Workflow Transformation
Doles Foods - Workflow AI Transformation
AI transformation of a critical treasury workflow.
Year :
2025-2026
Industry :
Food & Logistics
Client :
Dole Foods PLC
Project Duration :
12 Months
Problem :
Fragmented data across acquired systems left Dole unable to track or fight invoice deductions — manual review by 100-150 FTEs couldn't keep pace with the volume, so most disputes went unchallenged, leaking an estimated $100M per year in recoverable revenue.
Solution :
Data foundation
Unified fragmented systems (D365 F&O regional instances, Dynamics/SI Foodware, Sage 200, legacy JD Edwards/IBM mainframe) into Microsoft Fabric OneLake
Used mirroring + shortcuts — no full migration required
Multi-agent orchestration
Case Builder — assembles documentation for each deduction
Review — evaluates validity against governed rules, assigns confidence score
Dispute — drafts and files challenges before retailer windows close
Learning — feeds human corrections back permanently, no more tribal knowledge
Orchestrator — sequences the workflow, owns audit trail, applies consequence logic, routes only ambiguous/high-stakes cases to humans
Scaled beyond deductions
Same control-tower pattern extended across EDI invoicing, factoring, multi-currency sweeping, Dublin netting/FX
Each function has its own orchestrator, under joint human-AI governance
Challenges :
Fragmented, non-integrated data — regional D365 instances, specialty systems, legacy mainframe, and shadow spreadsheets with no connection between them
Perishability penalty — can't pause or repossess spoiling product, no leverage in disputes
Deduction complexity at scale — inspection-driven price changes, fuel/quality adjustments, frequent mismatches made valid vs. invalid indistinguishable at volume
Tribal knowledge risk — dispute judgment lived in individual collectors' memory and personal spreadsheets, lost when they left
Liquidity dependence — 60-90 day payment terms forced reliance on factoring at a discount just to get cash
Multi-currency/FX complexity — netting, intercompany flows, hedging governance across regions
Localized cash trapping — capital controls kept cash stuck in-country, limiting visibility and central treasury control
Summary :
Summary
Dole's acquisition-driven growth left treasury and cash collection running on fragmented, disconnected systems. Deductions worth 1.3% of invoice value went largely unchallenged — a ~$100M/year leak — because manual review by 100-150 FTEs couldn't keep pace with volume, complexity, and perishable-goods pressure. A unified data layer (Fabric OneLake) plus a multi-agent orchestration system turned deduction handling from reactive, memory-dependent guesswork into a governed, evidence-based process.
Outcome
Headcount on manual matching/review cut from ~100 FTE to ~25, refocused on judgment calls only
Every deduction now classified and disputed before retailer windows close, vs. most going unchallenged before
Evidence-based, confidence-scored classification replaces inconsistent human judgment
Clean cases close automatically; only real exceptions reach a human
Corrections become governed rules via the Learning Agent — institutional knowledge no longer walks out the door
Pattern extended treasury-wide (EDI invoicing, factoring, FX, netting) under a single Treasury Control Tower with joint human-AI governance
More Projects
Workflow Transformation
Doles Foods - Workflow AI Transformation
AI transformation of a critical treasury workflow.
Year :
2025-2026
Industry :
Food & Logistics
Client :
Dole Foods PLC
Project Duration :
12 Months
Problem :
Fragmented data across acquired systems left Dole unable to track or fight invoice deductions — manual review by 100-150 FTEs couldn't keep pace with the volume, so most disputes went unchallenged, leaking an estimated $100M per year in recoverable revenue.
Solution :
Data foundation
Unified fragmented systems (D365 F&O regional instances, Dynamics/SI Foodware, Sage 200, legacy JD Edwards/IBM mainframe) into Microsoft Fabric OneLake
Used mirroring + shortcuts — no full migration required
Multi-agent orchestration
Case Builder — assembles documentation for each deduction
Review — evaluates validity against governed rules, assigns confidence score
Dispute — drafts and files challenges before retailer windows close
Learning — feeds human corrections back permanently, no more tribal knowledge
Orchestrator — sequences the workflow, owns audit trail, applies consequence logic, routes only ambiguous/high-stakes cases to humans
Scaled beyond deductions
Same control-tower pattern extended across EDI invoicing, factoring, multi-currency sweeping, Dublin netting/FX
Each function has its own orchestrator, under joint human-AI governance
Challenges :
Fragmented, non-integrated data — regional D365 instances, specialty systems, legacy mainframe, and shadow spreadsheets with no connection between them
Perishability penalty — can't pause or repossess spoiling product, no leverage in disputes
Deduction complexity at scale — inspection-driven price changes, fuel/quality adjustments, frequent mismatches made valid vs. invalid indistinguishable at volume
Tribal knowledge risk — dispute judgment lived in individual collectors' memory and personal spreadsheets, lost when they left
Liquidity dependence — 60-90 day payment terms forced reliance on factoring at a discount just to get cash
Multi-currency/FX complexity — netting, intercompany flows, hedging governance across regions
Localized cash trapping — capital controls kept cash stuck in-country, limiting visibility and central treasury control
Summary :
Summary
Dole's acquisition-driven growth left treasury and cash collection running on fragmented, disconnected systems. Deductions worth 1.3% of invoice value went largely unchallenged — a ~$100M/year leak — because manual review by 100-150 FTEs couldn't keep pace with volume, complexity, and perishable-goods pressure. A unified data layer (Fabric OneLake) plus a multi-agent orchestration system turned deduction handling from reactive, memory-dependent guesswork into a governed, evidence-based process.
