Data capture is an essential component of workflow across various industries. The term refers to the process of data extraction from diverse document types (structured, semi-structured, and unstructured; digital and paper documents) and its transformation into a machine-readable format.
At this time, data capture technology is becoming the core solution for document processing optimisation. Data capture improves business work through automatic extraction, accurate classification, and relevant data recognition functions. It makes information search faster and more effective.
Due to the Grand View Research report, the global automatic identification and data capture market is predicted to expand at a compound annual growth rate (CAGR) of 11.7% from 2024 to 2030.
Software to capture data has high demand from the banking sector. It helps lead paperless operations and allow digitally connected banks to process workflow effectively and respond faster.
In this publication, we make a detailed overview of data capturing: describe its definition, clients’ sectors, the process stages, applied methods, and benefits of this technology for your company.
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What is data capture?
Data capturing definition refers to the process of data extraction from different types of documents to transform them into a machine-readable digital format. These documents can be structured or unstructured, paper or electronic.
Data capture works in definite stages: scanning, identifying, capturing, recognising, recording, and storing data from a file without manual entry. This solution optimises routine processes as managing assets, delivery, inventory, scanning, and security of documents.
Recent developments in the artificial intelligence (AI) field have moved data capture to a new level of ability to study information and improve software skills.
Automated Data Capture Applications across Industries
Automated data capture plays a crucial role across various industries and helps to accelerate the workflow, improve accuracy, and enable real-time decision-making. Below there are just a few examples:
Retail:
- Automatically capture sales data including transaction details, product prices, and payment methods.
- Track inventory movement and manage stock levels.
- Capture customer data and purchase history automatically.
Healthcare:
- Electronic Health Records: Capture patient data such as medical history, treatments, and prescriptions digitally.
- Medical Imaging: Automatically capture and analyze data from diagnostic imaging (e.g., MRI, CT scans).
- Wearable Devices: Collect patient health parameters, such as heart rate, sleep patterns, and activity levels continuously.
Manufacturing:
- IoT Sensors: Capture data from machinery and equipment to monitor performance, predict maintenance needs, and optimize operations.
- Supply Chain Management: Automatically capture data on inventory levels, shipments, and logistics to enhance efficiency and reduce costs.
- Quality Control: Use automated systems to capture data during the production process to ensure products meet quality standards.
Finance:
- Transaction Processing: Capture and process financial transactions in real-time, ensuring accurate record-keeping and compliance.
- Risk Management: Automatically capture and analyze data related to market trends, customer behavior, and economic indicators.
- Fraud Detection: capture and analyze data for identifying potentially fraudulent activities.
Transportation and Logistics:
- GPS: Automatically capture data on vehicle location, speed, and route to optimize logistics and improve delivery efficiency.
- Fleet Management: Capture data on fuel usage, vehicle maintenance needs, and driver behavior to reduce costs and enhance safety.
- Package Tracking: Automatically capture and update data on package location and delivery status to provide real-time tracking information to customers.
Telecommunications:
- Network Monitoring: Automatically capture and analyze data on network performance, traffic patterns, and service outages.
- Customer Service: Capture customer data and interactions automatically to personalize services and improve customer satisfaction.
- Billing and Usage: Automate data capture related to usage patterns, billing details, and payment information for accurate billing and revenue management.
How does Data Capture Work?
The digitalisation of business documents makes valuable data more accessible. You can capture data using different ways depending on your needs. It helps to optimise accounting workflows and provide seamless data transfer to necessary destinations.
Data capture devices can represent document scanners, barcode scanners, smart card readers, and special capture pads. Companies use this equipment to capture all needed information to make more informed and analytical decisions.
Organisations can capture data in 6 common steps:
1. Input
At this stage, the software scans paper or electronic documents and converts them into high-resolution files. Data can be hand-typed or printed in a file of different formats.
2. Correction
This stage is needed to prepare documents for optical character recognition (OCR) work. The system removes noises and corrects screws, makes binarization and skeletonization.
3. Detection
The software detects invoice aspects like tables and graphs. It helps provide accurate data extraction, use less disk space, and make faster validation.
4. Recognition
At this step, the software recognises data and each data field as a vendor name, a document number, etc.
5. Validation
The system provides the accuracy and quality of the recognized data by performing different checks.
6. Extraction
The OCR software helps extract data from document parts like tables, headers, footers, and other regions. Then the system uses this data to fill the relevant fields in electronic invoices and to feed it into the requested accounting system.
What are the methods of data capture?
Your company can choose the method to capture data depending on your business model and required information. Various software provides data capturing from different document formats: manually written, JPEGs, PDFs, emails, and many others. We mention the most popular methods below.
1. Manual data capturing
This method represents hand-typing requested data from written documents into a computer system for digital access. Manual keying is still relevant to capture unstructured data when volumes are so low that automation is unprofitable.
2. Automated data capture
This method helps businesses to optimise workflow by speeding up data extraction and reducing operational costs and human resources. Companies can capture data automatically with various technologies.
a) Optical character recognition (OCR)
This solution has developed a way to capture data. It increases the automation of back-office workflow that can involve PDF invoices, receipts, contracts, and other business document processing.
This technology provides automatic recognition of machine-produced characters during data capturing and extraction. OCR solution can recognise various fonts like printed and computer-generated characters. You can read more about this tool in our OCR tools benchmarks publication.
b) Intelligent character recognition (ICR)
The technology is applied in recognising handwritten and printed characters. ICR software captures and analyses handwritten documents like purchase receipts and employment applications. ICR solution is similar to OCR but more difficult due to the variety of handwritten characters with which this technology works.
c) Intelligent document recognition (IDR)
This solution combines various artificial intelligence (AI) technologies like computer vision and natural language processing (NLP). They help to identify patterns, index them on content type, and verify against lookup tables for correctness. The IDR solution is useful for forms and receipts processing, customer service support, and mailrooms. You can explore this tool using a free trial for intelligent document processing by Graip.AI.
