithms and statistical models to execute actions. This technology allows programs to predict accurate outcomes without having a programmer code its strings of action.
Simply put, machine learning systems utilize data to learn and improve its performance from experience. When it comes to automated data entry, machine learning receives hard-to-spot patterns or graphical details and uses statistical analysis to predict output data. As one of the fastest-growing technologies today, this outweighs the benefits of traditional data entry services. It is far superior to outsourcing data entry due to the following ways:
● With data almost 100% automated, it creates faster and reliable turnaround times.
Machine learning data capture follows particular rules which guarantee delivery of output on time. The systems adjust the algorithm to perform better and automate data with 100% accuracy.
● Easily scalable no matter what the job is.
The industry is only getting more competitive each passing day. Businesses must stay on par with competitors by following the best practices that produce quality output at the shortest turnaround time. Automation of data entry tasks allows companies to ease their workforce’s burden and focus on tasks that contribute to business growth.
● Lower cost of implementation and use.
In comparison to outsourcing data entry specialists, implementing an automated program can cost less. They don’t need to spend time and money looking for talent and training them. All they need is to run the program to make it work.
Overall, leveraging the latest technologies such as machine learning to capture data in real-time can help businesses adapt to the changing customer behaviors and needs.
Manual VS Automated Data Entry – What’s the difference?
Machine learning data capture automates data entering operations by utilizing machine learning.
Machine learning, or ML, is a branch of artificial intelligence (AI) that executes actions using algorithms and statistical models. This technology enables computers to predict accurate findings without the need for a programmer to code their action strings.
Machine learning systems use data to learn and enhance their performance over time. Machine learning takes tricky patterns or graphical information and performs statistical analysis to predict output data when it comes to automated data entry. This data learning surpasses the advantages of Manual Data Input services as one of the fastest-growing technologies today.
It is considered superior to outsourcing data entry in the ways listed below.
- Faster and Reliable Turnaround Times
- Easily Scalable No Matter What the Job is
- Lower cost of Implementation and Use
1. Faster and Reliable Turnaround Times
Machine Learning makes faster and reliable turnaround times with its data almost 100% automated. Moreover, Machine Learning Data Capture follows guidelines that ensure the output gets delivered on time. The systems adjust the algorithms to improve performance and automate data with 100% accuracy. Machine Learning is better than Manual Data Entry, especially when time and accuracy are considered essential factors.
2. Easily Scalable No Matter What the Job is
With each day, the industry becomes more competitive. Businesses must keep up with the competition by implementing best practices that result in high-quality output in the least amount of time. Moreover, they can relieve their workforce’s workload by automating data entry processes, allowing them to focus on duties that contribute to their success.
3. Lower Cost of Implementation and Use
Implementing an automated application can be less expensive than hiring data entry professionals. They don’t have to waste time and money seeking and training new talent. To make it function, all they have to do is execute the software.
Though it costs less, issues may still arise. Most of the outsourced staff could get located across the globe. They may also come from different cultures, which suggests that meeting halfway may be challenging. When one side refuses to learn about the other’s culture and location, poor communication and productivity can ensue.
When outsourcing, one needs to figure out what works best for the data collecting task at hand. Businesses should also consider the following:
- The size of the project
- Will the time be limited, or will it be ongoing?
- How soon is the output needed to be finished?
- Are there any other considerations, or is a simple Data Capture sufficient?
It makes sense to use technology for massive, continuous projects. In the long term, the expense of execution and the time it takes will pay for themselves. Manual data entry is frequently the best solution for one-time, small data capture operations.
Lets Start Automate Data Entry
Automated data capture offers the same advantage like manual data entry but with the use of artificial intelligence instead. It provides a competitive edge given that the algorithms can tremendously reduce manual errors in data entry reports.
Automated data entry software is the smart way to go if your organization is spending too much on manual data entry. After all, automated data entry system does not get tired, hungry, or feel bored.
Automating data entry tasks save time and money, encouraging organizations to allocate their budget to value-adding tasks. These are projects that require human intellect and intervention and ultimately bring growth to the company.
Moreover, our drastic transition towards the digital age led to the adaptation of more cutting-edge technologies. We can now leverage machine learning to make data entry more comfortable, more manageable, and productive.
The deployment of intelligent systems and solutions makes businesses more productive and reduces high operational costs.
Conclusion
Manual Data Entry and Machine Learning are both beneficial. When choosing between the two, one should consider the advantages and disadvantages that come with them. For small businesses, it is ideal for sticking with Manual Data entry, whereas, in much larger companies, it is recommended to adopt Machine Learning as time is a significant factor.
iTech’s automated data entry software is built with the ability to capture and process data from multiple verticals.
Depending on the project’s complexity, teams can apply OCR paired Machine Learning services or Robotic Process Automation. They can be used separately, together, or paired with manual processes depending on the input process and output needs.
Our data capture technologies can also help organizations to process unstructured documents automatically. This is important as data can be in different formats.
The results are unmatched quality, faster turnaround time, and lower operational and labor costs.
To solve all your problems with manual data entry, get in touch with our professionals today!
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IDS Commander iTech2021
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