COO-TOWER-1 · COO · AI-Driven Supply Chain Control Tower
Control Tower
On-time-in-full
98%
from 92 %
Mean time to mitigate disruption
6hours
from 36 hours
Problem & Capability
What & howExecutive problem
Decisions wait for spreadsheets and end-of-day batches.
Capability
AI predicts delays, shortages, fulfillment disruption and transportation bottlenecks.
Outcome & Strategic Impact
Why it mattersBusiness outcome
Faster operational decisions; fewer surprises.
Strategic impact
Operational resilience as competitive advantage.
KPI trajectory · Baseline → Target
ExhibitAI explainability — drivers, risks, next 90 days
Deploying an AI-enabled Control Tower will materially improve operational resilience by enabling real-time, predictive decision-making across manufacturing and supply chain. This will drive measurable gains in on-time-in-full delivery (from 92% to 98%) and sharply reduce disruption mitigation time (from 36 to 6 hours), strengthening Avery Dennison’s competitive position. The initiative supports our ambition to set the industry standard for operational reliability and responsiveness.
Drivers
- AI-driven early detection of supply and fulfillment risks
- Unified, real-time data visibility across plants and logistics
- Automated, prioritized mitigation recommendations for faster response
Risks
- Data integration gaps across legacy systems
- Change management resistance at plant and logistics levels
- AI model accuracy and trust in early deployment phase
Next 90 days
- Select two pilot sites (assumption: North America and EMEA) for Control Tower rollout
- Establish cross-functional rapid response team for data integration and process mapping
- Define and baseline KPIs; initiate weekly executive review of pilot progress