A global cosmetics manufacturer and distributor, managing a complex portfolio across multiple markets, was experiencing growing operational inefficiencies within its supply chain processes:

• High manual workload on order processing, invoice reconciliation, and stock status updates.
• Repetitive tasks consuming valuable time from planning, procurement, and logistics teams.
• Increased risk of human error and inconsistent data handling.
• Limited reactivity and flexibility in managing volume peaks, especially during product launches and seasonal campaigns.

The leadership sought to leverage automation to streamline processes, reduce operational costs, and increase reliability.

CoreChain conducted an end-to-end process assessment to identify automation opportunities with the highest ROI.

Data collected and analyzed:

• Time and effort spent per process and task (process time mapping).
• Error rates and rework levels in manual data entries.
• Process variability and exceptions handling frequency.
• Volumes and frequency of recurring activities.

• Lean process mapping and waste identification (non-value-added activities).
• RPA opportunity assessment matrix (effort vs. impact).
• Business case modeling (savings estimation, payback period calculation).
• Risk analysis on process automation feasibility and criticality.

CoreChain recommended the deployment of Robotic Process Automation (RPA) on a selection of high-volume, rules-based activities, including:

• Automated PO creation and update from procurement planning outputs.
• Supplier invoice matching and reconciliation against purchase orders and delivery notes.
• Automated inventory status reporting and alerts for stockout risks.
• Standardized data extraction and integration across ERP and planning tools.

Key recommendations:

• Prioritization of RPA on stable, mature processes to maximize success rate.
• Definition of exception management rules and manual fallback processes.
• Selection of RPA software solution aligned with the client’s IT ecosystem.

• Phase 1:

Proof of Concept (PoC) on two pilot processes.

• Phase 2:

Scaling up to the full process scope, based on success metrics from PoC.

• Phase 3:

Establishment of a Center of Excellence (CoE) for automation governance and continuous improvement.

Delivered tools and enablers:

• Process documentation and RPA bot design specifications.
• Exception handling playbooks.
• KPI dashboards for bot performance monitoring.
• Training and knowledge transfer to process owners and IT teams.

• Reduction of manual workload by 40% on automated processes.
• Near-zero error rates on automated data handling.
• ROI achieved within 9 months on initial automation scope.
• Improved agility to absorb workload peaks without increasing headcount.
• Increased employee engagement by refocusing teams on higher-value-added activities.