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Risk & Value Optimization

Score every intervention on risk removed per dollar, and show the calculation behind the ranking you filed.

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Rank every dollar by the risk it actually removes

Risk spend efficiency cases live or die on the denominator. Model expected failures per structure from real geometry and simulated conditions, then compare what each option removes, span by span and dollar by dollar.

Compare undergrounding, covered conductor, and replacement on one basis so the ranking rests on modeled risk removed per dollar, not on whichever business case was built first.

Score consequence, not just condition separating the overloaded pole on a hospital feeder from the identically loaded one on a rural spur.

Test the program before you file it seeing what the same budget removes under a different mix, then re-running it when cost inputs move.

The problem

Models built on historical failures can't price the failure that hasn't happened yet

Statistical models rank assets by what has broken before. That holds until someone asks why this program, at this cost, in this order. Answering needs a defensible number for every option, and the numbers take a full cycle to produce:

  • A cost-benefit case rebuilt by hand each time the program mix changes
  • Consequence scores that weigh a rural spur the same as a hospital feeder
  • Six weeks to compare three options, on a submission due in four

So the option you file for is the one you could defend fastest, not the one that removes the most risk.

And when the ranking gets challenged, the working sits across spreadsheets nobody outside the team can follow.

From ranking assets to pricing outcomes

From To
Historical failure rates Simulated failure probability
Program-level cost-benefit Per-structure spend efficiency
One option defended Every option scored
Months of manual analysis Options compared in days

Make capital calls you can defend line by line

When likelihood, consequence, and cost sit in one model, you can rank the options, show the working, and re-run all of it when the assumptions move.

Show which program removes the most risk per dollar across undergrounding, covered conductor, pole replacement, and vegetation work, all measured the same way.

Separate the assets that cause a hiccup from those that cause havoc by scoring customers served, crew access, terrain, and what sits downstream of each structure.

Answer the follow-up question while the review is still in the room re-running the ranking against a revised cost input or weather assumption in hours, not another analysis cycle.

Attach the working to the filing with load cases, weather scenarios, and cost inputs traceable behind every option you ranked.

Real-world applications

Cutting 25,000 condemned poles down to 4,000

Cutting 25,000 condemned poles down to 4,000 United States
100 Age-based condemnation
16 Physics-based review
−84% projected pole replacements

The Challenge

A regulatory commitment to remediate high-risk poles produced an estimate of 25,000 to 30,000 replacements, backed by age tables and qualitative field reports. The cost became a point of contention with the regulator.

The Analysis

Tip-loading analysis ran across every pole in the network, pairing finite element analysis with severe weather simulation to establish which structures still held their rated load, and for how long.

The Outcome

The replacement list fell to 4,000 poles, an 84% reduction, on evidence the regulator accepted, with risk identification running 10x faster.

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From statistical risk models to physics-based ones

From To
Probability inferred from past failures Failure simulated under stated conditions
Scores only the modeling team can audit Calculations anyone can open and check
A number that took a quarter to produce A number you can re-run in the meeting
Justifying spend after the decision Choosing the option before committing

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Risk & Value Optimization

Risk Impact Scoring

Risk-adjust your priorities. Easily gather the context you need for any risk mitigation or asset upgrade decision without the manual effort that lags critical decision-making windows. Automatically simulate every scenario you need to worry about to identify your best intervention actions. Execute network-wide cost-benefit analyses to clear blockers and make the right decisions faster.

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  • Evaluate risk likelihood, consequence, and cost through a consistent, data-driven lens. Automated, context-rich cost-benefit analyses pave the way to better reliability, resilience, and safety outcomes.
  • Scale your best judgment across your entire network so you can allocate hard-won dollars and quickly navigate critical decisions with confidence every time.
  • Quantify and justify decisions with ease so you can adopt a more proactive lens into the future.

Score every risk in your network by likelihood, even the ones you can't see

Flag and score every risk across your entire network, not just the ones you can see.

  • Move beyond piecemeal inspections that over-index on a small universe of known risks.
  • Score every risk, whether or not it falls in scope of a single field visit.
  • Diagnose how assets will fare under conditions from powerful storms to heat waves.
  • Make critical "what-ifs" an integral part of every risk assessment by simulating key variables.

Put your priorities in the right place

When two equally overloaded poles compete for attention, know which one to address first.

  • Assess risk impact continually, like your most detail-oriented analyst.
  • Reflect every asset's exact physical context and configuration.
  • Weigh factors from high-traffic intersection proximity to elevation geometry and nearby water.
  • Distinguish the assets that cause a hiccup from those that cause havoc.

Fast-forward to your best intervention option

Know exactly which poles to replace to improve SAIDI/SAIFI, beyond this year's replacement cycle.

  • Navigate cost-benefit trade-offs for every risk with ease.
  • Simulate multiple intervention options automatically to land on the winner.
  • Move fast enough to decide within the required timeframe, saving costs and red tape.
Risk & Value Optimization

Forecast and Backcast Resilience

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.

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  • 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.

Generate a fast recovery strategy for any scenario

Turn any scenario into a clear recovery roadmap by bringing dangerous conditions into your model before they arrive in the field.

  • Prioritize targeted upgrades instead of applying broad reinforcement cycles.
  • Translate asset level metrics like conductor creep, line tension, and pole loading into SAIDI, SAIFI, and safety outcomes.
  • Show how the same storm would play out before and after planned upgrades to prove your plan reduces risk.
  • Move from generic resilience statements to concrete, testable strategies.

Mobilize restoration and repair crews faster

Find the loading window that supports productivity without crossing safety limits by stress testing every pole against mechanical and environmental variables.