3. QR codes and barcodes
Barcodes contain encrypted information in the 1D format. You can read them using a barcode scanner. Barcodes are relevant in various sectors. In retail it can be used for inventory management, in logistics for location or task tracing, in medical services to check patient details, and in manufacturing to track product batches.
Quick response (QR) codes or 2D barcodes are more complex solutions. Companies can use this solution to capture data in documents, web pages, etc. Many digitised sectors apply QR codes. This solution is usual in retail, courier services, product packaging, and advertising. QR codes can contain links to any webpage with any amount of information.
4. Optical mark reading (OMR)
This electronic capturing method identifies human-marked data as darkened fields and checkboxes in documents. Due to its high accuracy, OMR provides perfect captured data from scanned survey forms, ballots, and objective tests.
5. Digital forms (web or app)
Sometimes companies need to collect information about Internet users. They can capture data in digital forms on the web, through an intranet page, or smartphone application.
6. Digital signatures
This type of document verification is equal to a handwritten signature. Digital signatures work to authorise approvals and permissions of digital documents or emails. This method to capture data is used for workflows that involve parties from different companies or departments. Digital signatures are legal and bring high security for personal information.
7. Web scraping and monitoring
This tool helps to manage a large amount of web data. Also, web scraping tools are called web bots or crawlers (for example, Google spiders). They crawl through web pages and code to gather, analyse and recognise specific data. Web scraping is useful for capturing and monitoring various data types available on the Internet. There could be news, prices, contacts, updates, currencies, comments, and reviews.
8. Magnetic stripe cards
The cards differ in that they have magnetic stripes with encoded data. It can be decoded using digital reading devices. This method to capture data is safe and used in hotel access cards, transport cards, ID cards, and credit/debit cards combined with other security methods.
9. Magnetic ink character recognition (MICR)
This solution can recognise characters that are machine printed in a magnetic link. MICR is used in banks for processing checks for payments.
10. Smart cards
The solution holds encrypted data on a microprocessor chip for identification purposes. Companies can use smart cards for staff identification and chip-based smart cards for safe bank transactions.
11. Intelligent voice capture
This method to capture data uses speech recognition technology. It helps understand and analyse voice. It can provide voice access, create set reminders, and make music requests.
12. Intelligent video and image capture
The video and image capture technology is used to recognise and extract accurate information for data analysis, security check-ups at the airport, biometric identification, etc.
What are the reasons for usage?
Companies can automatically capture data to reduce human resources and dependency on managing large volumes of information manually. This technology also provides a smooth flow of data processing. It makes information prepared and available from any workflow.
Artificial intelligence integration shows the most significant results in data capture development. This technology can imitate human intelligence to provide cognitive data capture. AI collects data with high accuracy at the right time and place. It helps companies to optimise client services and provide a quick response.
What are the advantages of data capture?
Automated data capture provides noticeable benefits in improving and optimising document processing.
Reduces manual errors
Automated data capture allows you to reduce human presence in the performance of repeated and exhausting tasks. It reduces possible manual errors and improves efficiency.
Increases employees satisfaction
Automated solutions can let your staff reduce monotony workloads and focus on creative tasks developing satisfaction.
Lowers operational costs
Modern IT solutions help businesses eliminate extra operational costs on inventory, rent, and payroll. They update data in real-time and reduce any errors.
Improves security and data storage
Encryption of automated capture protects data from unauthorised access and helps use less disk space.
Provides 24/7 availability
IT solutions can capture data during non-working hours and without geographical restrictions. It is the most useful feature for healthcare, shipping, and hospitality sectors when data has to be available at any time to increase business efficiency.
Organises centralised access
Automated solutions provide controlled centralised access to all business data by using cloud storage as a final destination.
Boosts customer experience
When collected data have no errors, it helps improve better understanding of customers and business quality.
Simplify decision making
Automated solutions bring benefits to effective data capture. It helps provide big-data analysis for faster and more profitable decision-making.
Challenges of Data Capture Solutions with Automated Data Capture
| Manual Errors | Elimination of human errors in data entry and processing |
| Time-Consuming Processes | Accelerated data capture processes with real-time information. |
| High Labor Costs | Minimized manual labor leads to lower operational expenses. |
| Data Inaccuracy | Automated validation and verification of data. |
| Incomplete Data Capture | Captures comprehensive data sets consistently and efficiently. |
| Limited Scalability | Handles large volumes of data. |
| Delayed Decision-Making | Enables real-time data availability for fast decision-making |
| Compliance and Regulatory Issues | Automates compliance checks and ensures adherence to regulations. |
| Integration Challenges | Integrates with various systems and apps. |
| Data Security Risks | Implements secure data capture processes and encryption measures. |
Conclusion
After many decades of transformation, data capture technology has developed into a multi-industry field. Nowadays, it improves business effectiveness and profitability. This solution even makes employees more involved in daily work.
These days there exist many methods of data capture by various IT technologies. Depending on your business sector and goals, you can choose the most appropriate mix of tools to capture data. Even small and medium businesses managing large data volumes can notice the return of graipinvestments (ROI) by applying automated data capture solutions.
Among data capture providers, you can pay attention to the Graip.AI platform. It represents an AI assistant that combines the power of rules-based robotic process automation and self-learning artificial intelligence. For example, our clients can apply the following solutions: Sales Request Automation for sales tasks and Invoice Automation for accounting. The sales tool reduces document processing time by 85%, while the accounting solution provides 99% accurate invoice processing and speeds up the work with vendor invoices.