Methods of Data Capture

Manual keying or data entry is still relevant with certain types of unstructured data where automated capture methods achieve low accuracy levels or volumes are so low and variable that automation is not justified.  ProcessFlows can provide manual keying, verification services and even hybrid automation as a managed service.

OCR technology revolutionised data capture and underpinned the digitisation and automation of back office operations that involved the processing of paper or digital documents such as PDF invoices, contracts, ID etc.

As a technology it provides the ability to recognise machine produced characters as part a data capture and extraction process. OCR systems can recognise many different OCR fonts, as well as typewriter and computer-generated characters.

Data capture has evolved significantly over the years from early versions that relied on simple character based OCR , to modern versions that incorporate Word recognition, zonal and document recognition as well as Artificial intelligence such as pattern recognition and machine learning to deliver the most accurate recognition for computer generated text. Please click here to learn more about OCR. Today, there are a wide range of OCR solutions available – either as a dedicated OCR application or a platform/ hybrid solutions.

Dependent upon the type of barcode that is used, the amount of metadata that can be included or marked up can be high, as is the level of recognition. QR codes for example can contain webpage links ultimately linking a webpage of almost anything and any amount of information. Barcodes can be applied to documents, webpages or almost any objects for a range of purposes including inventory management, location or task tracking, webpage opening or authentication via authenticated app, production batch tracking, delivery notes, digital form locating and more. Smartphone with barcode applications have removed the need for dedicated barcode scanning tools making barcode use even more affordable. For more about Barcodes, please click here.

Intelligent document recognition also interprets and indexes different documents based on the document type, its meta data and elements of the document identified. For example, invoices, letters, contracts, post codes, logos, key words, VAT registration numbers. Data that has been identified through OCR can be validated and verified through look-up tables and database as well configure or “taught” rules associated with such documents and data. and even databases to maximise accuracy.

Specialised applications exist for departmental projects such as invoice processing. IDR applications can hold information about suppliers generated from other line-of-business systems and match invoices to that information, using recognised text such as VAT number, telephone number, post code etc. The application then looks for keyword identifiers on the invoice and extrapolates the value nearby. Validation rules are then applied, for example the NET amount plus the VAT amount must equal the gross amount, minimising the chance for errors.

Despite advances in data capture and artificial intelligence, exceptions can happen when an automated approach is unable to confidentially automate a task such as the extraction of text (based on a set of rules or a recognition profile). When this happens an exception can be thrown and the task is passed to service desk for verification. Service desks can also assist machine learning to improve or train automated processes such as data capture or decision making. Our hybrid automation platform combines artificial intelligence with Human intelligence to offer the highest level of automated data capture of unstructured documents as service. An application of this approach is the ProcessFlows Intelligence AP automation service.

A valid digital signature associated with an email or document allows a user’s identity or the authenticity of digital messages or documents to be captured. Digital signatures are often used for digital approval workflows involving parties from different companies or entities.

Screen scraping is used by Robot Process Automation and other tools to navigate, interact and capture raw data that appears on a display digital display, application or website. Once the data is captured, it is then analysed to extract elements such as text and images etc and then a workflow executed to process the data as defined by the configured workflow rules.

This approach is used to capture human marked data on scanned forms, surveys and exams. A natural question to ask would be why a digital form won’t suffice before using this approach.

Magnetic swipe or proximity cards are used to store data. Card readers capture this data to confirm identity and control to access to a building or shared device for example. Bank cards are also Magnetic cards but include additional security features such as the Chip and Pin.

Intelligent image and video data capture involves real-time analysis of images and moving image data for objects or “triggers” before executing a certain process. There are a wide range for applications for automated image and video data capture and analytics including: health & Safety or QA monitoring, crowd and footfall analysis, sentiment analysis, facial recognition, ANPR (Automatic Number Plate Recognition), Fire detection or elevated temperatures in humans, animals or machinery (Thermal imaging), site protection, People counting, queue monitoring, patient activity, object counting, behavioural detection, prevention of vandalism and theft. Examples include: Konica Minolta Intelligent Video Solutions.