For decades, data capture has been an arduous, manual process whereby individuals have had to spend countless hours inputting data. It’s slow, tedious and often inefficient work. In fact, just the mention of “data capture” probably conjures up mental images of people tapping away on keyboards in a semi-robotic fashion with a vacant, far away look in their eyes.
But recent years have seen tremendous leaps and bounds in the realm of automation technology. This has largely relegated these data capture and data entry scenes to the historical realm
Using Machine Learning for Data Capture – How it Works
Machine Learning is a form of artificial intelligence (AI) that lends itself to use in conjunction with optical character recognition (OCR) technology.
OCR technology is perfect for data entry because it captures images of characters and then converts those images into text. Of course, this technology is not perfect and errors can arise during the scanning process — usually due to anomalies in the original printed materials. That’s where machine learning comes into play. Machine learning capabilities are integrated to make corrections as needed.
Machine learning is a “smart” technology that becomes more efficient over time. The algorithm is updated continually, so the technology is “learning” and improving from past mistakes and errors. Some human oversight is still necessary, but the amount of man hours required to capture a given data set is dramatically reduced — sometimes to mere minutes.
Five Ways OCR Data Capture is Benefiting from Machine Learning Technology
Machine learning has proven to be a game changer in the world of OCR and data capture. Here are five areas where we’ve seen tremendous leaps by way of efficiency, accuracy and breadth of capability.
Benefit #1: Human Error is Eliminated – No matter how experienced, dedicated or focused, human error is always going to be a factor when performing data entry. The repetitive, boring nature of this work means mistakes are inevitable. Even a small mistake — such as the omission or misplacement of a comma or decimal point — can have devastating effects. Machine learning-powered OCR data capture technology is far less error-prone. When a mistake does occur, the software’s algorithm can be updated to ensure that future errors are averted. This technology can also spot possible or likely errors, identifying suspicious locations in a data set so a human can review and make corrections when necessary.
Benefit #2: Data Type Comparisons – Data comes in many formats and machine learning technology is very effective at achieving uniformity and accuracy in this regard. A capable developer can configure the OCR data capture algorithm so it can process data such as currencies, postal codes and mapping data into consistent formats and tables. This not only saves time, but it also helps to maintain a data set’s accuracy since these are figures that might otherwise need to be addressed manually by a human data entry specialist.
Benefit #3: Continual Improvement – As the name suggests, machine learning technology continually improves and learns. That is quite remarkable! The algorithm is updated as new trends or patterns emerge. Updates are also performed in cases when a rare error is identified. This technology is such that it may never repeat the same mistake twice, leading to improved accuracy, efficiency and speed.
Much of the “learning” that occurs happens automatically, but it’s also possible to use this technology in conjunction with human insights. For instance, machine learning technology may identify a suspicious region of data, flagging it for human review. The human reviewer corrects the issue and the algorithm “learns” from this experience, applying its new lessons to future data captures.
Benefit #4: Data Capture Continuity – Human data entry specialists are just that — human. They get burned out. They get sick. They may quit their job. And when a keyer is lost, it represents the loss of time and money that was invested in their training. You may also see an adverse impact on consistency and continuity. Machine learning technology combats this by providing exceptional continuity and consistency.
Human data entry workers may also exhibit variances in their performance (in terms of quality, consistency and speed). All of these factors affect data capture and the overall quality of the data set. But machine learning brings unwavering consistency — consistency that humans simply cannot parallel. Improvement is the only change you’ll see with machine learning-powered data capture.
Benefit #5: Data Trend Identification – Data analysis is where the true value lies. Machine learning is extremely effective at identifying trends and patterns that might evade even the most seasoned analyst. The result is a technology that’s ideal for not only capturing the data, but processing it in a way that generates key insights to guide and inform business decisions.
Many business leaders find it intimidating to bring in a new technology that will take over a task that was previously performed by human hands. But with the right developer, the process can be a smooth one that brings nothing but positive results.
To learn more about how your business can integrate machine learning capabilities into your OCR data capture and automation tools, visit iTechData.ai.