How CMCC Foundation Uses Make to Cut HR Errors 65% and Speed Purchasing 85%
CMCC Foundation automated fragmented data workflows across MongoDB, SAP, and Monday.com using Make, cutting HR data entry errors by 65% and purchase request time by 85% during a major reorganization.
Impact
65%
HR data entry error reduction
50%
HR-related email traffic reduction
85%
Purchase request entry speed improvement
78%
Purchasing data entry error reduction
60%
Reduction in status-check calls
50% less
Time identifying workflow dependencies
Challenge
A major reorganization exposed fragile manual workflows across disconnected systems, with no visibility into how changes in one area would cascade through 250+ interdependent processes.
Solution
Deployed Make to automate data flows across MongoDB, JotForm, SAP S/4HANA, and Monday.com, with Make Grid providing visual dependency mapping across all scenarios.
Tools & Technologies
What Leaders Say
“Make brought flexibility, a user-friendly no-code interface, and outstanding support, significantly expanding what we can do.”
“Make Grid shows us which workflows are affected when something changes...checking 250+ scenarios manually would take days.”
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Full Story
CMCC Foundation, a European climate research nonprofit, faced a critical challenge during its 2024 reorganization: data silos across MongoDB, JotForm, SAP S/4HANA, and Monday.com created fragile, interdependent workflows managed manually through Excel and email. Changes in one department risked breaking processes elsewhere with no visibility.
The IT team deployed Make's automation platform to unify data flows across all systems. Automations captured inputs from JotForm, routed them through MongoDB, triggered SAP procurement workflows, and updated Monday.com boards — all without manual intervention.
To manage the complexity of 250+ interconnected scenarios, they adopted Make Grid, a visual dependency mapper that shows which workflows are affected before any change is made. What would have taken days of manual review now takes minutes.
Results were immediate: HR data entry errors dropped 65%, HR-related email traffic fell 50%, purchase request entries became 85% faster, purchasing errors fell 78%, status-check calls dropped 60%, and time identifying workflow dependencies halved.