Forecast and Backcast Resilience

See how your network will perform in any scenario and prove which upgrades actually improve reliability.

Forecast how every asset in your network will respond to heat waves, hurricanes, hail storms, and everyday loading. Pinpoint the upgrades that move the needle at the individual asset level, then backcast performance to show exactly how those changes improve reliability. Let the model handle the calculations so you can explore every scenario and build fast, defensible consensus for your plan.

Simulate how severe weather and operating conditions will impact your assets so you see where your network is most vulnerable and can prioritize the right upgrades.
Quantify resilience improvements at the individual asset level using metrics such as pole lean and cable clash rates, and connect them to system outcomes like SAIDI and SAIFI.
Automate ROI analyses across pre and post improvement states by backcasting upgrade impacts so you can forecast, deliver, and measure resilience gains and validate key decisions.

How do you turn any scenario into a recovery strategy?

Generate a fast recovery strategy for any scenario

Turn any scenario into a clear recovery roadmap on short notice. Bring dangerous conditions into your digital network model before they arrive in the field so you can see which poles, conductors, and vegetation need attention first.

Use the model to:

Prioritize targeted upgrades instead of applying broad reinforcement cycles.
Translate asset level metrics such as conductor creep, line tension, and pole loading into system outcomes such as SAIDI, SAIFI, and safety incidents.
Show how the same storm would have played out before and after planned upgrades so you can prove that your plan reduces risk.

This helps you move from generic resilience statements to concrete, testable strategies.

How do you keep pole utilization productive without risking failure?

Mobilize restoration and repair crews faster

Between broadband joint use and growing demand, pressure to increase pole utilization is only rising, but pushing loading too far can create hidden failure points. Use your network model to find the loading window that supports productivity without crossing safety limits.

Stress test every pole in your network against mechanical and environmental variables so you can:

See where current and proposed attachments push loading toward unsafe levels.
Identify specific structures that need reinforcement or redesign before you add more equipment.
Give restoration and repair crews a clear view of which poles are most likely to fail in a given event so they can stage resources accordingly.

Your goal is a network that carries more without leaving you exposed in the next storm.

Which upgrades actually change reliability outcomes?

Validate every asset upgrade

Move away from cyclical, broad stroke reinforcement, repair, and replacement programs that miss critical assets and waste capital. Use an individual asset health view to see which structures, spans, and lines truly require attention in your conditions.

With a physics based diagnosis of each asset you can:

Predict exactly which poles, spans, or conductors are likely to fail in defined scenarios.
Replace or reinforce only the assets that limit system performance instead of entire classes or regions.
Justify every upgrade with simulations that compare how pre state assets would perform in extreme conditions versus their strengthened post state.

This turns upgrade proposals into evidence backed recommendations instead of line items that are hard to defend.

How do you prove that O&M spend improves resilience?

Demonstrate how every O&M line item improves resilience

Use scenario based modeling to show how vegetation work, inspections, and other O&M activities reduce real risk rather than just ticking compliance boxes.

By simulating extreme weather in your digital network model you can:

See which spans and structures face the highest strike and clash risk from vegetation, including outside standard rights of way.
Support vegetation and maintenance decisions with hard data about community risk, not just distance rules.
Run pre and post maintenance scenarios to show how specific tasks improved clearance, reduced clash incidents, or prevented likely outages.

This makes it easier to defend O&M budgets, navigate difficult ROW discussions, and show leadership how operational spending directly strengthens resilience.