MFG-ENERGY-1 · Head of Manufacturing · Energy Optimization
Energy & Emissions Intelligence
Energy / unit
80index
from 100 index
Scope 1+2 emissions
70index
from 100 index
Problem & Capability
What & howExecutive problem
Energy use is opaque across hundreds of lines globally.
Capability
AI identifies excessive energy use, inefficient cycles and emissions hotspots.
Outcome & Strategic Impact
Why it mattersBusiness outcome
Lower energy bill, lower emissions.
Strategic impact
Supports 2030 sustainability commitments.
KPI trajectory · Baseline → Target
ExhibitAI explainability — drivers, risks, next 90 days
Deploying AI-driven energy and emissions intelligence will deliver measurable reductions in energy costs and carbon footprint across our global manufacturing footprint, directly supporting Avery Dennison’s 2030 sustainability commitments. This initiative targets a 20% reduction in energy per unit and a 30% reduction in Scope 1+2 emissions, strengthening our category leadership and valuation expansion through operational excellence.
Drivers
- AI-enabled visibility pinpoints inefficiencies and emissions hotspots across all lines
- Automated recommendations drive rapid, repeatable process improvements
- Alignment with customer and investor sustainability expectations enhances market differentiation
Risks
- Data quality and integration gaps may limit actionable insights
- Change management challenges could slow plant-floor adoption
- Energy savings may be offset by production mix or external energy price volatility (assumption)
Next 90 days
- Select three representative plants for pilot implementation and baseline measurement
- Integrate AI analytics with existing energy metering and atma.io data streams
- Establish cross-functional task force to drive adoption and monitor KPI progress