There are multiple methods of automatic data capture available to capture, extract and classify unstructured data  such as documents, images, videos, emails, websites, surveys and so on. The list of methods of data capture listed below is not exhaustive but it is a guide to the key methods used as part of business process automation project.

Due consideration of the origins of the data should be considered as it may be easier to integrate or capture the original data at source rather than use a processed or unstructured form of the data.  This is one of the key principles of Process AutomationBusiness Process Management best practice and optimisation.

There’s many methods of data capture for different scenarios and types of data.

Book in a 30 minute consultation with one of our Data Experts here to discuss your requirements.

Modern solutions for automated data capture and process automation often apply one or more of the methods below to achieve maximum accuracy depending on nature of the data and application use. The most appropriate data capture method depends on the nature of data to be captured and the application area.

  • Manual Keying


    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.

  • Nearshore keying


    Nearshore keying is the same as Manual keying but instead of the task being completed in-house it is delivered by a managed service or delivery centre within the European Union. Nearshore keying of Metadata can be an appropriate option when there are highly variable documents being processed or where automated methods result in exceptions that need to be handled manually.

    ProcessFlows can provide manual keying, verification services and even hybrid automation as a managed service.

  • OCR (Optical Character Recognition)


    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.

  • ICR (Intelligent Character Recognition)


    ICR is the computer translation of hand printed and written characters. A scanned image of a handwritten document is analysed and recognised by sophisticated ICR software. ICR is similar to optical character recognition (OCR) but is a more difficult process since OCR is from printed text, as opposed to handwritten characters which are more variable. Please click here to learn more about ICR.

  • Barcode/ QR recognition


    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.

  • Template based intelligent capture


    Templates are used to reduce variables and risks of failed data capture by optimising the capture process to certain document templates. This is combined with OCR & ICR to identify machine produced and to a lesser degree handwritten characters that are contained in particular area(s) of a document. This capability can be useful where the number of different document types being received are relatively low (typically up to 30 different document types) but consistent. Common applications include census, inter-bank transfers, logistics forms and application forms. Readsoft Forms uses this capability. Explore ReadSoft Data Capture and other solutions here

  • IDR (Intelligent Document Recognition)


    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.

  • Artificial Intelligence and Data Capture


    Artificial Intelligence is ultimately an umbrella terms for different artificial intelligence techniques. AI is best viewed in context of the use case and application. All of the methods described here can be augmented to some degree or another by Artificial intelligence such as

    • Computer vision, Image or pattern recognition to improve the recognition of any type image.
    • Neural Networks & Machine learning to assist with accurate recognition training based on large data sets and assisted learning.
    • Natural Language Processing for interpreting sentences and their meaning.
  • Hybrid Intelligent Automated Data Capture & verification services


    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.

  • Digital forms - Web or App


    When collecting information from users, which doesn’t exist already, it often makes sense to capture the data through a digital form either on the web, via an intranet page or smartphone app. Digital forms can be designed to structure the answers and data collected by avoiding too many open answers. They can also dynamically adapt to responses and prepopulate where information exists already. Ie. address look-up.

  • Digital Signatures


    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.

  • Web scraping or monitoring


    Since there is now a huge amount of data on the web, web scraping tools, called web bots or crawlers (ie. Google spiders) are used to crawl through web pages and code to collect, analyse and index specific data. Web scraping is used to capture and monitoring many types of web data such as news, updates, prices, contacts, policies, share data, currencies, connected devices, comments and reviews – basically anything accessible via the web.

  • Screen Scraping


    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.

  • Legacy System Integration or Data Import & Migration


    If data can’t be accessed in a legacy system due to missing features or proprietary APIs, products such as Alchemy Datagrabber Module, Formate and OnBase allow organisations with legacy systems (mainframe systems) to ingest data for improved search and archival applications.

    Examples include cheque requisition reports, property tax reports, invoice and credit note runs. The reports would be parsed by the application and broken down into individual records or pages. At the same time, index information is extracted from each record or page and associated with that record or page.

    The full text content of the document is also made available for searching. To improve the presentation of the document to the end user, an overlay can be added. The Overlay can be a representation of the form or paper that the original report would have been printed on. Therefore, in the case of an invoice, the record resembles the original printed invoice. Datagrabber can also be used to import images, or files, along with indexing information extracted from a legacy system or from a manually created file. It can also be used to create the required structure of a database within Alchemy.

  • OMR (Optical Mark Reading)


    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.

  • MICR (Magnetic Ink Character Recognition)


    This is a data capture technology capable of recognising characters machine printed in a magnetic ink. It is mainly used in the bank industry for cheque processing.

  • Swipe or Proximity cards


    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 Voice Capture


    The boom in smart devices has also seen the rise of voice controlled virtual assistants from the likes of Apple (Siri), Google (Google Assistant), Amazon (Alexa) and Microsoft (Cortana). These are the best examples of voice capture being used mainstream in our everyday lives. There are now many applications of Voice data capture in businesses. For example, applications such as CX-E (CallXpress) and virtual assistants provide the ability to capture voice commands and initiate business processes, transcribe voice mails and other functions unifying verbal communications data with other channels. Contact centres are a good example of where the unification and integration of voice data alongside voice, instant messaging, email, fax and forms deliver enhanced customer experiences and business processes.

  • Intelligent image & video capture


    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.

  • Augmented Reality


    Augmented reality is closely linked to video analysis and involves the real time processing of camera footage looking for programmed “trigger” objects. If a trigger object is identified, a process is executed to for example display an overlay graphic, video or other web data. AR applications are increasing in popularity as the digital and physical worlds get closer ie Google Streetview, Skyview, Pokemon. Our Airelens AR solutions is used to assist Remote Services operations in the field.

With advances in cloud computing, AI and mobile technology, data capture has come such as long way recent years and is required in some form in almost every digital process. The digital world can overlay and co-exist with the physical world and business operations to create new value and possibilities in our personal lives as well as our working lives.

Request a Consultation with a Data Capture Expert

What’s your data challenge?

We offer data and process consultations to help identify the right method of data capture for your requirements and process.

Book your consultation today:

Quick Contact