Why automate data entry?
Other downsides of manual data entry include:
- Employee burnout from repetitive tasks.
- Slow processing times for invoices, forms and customer data.
- Compliance risks caused by human error which include privacy violations and missing or incomplete documentation.
- Limited scalability when the document volume increases.
Key benefits of automated data entry
According to a 2023 Deloitte report on the state of software quality that surveyed over 3,000 quality assurance teams, 79% of organizations that automate experienced a positive ROI within the first year.
Automation increases data quality and contributes to ROI by offering:
- Speed: Process documents in seconds, not hours.
- Accuracy: Eliminate manual errors.
- Efficiency: Free employees to focus on strategic work.
- Scalability: Handle spikes in document processing volume without hiring more staff.
- Compliance support: Ensure data privacy with permission-based access and confirm data integrity with audit trails. In addition, you’ll never lose a document again.
Below are examples of how your company will experience these advantages across every team and department. We’ll also explore industry-specific applications.
Use cases within your company
Finance and accounting
- Automates invoice processing, expense reports, and purchase orders.
- Matches data with accounting software (e.g., QuickBooks, SAP, NetSuite).
- Reduces time to close monthly books.
- Improves accuracy in financial reporting and audits.
Human resources
- Streamlines employee onboarding paperwork.
- Digitizes resumes, applications and benefits forms.
- Maintains organized, searchable personnel files.
- Ensures compliance with labor regulations through automated documentation.
Customer service
- Extracts and routes information from customer emails and web forms.
- Triggers workflows for support tickets, returns or customer inquiries.
- Improves response times and record-keeping.
- Enhances customer satisfaction with faster issue resolution.
IT and data governance
- Maintains data integrity across systems by reducing data discrepancies.
- Streamlines database updates, system migrations and API integrations.
- Enables advanced analytics through faster access to clean data.
- Supports compliance initiatives by adhering to consistent documentation protocols.
Use cases by industry
Healthcare
- Converts patient records into a digital format.
- Gathers information from medical documents to improve patient record handling and billing.
- Automatically pulls out and sorts patient information from notes, test results, and insurance documents.
- Cuts down on administrative work and reduces errors.
Legal firms
- Retrieves essential data and transforms it into metadata to improve search capabilities.
- Simplifies e-discovery by identifying and sorting documents containing crucial information.
- Boosts the efficiency of client services by speeding up document-heavy workflows.
Logistics and operations
- Captures data from bills of lading, delivery slips and customs forms.
- Keeps inventory and shipping systems up to date.
- Tracks documents in real time across multiple locations.
- Improves forecasting and supply chain visibility.
How it works: step-by-step
Let’s say your accounts payable department receives hundreds of invoices every month. Here’s how AI-driven intelligent document processing would handle that process:
-
- Capture: The system ingests documents from email, scanners, watched folders and other sources.
- Recognize: OCR reads the content.
- Classify: AI determines the document type (e.g., invoice, receipt).
- Extract: Key data fields like vendor name, date, invoice number, and total amount are pulled from the document.
- Validate: Business rules check for missing data or other discrepancies.
- Route: The system sends the document to the right employee, kicks off a workflow or directly to your ERP or other business software.
- Store: A secure digital copy is archived with full searchability and audit trails.
This entire process can take seconds and requires zero manual effort. Most importantly, it scales. Once implemented, the same system can be configured to handle a wide range of documents and kick-off workflows — for everything from HR forms to customer contracts.
In more complex use cases, intelligent data extraction can recognize multilingual documents, read handwriting, and even identify sentiment in customer feedback. This expands automation potential beyond standard form processing to move the needle in terms of digital transformation and process innovation.
And since these systems “learn” from corrections and decisions over time, companies often see continued results and efficiencies well after the initial improvements in performance.
How to get started: A practical guide
Start by breaking the process into manageable steps. The following practical guide outlines how companies can implement automation efficiently and with minimal disruption.
Audit current workflows
- Identify processes with high document volume and repetitive input.
