Data is essential in today’s digital business world. Many of the world’s largest tech companies in terms of market cap rely heavily on data and even 45 percent of small businesses use customer information to drive marketing decisions. Data is also essential in the healthcare and manufacturing industries and many other sectors.
A surprising number of companies still rely on manual data entry to handle the information and figures necessary for their operations. Manual data entry is the traditional option for putting information into databases. It involves employees typing the data into spreadsheets, tables or documents, which are then organized and stored on hard drives, servers or cloud platforms.
Studies have shown that between 26 percent and 39 percent of healthcare workers spend time manually entering patient data and 48 percent of manufacturing companies still use manual spreadsheets or similar systems to record information. Entering data by hand is still common, but it exposes businesses and organizations to a unique set of problems that can only be solved by automation or simplification.
Why do companies collect data manually?
Manual data entry seems like a cheaper, more convenient option for many companies — especially small businesses or service providers. For example, a small accounting firm with a few clients may feel that manually filling spreadsheets is preferable to investing in new tech.
However, the time spent on repetitive, manual tasks could be spent on other activities. One study found that workers spend more than 40 percent of their time on simple, manual tasks. Small companies that automate could free their workers and managers to focus on higher-level tasks, like finding new clients or offering more lucrative services to clients. For example, an accounting firm could offer auditing, budgeting and financial analysis services after investing in software that could automate bookkeeping and reporting tasks.
What are the risks of manual data entry?
Manual data entry keeps businesses from having to invest in new software or change familiar workflows. However, this traditional practice exposes companies to risks. The most glaring issue is that mistakes in the entry process or failure to save documents or spreadsheets properly could lead to a complete loss of data.
Here is a closer look at what could go wrong for offices still opting for manual data entry.
Manual Data Entry Can Be Slow
Manually typing data into a spreadsheet can be tedious, even if the task is familiar and the employee has excellent typing skills. For companies that use large amounts of data for analytics purposes, manual data entry can be a full-time job.
The same is true for accountants, lawyers and other professionals who have to create detailed, information-dense documents.
In addition to tediousness, the time-consuming nature of manual information entry can cause delays and missed deadlines, which can be disastrous for some legal firms, accounting firms or any third-party service that needs to meet deadlines.
Prone to user error
Error rates for manual data entry are around one percent. This might seem like a small number, but keep in mind that an incorrect figure could cause other mistakes down the line, leading to errors that could have a major effect. For small accounting firms, such errors could be ruinous, leading to a loss of clients and even legal action.
More expensive in the long run
Manual data entry can be expensive on at least two levels.
First, in the long run, companies are paying employees to handle manual tasks that could be automated. A study by McKinsey found that employees spend 45 percent of their time on manual jobs that could be automated. These are wages that could either get cut out of the budget or be spent on workers handling more productive tasks that have a bigger impact on the company’s bottom line.
Secondly, errors are costly. Even small-scale mistakes can be damaging. For example, if an accounting firm makes an error while compiling a cash flow statement, they would need to first spend time and employee hours finding the error, then repeat the work necessary to correct the affected calculations. In addition to paying for the extra work hours, they may need to discount or refund the client, which will further impact the bottom line.
Tips for reducing manual data entry
It may not be realistic to completely automate data entry. The switch to full automation will take time. However, businesses can take steps to reduce the reliance on manual information entry and begin the process of saving time and money and reducing errors.
Here are the two different methods for limiting the errors, time requirements and costs associated with manual data entry.
Simplify data entered
Companies that still perform manual data entry can take steps to reduce the amount of information they have to input.
By first auditing the information to see whether it is relevant, it is possible to reduce unnecessary data entry. For example, an audit may find that some information is not important due to process changes in the business’s operations or new policies. Also, some data may be redundant because it provides the same insights as information already on file.
The simplification can reduce data entry time and make the data analysis process easier.
Automating data entry
Automating the process is the most straightforward solution to many of the problems with manual data entry. This step requires investing in software that can find, select and record information automatically.
However, computers are able to handle the process more quickly. Not only are their processors faster than the human brain and hands, but they function 24 hours per day, allowing them to continually record information without a break.
Also, automation can eliminate the human errors that inevitably happen during manual data entry. As long as the software has the correct parameters, it can enter information correctly without any typos or incorrect calculations.
Automated data entry has other advantages. Some software can even check existing data from outside sources for errors. This tool can help audit data sets from clients and find errors before the service provider uses the figures. Such software can also help with assessment and authorization tasks using AI and the cloud for auditing and communication between departments and from business to client.
Finally, in addition to data entry, some software can perform analysis of the information to provide additional insights helpful for the business or their clients.