Things To Know Before Automating Data Extraction and Data Entry

A survey conducted by OnePoll found that data entry is the most hated office task. The distaste is understandable. Manual data entry, and the associated task of data extraction, is tedious, monotonous, and can be mind-numbing. Despite this, or perhaps because of it, the average employee spends more than 40 percent of their day on data entry or related tasks. The benefits that can be acquired through automating manual data extraction and entry thus appear to be a no-brainer.

But automation is no magic formula. There are benefits as well as drawbacks, the relative weightiness depends on, among other things, the type of data. This article will guide you through the considerations before automating data extraction and data entry.

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Advantages of automating data extraction and entry

Automated data extraction and entry overcome many of the issues that come with the manual process. Automation of these tasks involves consolidating data and converting them into electronic files using tools and technologies such as optical character recognition, intelligent character recognition, and intelligent document processing.

Automated data extraction and entry offers several advantages.

Increased efficiency: Speed is the greatest advantage that automation has over manual. The artificial intelligence of automation tools combined with high processing speed enables them to scan numerous records and transcribe them quickly.
Improved accuracy: Human errors inevitably creep in during manual data extraction and entry. Automation eliminates errors commonly associated with manual data entry such as typos, transpositions, and omissions.
Faster analysis and clearer insights: Automation tools can extract large amounts of information quickly and accurately. The result of this is an early analysis of the extracted data and thus gaining valuable insights faster.
Cost savings: Costs associated with manual data extraction and entry—human, training, supervision—can be substantial. Automation can help reduce this significantly. Besides the labor costs, higher accuracy, faster turnaround, and seamless integration with ERP, CRM, or other systems that automation allows can contribute to a positive financial impact.

Automating manual data extraction: Techniques that can be used

Information is generally extracted from a document using optical character recognition (OCR) technology, which converts images of text into machine-readable forms. The extraction process can be rule-based or machine learning (ML) based.

In the above-mentioned method, hard-coded rules and workflows are used to extract information. This method is limited and unreliable for unstructured and semi-structured documents. Different rules have to be defined for different document formats. And if a change is made to the structure, then the rules need to be updated, too.

The machine learning approach uses smart algorithms that have been trained on extensive data to recognize and extract relevant information from documents. ML-based information extraction can handle structured as well as unstructured data and is more flexible. However, ML-based extraction tools often struggle with nuances and exceptions.

Challenges with automating data extraction and data entry

Automated data extraction and data entry provide plenty of advantages over the manual process. But they are not without drawbacks. And depending on how you view it, some of these problems can be severe.

Data insecurity: Relying on an automation tool for data extraction and entry means that the responsibility of data security becomes shared with a vendor. The tool runs software, all software has vulnerabilities, and vulnerabilities can be exploited. And since they’re generally cloud-based, the risk is increased.
Reduced control and visibility: Automated data extraction generally happens on the cloud. Organizations thus lose some visibility as the operations are generally obscure and they cede control over their data in relation to monitoring and logging.
Limited flexibility: Automation tools provide generic, one-size-fits-all solutions but organizational data extraction and entry needs are anything but. And they adapt poorly to dynamic changes in the web, making them unsuitable for extracting web content. Further, the quality of the output of automated extraction and entry depends on the input, thus automation is ineffective for a sizeable amount of data types.
Unsuitable and impractical for some: Organizations that do not work with large data or that have disparate data types may find it uneconomical or impractical to use automated data extraction tools. These tools may also require some technical expertise to leverage them maximally.

Outsourcing as an alternative: Overcoming the challenges of automation

Automated data extraction and entry is handy but the handiness comes with ingrained hitches. To enjoy the benefits that automation offers without the downfalls that come with it, you’ll have to look for a viable solution like outsourcing. You can partner with external service providers such as a reliable data extraction company that can provide specialized data entry and web data extraction services.

When you outsource data extraction services, you get the advantages that automation provides—accuracy, efficiency, and cost-saving—without the drawbacks. Data extraction and data entry service providers generally have the latest tools and skilled personnel and offer cost-effective solutions. They leverage the speed that automation enables with humans in the loop serving as crucial checkpoints. This helps guarantee efficiency without sacrificing accuracy. And because there is no lumpsum investment in technologies or hiring and training employees, cost savings from outsourcing can be substantial.

Outsourcing can also help avoid the problems of data insecurity and lack of flexibility inherent in automation. Depending on the sensitivity of the data, a suitable outsourcing company can perform the extraction and entry operations onsite, reducing the risk of interception and leakage.

A data extraction and entry company also does not operate on predefined rules, unlike an automation system. It is thus more flexible and adaptable to specific needs. Endowed with humans with diverse domain expertise, it can handle complex and nuanced data much better than an automation tool can. Whether the need is based on data type, size, or scale, it can be concluded that outsourcing is more flexible than automation.

In a nutshell

Automation systems for data extraction and data entry have helped reduce the tedium associated with the task significantly. Not only that, automation can help enhance quality and speed and reduce costs.

But using automated tools remains fraught with hurdles and concerns. Some issues are weighty and can completely undo the benefits of automation if run into. Outsourcing bypasses the problems with automation and offers a pragmatic alternative, combining the efficiency of automation systems with the reliability of humans.