Keeping your business competitive in today’s fast-paced markets requires efficient and streamlined processes. If your business relies on data that is not available in an easy-to-access format, manual data entry can quickly become a bottleneck and harm your business. Data entry automation software can help your business eliminate such bottlenecks and automate entire workflows.
A Rising Need For Automated Data Entry Tools
Today’s businesses run on data, and having quick and reliable access to data is a significant competitive advantage. But what are the options if your business relies on data which is trapped inside PDF or printed paper documents?
All too often, manually re-keying data is the answer. But manually extracting data from PDF documents or other sources is not only time-consuming and tedious, it also comes with elevated costs, high error rates, and scaling issues.
Luckily, there is a better way. Automated data entry is a viable solution for businesses of all sizes to automate document-based workflows.
What Is Data Entry Automation?
The term Data Entry Automation describes a group of software products that are used to streamline data ingestion processes. Automated data entry systems are capable of reading information from a difficult to access data source (PDF files, printed documents, emails, websites, …) and ingest the data into a more adapted data storage (databases, spreadsheet files, …).
The goal of data entry software is to replace or streamline a workflow that is usually performed by a human data entry clerk with a fully or partially automated process.
Popular Use Cases For Automated Data Entry
Data entry automation has a wide range of use-cases. In a typical office setup, automated invoice scanning probably belongs to the better known use cases. Another popular use case for data entry automation is form processing. Automated form processing is heavily used in a variety of industries, for example for insurance claims, medical forms or mortgage applications.
Next to automating document based workflows, obtaining data from websites is another application for data entry automation. Web scraping (see below) is for example used to read pricing informations from ecommerce websites or extract contact information from business websites.
The Process Of Data Entry Automation
An automated data entry system consists of multiple independent processing steps. The diagram shown below shows the basic steps of an automated document processing system.
From left to right, the steps in the diagram are: Import the original documents, Preprocess each document (OCR), Extract the data fields you are after, Validate the extracted data, Dispatch the data to where it belongs.
Let’s cover some of the process steps more in detail …
Preprocessing And Parsing Documents
One of the challenges of automating a data entry process is to obtain the data in a machine-readable format. While humans are well trained to understand visual representations of data (e.g. an invoice or a report), it is sometimes challenging to teach a computer to find and extract the right data. The process of programmatically obtaining the right data from a visual representation which was designed primarily for humans (documents, computer displays, …) is called Data Scraping.
Optical Character Recognition (OCR) is a technology heavily used in data scraping. OCR is used to convert a visual representation of text (e.g. a scanned document or text shown on computer display) to a machine-readable string of characters.
Web scraping is another frequently used method to obtain data from documents which were primarily built for humans. Web scrapers are capable of extracting certain data fields from websites and internet applications. As websites are built using text-based markup languages like HTML, web-scrapers can leverage the structuring HTML tags (HTML DOM) to identify the right data more easily.
Once the full text of the document is available, it’s about time to identify and extract all relevant data points. This process is called “parsing” and there are different approaches to do this. For example, Docparser is a PDF parser which offers a point & click interface to create custom layout parsers without any coding.
Augment And Validate Data Manually (Optional)
While full automation is the ideal scenario for most businesses, having an additional human operated step in the process is sometimes necessary.
Depending on where your data was initially stored (e.g. a scanned document), you might want to add a manual validation step to correct wrongly detected text values. This additional step is for example needed, if the accuracy of your OCR process is not high enough due to low quality scans.
Another case for human intervention is to augment data sets before sending them to your target system. A human operator can for example search for additional information in another data source and augment the initial data set manually.
Move The Data To Where It Belongs
Obtaining a clean set of structured data (e.g. CSV, XML or JSON) is just one part of the equation. The full power of data entry automation is obtained whenever the extracted data is automatically moved to a target system of choice, for example a fully automated PDF to database, or PDF to Excel conversion.
At Docparser, we offer various integration options which let you automatically import documents and send the parsed data to hundreds of apps in real-time.
Things To Consider When Setting Up An Automated Data Entry System
Data Entry Automation Is About Saving Time
Obviously, saving time is the biggest selling point of an automated data entry system. Measuring how long it takes to perform one single data entry task manually will give you an instant idea of the time savings which you can achieve. Multiply this with your monthly task volume and you get an idea of the time savings involved and your ROI.
Measuring your estimated time savings also allow you to fix a budget for setting up an automated system. If setting up an automated system takes months and costs a fortune, you might just be better off continuing with manual data entry.
Other Questions To Ask Yourself
There are however a couple of other things you should consider before spending time with setting up an automated system. In a nutshell, you need to ask yourself
- if your task can be automated from a technical point of view
- if it makes sense from a business point of view
From a technical point of view, you can ask the following questions when choosing a data automation provider:
- Can the data in its current form be read by the system?
- Is it actually possible to correctly interpret your text data and convert it into well-structured data objects?
- If OCR is needed, what level of accuracy can be achieved and what level is needed?
- Can you automatically validate the data with a set of custom rules?
- Is a manual data validation step needed?
- Does your target system provide an API to automatically import the data?
From a business point of view, the following questions should not stay unanswered:
- Are you legally allowed to access this data programmatically? (e.g. many websites forbid web-scraping)
- How much does it cost to set up an automated system?
- Who will set up and maintain the system?
- After how many weeks/months is the automated setup generating a positive ROI?
Where To Get Started
There are many different data entry applications on the market and each of them comes with its own specialty. Traditionally, many data entry applications were custom solutions for rather big enterprise customers. With the rise of cloud applications, data entry software for small businesses is available nowadays though.
If you are looking for a document workflow automation solution, you are already at the right address. Our solution Docparser (see screenshot below) offers a powerful and affordable set of tools to extract data from PDF, and to automate entire document-based workflows. You can create a free account right now without any strings attached. Setting up Docparser is easy and most users have their first documents parsed within a couple of minutes.
If you don’t want to automate a document based workflow, but rather read information from the internet or a computer display, try a Google search for “Robotic Process Automation” (RPA) or “Web Scraping”. Spoiler alert: RPA is a technology mostly used in big enterprise corporations.
In case your data is currently available in a cloud application and you want to automatically move it to another software, check out integration platforms such as Workato, Zapier or Microsft Flow might actually be a good fit. Docparser integrates will all of the mentioned platforms seamlessly.
How does your data entry workflow look like? What is your experience with data entry automation? Let us know in the comments or contact us by email.