Data-driven decision engine that models whether to refurbish or replace an asset based on current condition, repair cost history, embodied carbon, and remaining useful life. Eliminates guesswork and ensures the most sustainable and cost-effective outcome every time.
Process Steps
Assess Condition
Pull asset condition score, repair history, and age from the registry.
Model Scenarios
Engine compares refurb cost, replacement cost, carbon impact, and remaining life.
Recommend Action
System presents recommendation with financial and carbon justification.
Execute Decision
Route asset to refurbishment workflow or procurement with full audit trail.
System Flow
Key Features
Cost Comparison
Side-by-side total cost of ownership analysis for refurb vs replace options.
Carbon Modelling
Calculate embodied carbon saved through refurbishment vs new manufacture.
Remaining Life Prediction
Estimate extended useful life after refurbishment based on condition data.
Decision Audit Trail
Full record of every refurb/replace decision with supporting data.
Application Screens
Asset Assessment
View condition, history, and carbon data for the asset
Scenario Comparison
Side-by-side refurb vs replace cost and carbon analysis
Recommendation Detail
System recommendation with supporting justification
Decision Log
Historical record of all lifecycle decisions
Benefits
- Eliminates subjective refurb/replace decisions
- Quantified carbon savings per decision
- Reduced total cost of ownership
- Defensible ESG reporting data