Top Logistics Automation Systems You Should Implement
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Data capture is a technology designed to extract data from physical sources (analog data), converting it into useful digital information (digital data).
In the dynamic landscape of today’s business world, knowing how to capture the right data efficiently and accurately is no longer an option — it’s a necessity. In other words, businesses must appreciate the significance of real-time data if they want to keep a competitive edge and this is where data capture comes in.
Data capture refers to the process or technologies that help businesses extract certain information from documents or forms and turn them intro structured formats that can be used by computer for further processing or analysis. The captured data can act as the fuel that drives various automated workflow and decision-making.
In this blog post, we'll talk about the process of capturing data, the different methods of data capture, and solutions that can help businesses automate data capture.
In the past, data capture was a manual process. Businesses would have to hire workers to read the paper documents, identify data fields that need to be extracted, and manually enter the relevant information into different software or a centralized system. This was not only time-consuming but also error-prone. Even a simple typo could result in incorrect data input into the system, leading to downstream issues.
Now, with more advanced technologies, businesses can automate data capture. Automated data capture uses technology, such as optical character recognition (OCR), machine learning (ML), natural language processing (NLP), and more, to extract data from documents automatically. This is a much more efficient and accurate way to capture data, eliminating the need for manual input.
Organizations can use data capture technologies in a variety of ways, such as:
As you can see, data capture has a wide range of applications. It can be used to automate various business processes and workflows, which can lead to increased efficiency and productivity.
In today's digital age, data is more critical than ever before. Businesses rely on data to make informed decisions, enhance operational efficiency, understand their customers, and improve their products and services.
However, a lot of data is still trapped in physical documents and forms. About 80% of data is unstructured, which means it's not in a format that computers can easily analyze. This includes data like emails, images, PDFs, and handwritten documents.
Businesses need to capture this data and convert it into a digital format to unlock its value.
To better understand how data capture works, we need to look at some of the different methods that businesses use. Here are the two main types:
This is the traditional approach to capturing data from documents. As the name suggests, manual data capture involves manually entering information into a computer system. One has to key in what's captured from the document and do any required validation.
The disadvantages of manual data capture are obvious. Firstly, it is time-consuming. At a time when things move fast and time is of the essence for many businesses, manually entering data isn't feasible.
Secondly, it's prone to data entry errors. Humans make mistakes and often need to go back and re-enter data as a result. This inevitably leads to lost productivity and operational inefficiencies.
Moreover, manual data capture does not scale well. As a business grows larger and processes more documents, this approach quickly becomes unsustainable.
This is the modern alternative to manual data capture. Instead of manually keying in information from a document or form, businesses can use automation software to extract that information automatically. Thanks to artificial intelligence (AI) and machine learning, this software can understand the document's layout and extract relevant data with little human input.
There are different ways to automate capturing of data, including:
OCR entails scanning text within an image or PDF and extracting it. It then converts that text to machine-encoded text. Unfortunately, the information isn't structured, so the results cannot be utilized by a computer.
ICR is a more advanced version of OCR. This version can even recognize handwritten characters and extract data from them. However, ICR also suffers from the same issue as OCR in that it can only extract unstructured data.
Intelligent Document Processing is the most advanced and sophisticated approach to data capture. It leverages several AI technologies like OCR, ML, LLM to understand the content of the documents, identify the relevant information, and convert them into formats that computers can understand.
It can automatically extract data from images, PDFs, and handwritten documents while understanding the context and organizing it into a structured format. This makes it possible to use the data directly for business purposes.
Barcodes or QR codes are often used to store data about a product, such as its price or SKU number. This information can be captured using a barcode scanner and imported into a computer system.
This method facilitates data capture through web and mobile applications. It is customizable and eliminates the need for paper-based forms. Digital forms offer greater security and privacy, as data is stored electronically and can be password-protected. Additionally, they can be integrated with back-end systems for even greater efficiency.
Digital signatures often replace paper-based signatures and can be used to sign documents, contracts, and other legal agreements.
Digital signatures are more secure than traditional signatures, as they cannot be forged. They also provide a record of when a document was signed and by whom, which can be useful for auditing purposes.
This method involves using bots and web crawlers to search and collect data from the internet. This data can then be transferred to relevant databases for use. The main advantage of web scraping is that it can be used to collect constantly changing data, such as weather data or stock prices.
Voice capture is a data entry method involving using speech recognition software to convert audio recordings into text. This text can then be transferred to a computer system for further processing.
It can also be used to understand and interpret spoken commands. Apple's Siri, Amazon's Alexa, and Microsoft's Cortana are all examples of voice capture technology.
Many other data capture methods exist, including magnetic stripe cards, Optical Mark Reading, Magnetic Ink Character Recognition, smart cards, video/image capture, and more. However, these are the most common methods used today.
Investing in data capture in your business can profit your organization in several ways. Here are some of them.
Data capture technology helps businesses improve overall efficiency a few ways. Firstly, it can process documents much faster than manual data entry. After training the extraction models with enough number of samples, automated data capture solutions can quickly read and interpret data from various types of documents. This can free up employees from manual data entry, time that can be used for other tasks that can create even more value than manual data entry.
Secondly, data capture technology is much less error-prone than manual data entry. This is because the technology can read data more accurately and consistently. This can help reduce errors in data entry, saving businesses time and money.
Finally, structured data generated by data capture technology enables the automation of various workflows. This can help businesses automate repetitive and mundane tasks. For example, a data capture system can automatically populate invoices with data from a sales order or even automate account payable processes.
Wait times are one of the most common complaints that customers have. This is especially true in customer service-oriented businesses, such as retail or hospitality. Data capture can help to reduce wait times by quickly collecting customer data and transferring it to the relevant system.
For example, a data capture system can retrieve data from IDs and proof of address documents in order to open a new customer account. This can be done in a matter of seconds, rather than the minutes or even hours it would take manually.
Storing data physically comes with a lot of risks. Physical documents are prone to damage; once they're gone, they're gone for good. There's also the issue of security — unless you have a very sophisticated (and expensive) system in place, anyone can access your physical documents.
Data capture technology helps to solve both of these problems. By digitizing your data, you can create backups and manage access much more easily than with physical documents. This makes your data more secure and less likely to be lost or damaged. In addition, it makes it much easier to track who is accessing your data and when, which enhances security even further.
Data capture technology helps businesses to get usable insights in real time. This allows for better and faster decision-making. For example, retailers can use data capture to gain insights about consumers' purchase behaviors, frequencies, preferences, and more. This information can be used to segment customers and send them personalized recommendations. In this way, data capture technology can help businesses to increase customer loyalty and improve their bottom line.
FormX is the leading data capture platform, helping businesses, including major shopping malls, real estate businesses, charities, etc., automate their data capture and various workflow with little to zero code. We can process various documents, such as invoices, receipts, proof of address, bank statements, etc.
Alternatively, you can train your own custom extractor that requires as little as one sample to train and a few minutes to set up.
Contact us today to learn more about how FormX can help your business.