When it comes to managing road networks, the real challenge isn’t just understanding the condition of assets today, it’s forecasting what they’ll look like tomorrow and beyond.
Budgets are tight, assets are aging and expectations from road users keep rising. For local authorities and national highways, making smart, data-driven investment choices means looking ahead, and that’s where deterioration modelling comes in.
Within iROADS, deterioration models do more than forecast the future. They empower asset managers to explore ‘what-if’ scenarios, test different funding strategies and plan interventions that keep networks performing well for years to come.
The Power of Deterioration Modelling
Every road, bridge and pavement follows its own pattern of wear and decay. Factors like construction type, material quality, traffic loading and even local climate all influence how quickly assets deteriorate.
IROADS integrates condition surveys (SCANNER and PAS 2161 format data), construction data, maintenance history and traffic information into a single data repository – creating a reliable foundation for accurate forecasting.
Using this data, deterioration modelling forecasts how asset condition will change over time. By combining current condition with deterioration trends, authorities can forecast:
- How the network will perform over the next 1, 5, 10 or 20 years
- Which assets are likely to fail first
- What level of investment is needed to maintain or improve condition
This level of forecasting allows authorities to see the difference between reacting to problems and strategically preventing them.
Testing “What-If” Scenarios
Forecasting isn’t just about predicting decline, it’s about understanding the impact of choices.
By running what-if scenarios, authorities can test different maintenance and funding strategies before committing resources. For example:
- What happens to overall network condition if budgets are reduced by 10%?
- How would increasing resurfacing treatments affect long-term performance?
- What’s the cost of deferring certain interventions to later years?
Scenario analysis provides the ability to compare different investment approaches side by side, helping authorities find the balance between cost, performance and risk.
These insights turn complex data into a clear story: how today’s decisions shape tomorrow’s network.
Cross-Asset Prioritisation: Seeing the Bigger Picture
Local authorities manage a wide range of assets, from carriageways and pavements to bridges, lighting and drainage. Each has competing needs and different rates of deterioration.
Cross-asset prioritisation brings all of this information together. By analysing performance, cost and risk across multiple asset types, authorities can determine where every pound of investment will deliver the greatest network-wide benefit.
This approach allows asset managers to:
- Compare needs across asset categories on a consistent basis
- Target interventions for the highest return on investment
- Support fair, transparent budget allocation decisions
- Demonstrate value and justify funding with clear evidence
- It’s holistic decision making, backed by data and research by TRL over the decades.
Driving Better Decisions and Funding Outcomes
Forecast modelling and cross-asset prioritisation doesn’t just improve planning, they strengthen funding cases too.
As the Department for Transport continues to link incentive funding to evidence of effect asset management, authorities using robust modelling and scenario analysis are better positioned to:
- Demonstrate data-driven decision-making
- Justify investment strategies
- Support submissions for full funding uplifts
By turning data into insight, Local Authorities can show that investment plans are not only efficient but strategically aligned with national asset management objectives.
Looking Ahead
To plan with confidence, forecasting, scenario testing and cross-asset prioritisation need to be part of everyday practice.
iROADS makes that simple by turning your data into clear, defensible decisions:
- Bring data together: SCANNER, PAS2161 format data, inspections, works history, traffic – all in one place
- Forecast accurately: calibrated deterioration models for local conditions
- Test options fast: compare funding and treatment scenarios side by side
- Prioritise wisely: spend where risk and impact are highest
- Evidence funding cases: clear outputs to support DfT incentive funding
- Keep improving: plans update as new data comes in
iROADS helps you automate the hard work so you can focus on delivery.
You are not just managing the network; you are shaping its future.
