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Storm impact prediction & network preparedness

Storm impact prediction and network preparedness combine AI/ML, geospatial analytics, earth observation, weather intelligence, GIS and IoT to keep networks resilient.
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Utilities often lose visibility of their own network exactly when a storm makes it matter most.
WHY THIS STORM IMPACT PREDICTION & NETWORK PREPAREDNESS CHALLENGE?
Storm response needs a prepared network, not a reactive one

Wind and rain knock out communications and data links at the exact moment field teams need them most. Storm impact prediction flags the most exposed network segments, so preparedness starts before the storm arrives.

Key benefits
Stronger Storm Response Through Network Preparedness

Storm impact prediction and network preparedness keeps critical workflows connected when conditions turn severe.

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Communications built to hold up through the worst of it

Higher communications availability and resilience keep field and control room teams connected during severe weather.

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Critical workflows moving as fast as the storm

Lower latency for critical workflows means dispatch and safety decisions do not wait on a slow data path.

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Every distributed asset visible before impact

Improved visibility of distributed assets shows exposure across the network before the storm reaches it.

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Less scrambling to move data mid-event

Reduced dependence on manual data movement keeps information flowing automatically when teams are stretched thin.

How NTT DATA helps

01
Connect the data you need

NTT DATA brings together weather intelligence, geospatial analytics, earth observation and IoT network telemetry your storm plan depends on.

02
Apply intelligence at the right point

AI/ML sits where a network resilience or crew staging decision happens, not buried in a post-event report.

03
Build on workflows you already run

Storm impact outputs connect into your existing operational technology (OT) and enterprise systems, not another isolated layer.

04
Protect critical infrastructure

Permissions, cybersecurity controls, validation and fallback mechanisms get defined to match the safety bar your network requires.

05
Scale from proven use cases

Each new storm preparedness use case grows from a controlled deployment measured against clear operational KPIs, so scale-up follows evidence, not guesswork.

Proven impact
Networks built to stay up through the storm

Storm impact prediction connects weather, network and asset data so workflows keep running when conditions turn severe.

Results that matter
Indicative Performance Objectives for Storm Impact Prediction & Network Preparedness

Objectives depend on baseline performance, infrastructure and deployment scope across climate-risk operations.

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Faster storm risk assessment

20% to 40% reduction in risk assessment time, reflecting quicker movement from weather data to a preparedness decision.

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More lead time to stage crews and equipment

15% to 30% improvement in warning lead time, giving teams more time to prepare before impact.

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Less manual review of network exposure

30% to 50% reduction in manual geospatial review, freeing analysts to focus on the most exposed segments.

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Faster network readiness before landfall

20% to 40% reduction in response preparation time, reflecting quicker movement from prediction to readiness.

Every storm deserves a prepared network

Shape the conversation that keeps your network running through every storm.

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