  • 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 repair crews a clear view of which poles are most likely to fail so they can stage resources.
  • Build a network that carries more without leaving you exposed in the next storm.

Validate every asset upgrade

Use an individual asset health view to see which structures, spans, and lines truly require attention in your conditions.

  • 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 by comparing pre state performance in extreme conditions against the strengthened post state.
  • Turn upgrade proposals into evidence backed recommendations instead of line items that are hard to defend.

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 instead of just ticking compliance boxes.

  • See which spans and structures face the highest strike and clash risk, 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 improved clearance, reduced clash incidents, or prevented outages.
  • Defend O&M budgets and navigate difficult ROW discussions with hard data.
Risk & Value Optimization

Equipment Inspections

Stress-test and diagnose every single asset across the full lifecycle from repair, replacement, and reconfiguration without setting foot in the field and focus field time on validation and triage. Digitally inspect your equipment so you can see how every asset will respond to simulated gale force winds, flash floods, and more when you can't have your team out for the real thing.

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  • Prevent more outages and safety incidents by keeping your equipment in its best shape.
  • Stop manually answering the same hundreds of questions per pole. Leave the manual heavy lifting to AI and empower your team to focus on the right questions about improving resilience.
  • Be the first to know about critical vulnerabilities by simulating hundreds of mechanical and environmental variables, from heat waves to line tensioning, so you can see the unforeseen and take preventive action.

Replace, repair, or reconfigure?

Look to your network model for a 90% automated triage plan to get every asset in shape.

  • See which equipment needs attention and diagnose the right next step for each asset.
  • Choose whether to replace a concrete pole with steel, add a stay, or relocate.
  • Measure pole height, lean, bend, and conductor tension with precision at scale.
  • Stress-test your equipment to find and fix your weakest links.

Get pole load "just-right"

Find the ideal pole load so your efficiency never becomes the enemy of reliability or safety.

  • Maximize pole utilization for broadband joint use and expanding carrying capacity.
  • Avoid the catastrophic consequences of pushing pole utilization too far.
  • Stress-test every pole against hundreds of mechanical and environmental variables.
  • Find the right loading formula that supports productivity without risking failure.

Flag buddy poles

Automatically detect and flag double poles so you can maintain every asset, not just the ones in your GIS.

  • Find poles you cannot maintain today because you are unaware of them.
  • Detect double poles by height, type, and spatial relationships in your network model.
  • Get a clear lay of the land across every asset you are liable for.
  • Allocate maintenance work orders with confidence across all assets that need attention.

Safeguard against conductor clashing

See exactly where clashing and galloping are most likely and most severe, without relying on field surveys.

  • Track conductor behavior that changes on a dime in different conditions.
  • Pinpoint tension imbalances and structural flaws across every conductor in your network.
  • Layer on prime wildfire conditions or a hailstorm to test each span.
  • Act against short-circuiting and equipment failure before they happen.

Understand cumulative asset stress

Factor in how asset integrity changes over time as equipment experiences cumulative stress like cable creep.

  • Go beyond how assets stand today or fare in high winds, ice, or heat.
  • Simulate creep curves in custom increments based on the actual age of assets.
  • Layer in as many other variables as you see fit for thorough inspections.
  • Make the best lifecycle decisions with a view of stress over time.

Stay ahead of asset failure with network-wide FEA

Calculate strain and stress on all network components with AI-assisted FEA in your digital model.

  • Cover poles, spans, cross-arms, insulators, pins, and braces.
  • Detect hidden risks and prioritize replacements and repairs.
  • Evaluate which poles are at capacity and which can carry more load.
  • Keep every asset at peak performance, no matter where you are in the lifecycle.
Risk & Value Optimization

LiDAR & GIS Reconciliation

Your operations are only as strong as the data you rely on. Combining accurately classified LiDAR with your GIS generates a powerfully accurate network model. You can confidently navigate life-saving decisions and major grid hardening investments across every corner of your network. This high-fidelity foundation ensures that your digital twin reflects the real-world state of your infrastructure.

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  • Use LiDAR to identify and resolve GIS discrepancies to find the best pathways to resilience.
  • Diagnose standard compliance issues remotely without relying on outdated paper records.
  • Reduce faults with data-driven decision-making across the entirety of your network.

A blueprint to inform your most important decisions

Save your effort for managing real-life risks instead of correcting data issues.

  • Identify and catalog unknown assets with a topological fit function.
  • Model asset distribution, proximity to topological variables, and asset type and purpose.
  • Maintain control over your network and avoid at-fault assertions during audits.
  • Turn a fragmented system of record into a traceable record of accountability.

A single source of truth to direct your operations

Remove unnecessary friction and keep your GIS records up to date automatically.

  • Sanity-check your GIS against high-quality LiDAR scans and satellite imagery.
  • Avoid the wasted time and cost of sending field crews to incorrect GPS coordinates.
  • Replace paper processes with a clean, consistent source of truth.
  • Keep office and field teams working from the same physical data.

Reconcile discrepancies at scale

Transition from manual data entry to an automated, physics-based reconciliation workflow.

  • Align LiDAR and GIS records into a foundation that stands up to regulatory scrutiny.
  • Identify where your physical network differs from your digital database before gaps become liabilities.
  • Start every project with an accurate baseline, from routine maintenance to major rebuilds.
  • Back every decision with verifiable physics to protect your professional standing.

See your network as one physics-enabled digital twin

Book a personalized demo and see how leading utilities rank, defend, and re-run every capital risk decision.

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