- Examples: Invoice processing, employee onboarding and contract management.
- Choose the right tool
- Look for a combination of features including deep OCR, AI, machine learning and workflow automation.
- Check for easy integration with your existing systems (ERP, CRM, HRIS and accounting software for example).
- Evaluate vendors on support, compliance, scalability and total cost of ownership.
Digitize paper documents
- Use scanners and mobile capture apps.
- Establish centralized intake folders on a shared drive or designated inbox.
- Create naming conventions and filing standards.
Define business rules
- Determine how data should be validated, routed, or escalated. Example: invoices over $10,000 require a second approval.
- Align rules with compliance needs and company policies.
- Pilot with one process
Start small
- Pick a single workflow like invoice capture or entering contract terms and renewal dates.
- Measure speed, error rates and employee feedback.
- Use the pilot to refine your configuration before full rollout.
Train employees
- Offer short sessions or tutorials.
- Emphasize that automation is there to support — not replace — them.
- Appoint champions in each department to drive adoption.
Scale up gradually
- Expand automation to other departments or document types.
- Adjust rules as needed and monitor system performance.
- Set measurable KPIs to track ongoing success.
Real-world case study: HVVG Medical Group
HVVG Medical Group, a large healthcare provider with 24 facilities across Germany, transformed its invoice processing by implementing DocuWare Intelligent Document Processing. Before automation, their staff manually entered every invoice into accounting systems, a time-consuming process prone to human error.
HVVG was able to drastically reduce processing times, accelerate approvals, and minimize errors, all while boosting employee morale by removing repetitive tasks. The system automatically captures, indexes, and routes invoices, allowing staff to focus on higher-value work.
Key benefits HVVG experienced include:
Faster invoice turnaround, enabling quicker payments and improved vendor relationships
Significant reduction in data entry errors, improving financial accuracy and compliance
Increased employee satisfaction due to reduced manual workload and streamlined workflows
How to choose a data entry automation platform
Selecting the right automation platform is crucial to ensure a smooth implementation and to lock in long-term success. Focus on key factors that will align with your company’s technical capabilities and business goals.
When evaluating solutions, consider:
Ease of use: Will non-technical users be comfortable with it?
Integration: Does it connect with your existing ERP, CRM or HR systems?
Scalability: Can it grow with your needs?
Support: Is onboarding and training included?
Security: Does it meet your company’s security standards and compliance requirements?
How can I minimize business disruption?
Automating data entry on a day-forward basis and digitizing other document types in order of priority is one commonly used approach. In addition, develop a plan for user adoption and provide training in advance.
Does using automated data entry violate data privacy laws or other compliance requirements?
Automation enforces data privacy by limiting access to authorized employees both during the process and when documents are digitized. In contrast, paper documents can be viewed by anyone who walks by the desk of staff members entering data. It also enforces retention schedules so that documents are kept or deleted according to your business rules
How can I be sure my company’s data is secure?
Automated data entry tools typically use API-based or secure file transfer methods, meaning there is no exposure of sensitive data. They also safeguard data by encrypting data, preventing unauthorized access and performing regular security audits.
Will the automation solution be compatible with my other business software?
The solution you choose should use REST-based platform services and APIs to enable data exchange with your other business software. This allows data transfers between systems, no matter what the device type or operating system is.
Why is it time to automate now?
With today’s cloud-based platforms, small and mid-sized organizations can compete with larger firms without adding headcount. Smaller departments or companies with lean teams can especially benefit, as automation levels the playing field, allowing them to compete more effectively.
If you’re not exploring automated data entry, we hope we've convinced you that it’s time to learn more. Automation not only reduces costs, processing time and errors but also enhances data quality, supports compliance and increases overall operational efficiency.
DocuWare offers state-of-the-art automation options that don’t require extensive IT resources or large upfront investments. By starting with focused workflows, companies can prove value quickly and scale their automation efforts over time, improving productivity and employee satisfaction along the way.