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Recap: Reducing Wildfire Risk with Analytics and Automation & AI Modeling Advancement

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Last month, Neara was a sponsor at both Distributech and Utility Imagery & Inspection Consortium!

At Distributech, Southern California Edison, Deloitte, and Neara pulled back the curtain to show how SCE has reduced wildfire risk using unified analytics.

Here are the key takeaways from our discussion:

Risk-based (vs. time-based) vegetation inspections are a game-changer in addressing wildfire risks faster and more cost-effectively 

So far, SCE is completing vegetation work 50% faster by getting clearance reports into field crew hands faster. It once took 60-90 days to acquire data and generate vegetation clearance reports. Now? SCE is generating clearance reports within 9-11 days.

Unified analytics = consistency that keeps on giving

SCE’s approach to unified analytics starts with data conflation across each circuit and ensures careful pairing of data collection approaches with each data type. Then, the various data types get cleaned, classified, and normalized into a digital model so they’re ready to facilitate clearance risk analyses. 

When your veg clearance reports are durable, digital artifacts instead of papered work orders with the lifespan of any given trim job, you can infuse all field operations with more accuracy. Digital clearance reports create unprecedented consistency, reducing barriers to action and driving down costs, reducing the likelihood of repeated or misdirected work. 

“Measure twice, cut once.” 

Literally. Give pre-trim crews hyper-accurate visibility into both as-(remotely)surveyed conditions and how sag and sway will impact veg clearance on a sweltering day or when a NE wind >60 mph shakes things up. 

At the Utility Imagery & Inspection Consortium, we sat down with Exelon, Oncor, and Dominion on a panel discussion about how AI modeling and imagery technology are advancing.

Here are our top three takeaways from this discussion.

“Just start.” 

“My data is perfect.” – said no one ever. 

Don’t be intimidated by a lack of perfect data because new insights, however incremental, can reap big wins in improving safety and efficiency. Plus, getting started with network modeling is the best way to identify shortcomings in the data you’re starting with so that you know what to do next. 

“Change your benchmarks.” 

“The last thing I need is 1,000 more work orders.” – said every network operator

What happens when new tech reveals 10x more risks than you were previously able to see at any given time? 

Rather than engage in a never-ending game of whack-a-mole, adjust your prioritization framework to be in sync with your expanded visibility. Yesterday’s P1 may actually be a P2 based on what you’re now able to see. The best AI applications will help you not just see more risks but will also sharpen your ability to differentiate between what actually needs your attention right now and what can wait. 

“Embrace data governance.” 

The more you embrace technology, the more data “exhaust” your operations will create. 

The benefit? You’re building quite possibly your most valuable enterprise asset to date. 

The challenge? Ensuring you put that data to work in a way that benefits not just your operations but your entire ecosystem and community. Data is powerful currency in facilitating public / private partnerships that can drive faster, safer decision-making when it matters most.

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