After a storm, a utility’s assessment of damage to the grid is critical and the stakes are extremely high. Power needs to be restored to customers as quickly as possible, and field worker safety is paramount. But some utilities still struggle with antiquated processes that impede efficient, effective storm assessment and there are severe consequences associated with a lack of the right data to make the right decisions at the right time.

In one example, some field workers take handwritten notes on paper pads. Relaying critical field data in this manual, paper-based fashion can result in hours of delay in getting the assessment recorded. Someone needs to receive the written data, transcribe the notes, and enter the information into the schedule management system. Only then is a repair order transmitted to the warehouse for fulfillment and to a repair crew that is finally ready to roll.

And this is actually a best-case scenario. Handwritten notes are routinely unclear and the data needs to be clarified and confirmed, which can cause additional delays.

Even when using tablets or smart devices to communicate, the data that is often collected in the field is not stored in a central database for effective use and catalogued for re-use. In a lot of instances, data collected by smart devices have only partially solved the data challenge.

The impact of delays and inaccurate data can be compounded by partners in the mutual assistance program, who are unfamiliar with the infrastructure and geography. This unfamiliarity can result in costly rework orders. In one extreme example we have seen, a mutual-assistance partner inadvertently reversed the design of a feeder and later caused power outages.

In a historical example of storm damage, four hurricanes struck Florida in 2004 over a six-week period. The impact from these storms required the investor-owned utilities to replace more than 3,000 miles of wire (a length that, if stretched end to end, could reach from Tampa to San Diego). About 32,000 poles and 22,000 transformers had to be replaced, all for a combined storm cost of more than $1 billion.

Source: “After the Disaster: Utility Restoration Cost Recovery,” Edison Electric Institute, February 2005.

Some of the delays had more to do with a lack of clear, accurate data in the hands of field workers than anything else. Decisions about what to restore and in what order are decisions that require a lot of data. Imagine the logistics: Where does a utility suddenly get 32,000 poles? If a real-time inventory isn’t available, how does a utility know what it already has on hand? How can a utility coordinate with the field workers doing the restoration to make sure they are being efficient in their efforts? How is the work conducted by mutual assistance reconciled with the invoices that come in from the utility partners?

It is mission-critical for utilities to collect, manage, and deploy data with advanced techniques. This innovation gets the appropriate data to the proper people so that power can be restored more rapidly and safely.

Top three powerful uses of data

Data is the most powerful tool in a storm assessment. Making data available to field workers increases safety, cost savings, and the metrics used to measure uptime to the grid. Data also helps mutual assistance partners understand the utility’s grid to make better decisions. Consider these use cases:

  1. Reimagine the field worker experience
    Using mobile devices such as rugged tablets, field workers and mutual assistance partners can access GIS coordinates to identify location of assets or review engineering documents to view “before” photos and designs and compare to the “after” situation of damage. Additionally, wearing augmented reality tools—such as smart glasses—allows experts in the control room to “see” the field situation, and field workers and mutual assistance partners can receive specialized instructions in real time.
  2. Restore power efficiently and effectively
    Digital processes can shorten delays by seamlessly transmitting damage assessment data across the whole value chain: outage management, schedule management and inventory management.
  3. Add shareholder value
    Analytics is the least expensive way to add shareholder value. By making better use of data, utilities can find new insights for faster decision making. But in order to realize this level of value, utilities must be proactive in managing data as an asset.

Manage data like an asset

Utilities can follow three “A’s” for data integrity:

Available

Data must be accessible across the enterprise, not trapped in silos.

Accurate

Data must be kept fresh, maintained, and up to date.

Analyzed

Data must be reviewed to make sure it is helping connect the dots.

It’s a new year – and time for utilities to move from reactive processes to proactive data management.

Glen Sartain

Principal Director

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