I just completed the first Economic Work Object (EWO) for "Manual Data Transfer Between Systems" — and the numbers are staggering:
💰 $28,500 per employee annually — that's what US companies lose on manual data transfer
⏱️ 2 hours per day — average time employees spend copy-pasting between systems
📊 137,000+ job postings worldwide — require manual data entry skills right now
🤖 50-90% reduction — what RPA automation delivers predictably
This isn't anecdotal. This is based on 27 verified sources: enterprise case studies (NHS, JLL), industry reports, Stack Overflow discussions, and real job postings.
We're building the world's first open ontology of repetitive human labor — a graph database that maps every repeatable work pattern to its economic cost and automation potential.
Why this matters:
- For CFOs: Calculate your exact exposure to manual work
- For Operations: Identify which processes to automate first
- For RPA vendors: Understand real customer pain points with evidence
- For researchers: Access structured data on work patterns
I'm looking for 5-7 experts to validate this first EWO:
→ CFOs / Financial Controllers
→ Operations Managers
→ HR Directors
→ RPA Consultants
→ Data Engineers / SREs
If you work with repetitive manual processes and want to see if our data matches your reality – fill out this 3-minute form:
https://forms.gle/hmAoNKEABUxmxYBP8
This is just the first of hundreds of work objects we'll map. The goal: make invisible toil visible, measurable, and automatable.
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