Outcome
Headcount on manual matching/review cut from ~100 FTE to ~25, refocused on judgment calls only
Every deduction now classified and disputed before retailer windows close, vs. most going unchallenged before
Evidence-based, confidence-scored classification replaces inconsistent human judgment
Clean cases close automatically; only real exceptions reach a human
Corrections become governed rules via the Learning Agent — institutional knowledge no longer walks out the door
Pattern extended treasury-wide (EDI invoicing, factoring, FX, netting) under a single Treasury Control Tower with joint human-AI governance
More Projects
Workflow Transformation
Doles Foods - Workflow AI Transformation
AI transformation of a critical treasury workflow.
Year :
2025-2026
Industry :
Food & Logistics
Client :
Dole Foods PLC
Project Duration :
12 Months
Problem :
Fragmented data across acquired systems left Dole unable to track or fight invoice deductions — manual review by 100-150 FTEs couldn't keep pace with the volume, so most disputes went unchallenged, leaking an estimated $100M per year in recoverable revenue.
Solution :
Data foundation
Unified fragmented systems (D365 F&O regional instances, Dynamics/SI Foodware, Sage 200, legacy JD Edwards/IBM mainframe) into Microsoft Fabric OneLake
Used mirroring + shortcuts — no full migration required
Multi-agent orchestration
Case Builder — assembles documentation for each deduction
Review — evaluates validity against governed rules, assigns confidence score
Dispute — drafts and files challenges before retailer windows close
Learning — feeds human corrections back permanently, no more tribal knowledge
Orchestrator — sequences the workflow, owns audit trail, applies consequence logic, routes only ambiguous/high-stakes cases to humans
Scaled beyond deductions
Same control-tower pattern extended across EDI invoicing, factoring, multi-currency sweeping, Dublin netting/FX
Each function has its own orchestrator, under joint human-AI governance
Challenges :
Fragmented, non-integrated data — regional D365 instances, specialty systems, legacy mainframe, and shadow spreadsheets with no connection between them
Perishability penalty — can't pause or repossess spoiling product, no leverage in disputes
Deduction complexity at scale — inspection-driven price changes, fuel/quality adjustments, frequent mismatches made valid vs. invalid indistinguishable at volume
Tribal knowledge risk — dispute judgment lived in individual collectors' memory and personal spreadsheets, lost when they left
Liquidity dependence — 60-90 day payment terms forced reliance on factoring at a discount just to get cash
Multi-currency/FX complexity — netting, intercompany flows, hedging governance across regions
Localized cash trapping — capital controls kept cash stuck in-country, limiting visibility and central treasury control
Summary :
Summary
Dole's acquisition-driven growth left treasury and cash collection running on fragmented, disconnected systems. Deductions worth 1.3% of invoice value went largely unchallenged — a ~$100M/year leak — because manual review by 100-150 FTEs couldn't keep pace with volume, complexity, and perishable-goods pressure. A unified data layer (Fabric OneLake) plus a multi-agent orchestration system turned deduction handling from reactive, memory-dependent guesswork into a governed, evidence-based process.
Outcome
Headcount on manual matching/review cut from ~100 FTE to ~25, refocused on judgment calls only
Every deduction now classified and disputed before retailer windows close, vs. most going unchallenged before
Evidence-based, confidence-scored classification replaces inconsistent human judgment
Clean cases close automatically; only real exceptions reach a human
Corrections become governed rules via the Learning Agent — institutional knowledge no longer walks out the door
Pattern extended treasury-wide (EDI invoicing, factoring, FX, netting) under a single Treasury Control Tower with joint human-AI governance