AgricultureOperations

How Syngenta Uses Celonis to Prevent 4,200+ Production Stops and Unlock Cash

Syngenta, a global agriculture leader headquartered in Switzerland and operating in 100+ countries, deployed the Celonis Process Intelligence Platform to bring AI-powered transparency to master data management and Order-to-Cash operations. By connecting data across its SAP systems and applying intelligent automation through Celonis Action Flows, Syngenta’s team prevented over 4,200 production stops in ten months, freed millions in working capital, and eliminated 102,000 hours of manual rework — with the solution now live across 20+ processes.

Outcomes

2,100+Production stops prevented (3 months)
4,200+Production stops prevented (10 months)
Millions (USD)Working capital freed
30,000Hours saved from MDM rework
72,000Hours saved from OTC automation
102,000Total hours saved
148 days averageOrder-to-Cash cycle time reduction (Poland)
20+Processes optimized with Celonis

Tools & Technologies

1CP
Celonis Process Intelligence Platform
Process mining platform that extracts and visualizes end-to-end process flows from enterprise system event logs.

AI Categories

Challenge

Syngenta’s production operations were routinely disrupted by master data quality issues — missing SAP fields, duplicated records, unsynchronized materials — that the MDM team had no efficient way to detect before they halted production runs, with data scattered across systems, emails, and spreadsheets and no unified view of where problems were forming.

Solution

Syngenta deployed the Celonis Process Intelligence Platform to create an end-to-end digital twin of its production and Order-to-Cash processes, using Celonis Action Flows to automatically surface master data errors, recommend corrective actions, and drive automation across 40+ countries — preventing production stops before they occur and reducing manual rework at scale.

Full Story

Syngenta operates at the intersection of chemistry, biology, and agriculture, developing crop protection products and seeds for farmers across more than 100 countries. The company’s scale is a competitive advantage, but it also generates operational complexity that compounds with growth: more countries, more subsidiaries, more systems, and more opportunities for data inconsistencies to cascade into production failures.

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