Data entry automation. The key to optimize workflows

Data entry automation. The key to optimize workflows

By definition, data entry automation refers to the process of optimizing data entry by eliminating or reducing manual processes via software-based solutions. Such software can usually extract data from PDF files, documents, images, emails or websites and only present  the relevant information in a structured format.

The automated data entry software uses RPA and OCR, among other technologies, to cope with repetitive tasks and to “read” documents on a large scale. They are accurate, flexible, scalable, fast and save companies a lot of valuable time and resources.

• Upload or add data source

Organizations receive unstructured raw data in the form of documents, images or scanned files which have to be imported into the automation software data collection system.

• Process any file or document

This important step converts documents into machine-readable formats. Advanced OCR, AI and ML functions enable algorithms to “read and understand” documents.

Data entry automation software recognizes and extracts only relevant parts of the data inside a document or an image. The AI algorithm can be trained to identify fields and data points of interest.

This optional step enables manual or semi-automatic verification based on validation rules. The extracted data can be checked for correctness and, if necessary, even improved.

The data entry automation process’ final step is to deliver the extracted data to its downstream software. The extracted data as structured output (XML, JSON, Excel etc.) can be conveniently pushed/ imported into ERP/ CRM/ data warehouse/ data lake or any other software for further workflows. Almost all organizational processes & workflows can gain from information access automation.

Benefits of Data Entry Automation

Data entry automation is a blessing to many individuals of a record team. Be it a highly automated sector or any other, manual processing of data has been proven to be far more persistent when it comes to managing accounts, operational costs, etc.

Automated data entry software programs remove the inefficiencies of the paperwork done by humans. Businesses are choosing to automate their data entry processes completely for reducing costs, saving time, better accuracy, increasing productivity, and even increasing business scalability.

Few advantages of adopting information access automation are listed below:

●    Greater accuracy

Automated information access software programs leverage AI & ML competencies to extract information correctly and minimise post-processing. Such algorithms are prepared to deal with common information constraints & remove errors.

●    Reduces costs

Record keeping and data entry mostly requires hiring dedicated data entry professionals. You can easily reduce operational costs by doing away with inefficient processes done manually by leveraging OCR and Artificial intelligence.

●    Saves time

You can save up to 75% of time spent on data entry by deploying OCR. It helps in improving and creating efficient data processing workflows by faster data entry processes.

●    Highly scalable

You can equip yourself to handle any unexpected spike in data entry demand for huge volumes of data

●    Increases productivity

Allocate man-hours and resources to much more productive tasks that immediately affect the bottom line.

●    Increases worker satisfaction

Repetitive manual data entry processes impact workers, you can easily eliminate the need of monotonous data entry requirements and effectively engage your employees in more productive tasks.

When to automate records analytics?

Automation can truly advance and enhance the data analytics process, but the real question is when exactly should you deploy automation? As a basic rule, it is most appropriate for rules-based, repetitive tasks that are a part of a stable business process. However, with advancements in Artificial Intelligence, it has become possible to automate even the cognitive tasks that may not be rules-based.

Many analytical responsibilities could use automation:

  • Creating dashboards, and reporting in a trendy fashion, are perfect applications for automation. Automated analytics structures can help in streaming, processing, and aggregating records for publishing to interactive plots and live data summaries.
  • Automation simplifies records preservation responsibilities which include editing and tuningthe records in a data warehouse. An enterprise needs to take advantage of the numerous equipment that facilitates mechanically integrating new records, reassessing or migrating records from legacy structures.
  • Data entry automation can streamline records coaching responsibilities. Tools like visible programming platforms can mechanically label records, educate and validate models, and iterate verification of the runs to optimize parameters.
  • Another crucial application for an enterprise could be automating data validation to detect typos, flag off and impute missing values, while identifying content and formats that do not match a dynamic data model. Through this type of analytics automation, you will not only be able to streamline data modelling processes, but also will be able to enforce adherence to the dynamic data models by automatically analysing and transforming data.

When you are at a business juncture, where you think the above mentioned analytical responsibilities can be automated, that is when you must deploy data entry automation.

Read about Data entry automation Uses cases .

How does KlearStack enable businesses to automate their data processing?

KlearStack Artificial Intelligence automates the acquisition of invoices and free-form expense reports, resulting in fewer corrections, lower costs, and faster payments. KlearStack provides automated invoice processing without templates, reducing the hassle of manual entry of unstructured documents. Say no to templates and regex rules!

Interested in Intelligent Data Entry Automation Tools?

The OCR Platform from KlearStack is an intelligent data digitization solution which is powered by AI technology, and can accurately extract data from a variety of documents.

Ashutosh Saitwal
Ashutosh Saitwal

Ashutosh is the founder and director of the award winning KlearStack AI platform. You can catch him speaking at NASSCOM events around the world where he speaks and is an evangelist for RPA, AI, Machine Learning and Intelligent Document Processing.