Data Entry

Data entry is the work of turning source material such as paper forms, PDFs, emails, images or voice files into structured digital records inside a database or business system, so the teams downstream can report and act on numbers they trust.

Good data entry is invisible. Bad data entry shows up as duplicate customer records, wrong invoice totals and dashboards nobody trusts.

Harvard Business Review’s 2017 study on data quality found only 3% of company data met basic quality standards.

That finding still shapes how buyers scope the work. It’s also why accuracy clauses — not speed clauses — carry the weight in a data entry contract.

The job ranges from one temp typing addresses into a CRM to a 200-seat offshore floor keying insurance claims under a tight service level agreement.

The economics are what push most mid-market firms offshore. Entry-level operators in Manila or Cebu cost 60% to 75% below onshore rates, and accuracy on a well-scoped queue typically clears 98%.

Key takeaways

• Data entry converts unstructured source material into structured records that downstream systems can query.
• Accuracy, not raw speed, is the metric that matters; the industry benchmark is 98% or better on double-keyed work.
• Philippines outsourced rates sit at USD 5 to USD 9 per hour in 2026, against USD 18 to USD 25 onshore.
• Optical character recognition (OCR) and robotic process automation (RPA) now absorb the repetitive layer, so people work the exceptions.
• Regulated records stay in-house unless the provider signs the agreement that covers them.

How it works

Data entry runs as a four-step loop: capture, key, validate, load. Source documents arrive as scans, PDFs, forms or voice files; operators key the fields into a template; a rules engine checks them; the clean record lands in the system of record.

OCR lifts printed text off a scan, bots move validated records between applications, and operators handle only the exceptions the bots reject.

Deloitte’s 2020 intelligent-automation survey found 78% of organisations were already deploying RPA. Pure manual keying is now the exception — most queues read first and key second.

Quality gets measured two ways. Character accuracy tracks keystroke errors per 10,000 characters. Field accuracy tracks how many complete records pass validation. Contracts usually target 99.95% character and 98% field accuracy.

Double-keying is the mechanism behind those numbers. Two operators key the same critical fields blind, the system compares them, and only the disagreements reach a reviewer.

Pricing benchmark (2026)

Rates move with volume, document quality and turnaround.

The Philippines holds the deepest labour pool for this work.

The IT and Business Process Association of the Philippines (IBPAP) publishes headline figures for the country’s information technology and business process management (IT-BPM) sector: 1.9 million workers and USD 40 billion in revenue.

A large slice of that is back-office keying — the tier this page describes.

Examples

Data entry deployments cluster where document volume is high and judgment is low: insurance claims, product catalogues, legal discovery and survey capture. The four dated queues below, from 2024 to 2026, illustrate the pattern.

Insurance claims processing. A US health insurer ships 20,000 daily claim forms to a Cebu team. OCR pre-fills 70% of the fields; operators key the rest and clear mismatches inside a shared queue. Handwritten adjuster notes are the slow part, not the volume.

E-commerce catalogue upload. A Shopify merchant hands 4,000 SKUs (title, description, weight, HS code and images) to a Manila provider. Turnaround runs 96 hours at USD 0.35 per SKU. Per-SKU pricing works here because the field set never changes.

Legal document indexing. A Chicago law firm keys 12,000 pages of discovery into a case-management platform, tagged by date, party and privilege. Two-shift coverage lands a five-day close. Privilege calls stay with the firm’s own paralegals.

Field research capture. A market research agency turns 8,000 handwritten survey cards from a Jakarta shopping mall into a clean SPSS dataset inside a week. Handwriting is why this queue never went to OCR alone.

A fifth pattern shows up in almost every finance back office. Supplier invoices run through OCR first, and only the lines the reader can’t resolve reach an operator.

That operator keys vendor, date, tax code and line total. The exception rate drives the price here, not the page count.

The global business process outsourcing market, of which data entry is a foundational slice, reached roughly USD 347.95 billion in 2025, per Precedence Research.

Related terms

Data entry sits near the bottom of a stack of service lines. The terms below mark its boundaries: what happens to records after keying, which tier handles the judgment work, and which delivery models set the price you pay.

• Back Office: the non-client-facing operations layer where most data entry sits.
• Business Process Outsourcing (BPO): the delivery model that carries data entry as an entry-level service line.
• Data Processing: the downstream step that turns keyed records into usable outputs.
• Knowledge Process Outsourcing: the higher-judgment tier that sits one rung above data entry.
• Transcription: the audio to text sibling service, run on the same accuracy and QA workflow.
• Offshoring: the delivery model that unlocks Philippines and India pricing.

FAQ

Buyers ask the same six questions before they sign: what accuracy to demand, what the work costs in 2026, how far OCR gets them, what has to stay in-house, where data entry stops, and how long a new provider takes to go live.

What’s the accuracy standard for outsourced data entry?

Contracts typically require 98% field accuracy and 99.95% character accuracy. Providers hit that with double-keying, where two operators enter the same record and a rules engine flags every mismatch for review.

How much does outsourced data entry cost in 2026?

Philippines rates run USD 5 to USD 9 per hour, India USD 4 to USD 8, and onshore US operators USD 18 to USD 25. Volume pricing, per 1,000 records or per document, is common on OCR-heavy queues.

Can OCR replace human data entry?

Not entirely. OCR handles clean printed text well, but handwriting, low-resolution scans and non-standard layouts still need a person. Most queues now read with OCR first and route only the exceptions to operators.

What tasks should stay in-house?

Anything touching regulated data, such as protected health information or attorney-client material, without a signed business associate agreement. Everything else, from catalogues to order forms and invoice indexing, is safe to send to a vetted provider.

How is data entry different from data processing?

Data entry is the capture step: getting information from a source into a system. Data processing is what happens next: sorting, calculating, formatting and reporting on the records you captured.

How fast can a new provider be live?

A pilot queue of 500 to 2,000 records usually launches inside three weeks, while full production on a 20-seat team tends to clear the eight-week mark once security, VPN access and QA sampling are agreed.

Ready to shortlist providers? Browse the OA BPO directory to compare vetted data entry teams by price, capacity and specialism.