A hydroelectric dam, transmission lines, wind turbines and solar arrays across a connected utility landscape at sunrise.

Talks that move

Predictive Utilities

Connecting trusted utility data, predictive intelligence and operational workflows so teams can act earlier across increasingly complex infrastructure.

Schedule a meeting

Listen podcast

-15

+15

0:00

/

0:00

Conditions shift before the next inspection round begins. In utility operations, the gap between a weak signal and a late response can become a reliability, safety or customer issue.

WHY THIS "PREDICTIVE UTILITIES" CHALLENGE?

Data is growing. Decision time is shrinking

Utilities are moving beyond isolated digital initiatives. Across G&R, T&D and Supply, information from assets, enterprise platforms and external conditions must come together close to the point of decision. The challenge is not collecting more data. It is creating an interoperable, cyber-resilient path from signal to action without weakening human accountability in critical infrastructure.

Key benefits

Earlier insight has to reach the workflow

See risk before it becomes disruption

Contextual analytics can reveal anomalies earlier and give teams more time to respond.

Improve availability with better context

Link physical and market conditions to asset and operational decisions across generation, networks and supply.

Reduce manual effort without losing control

Automate inspection, analysis and coordination tasks while retaining oversight wherever safety, regulatory or operational risk requires it.

Build once, scale with discipline

Reuse data, connectivity and governance patterns across sites, asset classes and business units.

How NTT DATA helps

01

Reliable data and connectivity foundation

Connect authorised operational, asset and enterprise sources across OT and IT environments.

Utility field technician checking sensor and fiber connections inside a substation instrumentation cabinet.

02

Asset and process context

Organise information around the equipment, workflows and decisions that shape operational performance.

Water utility engineer examining a flow meter among pumps, valves and large treatment-plant pipes.

03

Predictive intelligence at the right layer

Apply artificial intelligence, machine learning, generative AI and analytics where they can support earlier detection, prediction or automation.

Inspection drone flying beside high-voltage line insulators in a mountainous transmission corridor.

04

Governed workflow integration

Embed outputs into existing processes with permissions, cyber controls, validation, fallback mechanisms and human oversight.

Gas utility operators coordinating a controlled valve-station procedure with a work permit and radio.

05

Measured scale-up

Start with controlled use cases, track operational KPIs and extend proven patterns across sites and business units.

Utility crews and service vehicles preparing to deploy from a substation operations depot at sunrise.

Utility staff inspecting a rain-wet electrical substation at blue hour with a fully lit city in the distance.

Proven impact

Earlier signals. More confident action

The source defines indicative improvement objectives, not evidenced deployment results.

Results that matter

Deployment targets to validate against each utility’s baseline

Operational cycle time

Indicative objective of a 20-40% reduction.

Manual workload

Indicative objective of a 20-40% reduction.

Decision and response time

Indicative objective of a 15-30% reduction.

Operational visibility

Significant improvement is the stated objective; the measurement method still needs to be defined.

Ready to move from signals to earlier decisions?

Start the conversation about where predictive capability can create the most operational value, with governance designed for critical infrastructure.

Let's talk

Related
NTT DATA Talks