HomeDigitalizationAutomationHow COVID-19 has changed energy networks for the better

How COVID-19 has changed energy networks for the better

The pandemic has accelerated the arrival of a ‘new normal’ for utilities argues Jay Cadman.

Jay Cadman, Senior Vice-President of Enterprise, IQGeo

The shift in working patterns driven by COVID-19 restrictions has accelerated the digital transformation initiatives of utilities.

And those companies that adapted effectively will retain significant beneficial changes long after the pandemic is over.

Challenges including reduced and remote workforces, decreases in commercial energy demand, surging customer calls and use of digital and self-serve channels during lockdown have compelled companies to digitalize and decentralize their operations.

Constraints on human resources have necessitated the empowerment of office and field teams to deliver smarter, more proactive, and more predictive customer service.

As a result, customers themselves are also increasingly encouraged to make use of self-service resources wherever possible. This has driven the democratization and decentralization of network data and decision-making to produce more lean, agile operations and an efficient, productive workforce capable of doing more with less.

A promising post-pandemic trend is the erosion of traditional silos between departments and workflows from design to engineering as data is increasingly shared to create more integrated, efficient operations.

We have also seen data silos broken down and geospatial network data being shared with everyone from call-center staff to customers.

In many respects, this shift in access to network data can be seen as the silver lining behind the pandemic cloud for network operators. These are just some of what we hope will be permanent shifts in electrical network management spurred by recent restrictions and how they are contributing to the digital transformation of the energy industry.

Democratization of information

A remote and reduced workforce has necessitated the opening of network data to the wider workforce and even to customers. In a remote working world, network information can no longer be held in proprietary apps, paper maps or spreadsheets accessible only to cartographers or central office.

Many companies previously used centralized, ‘closed’ network maps, paper-based processes, and applications accessible only to GIS data specialists, creating a data gap between the office and the field.

This meant that if specific workers were furloughed or ill, access to vital knowledge and insights was interrupted.
Centralized, siloed data prevented field engineers or call-center staff from working independently, and impeded moves to smarter, more proactive, and targeted repairs, upgrades, or customer service.

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Crucially, siloed systems make it difficult for teams to quickly update geospatial network information with records of recent upgrades, repairs, and as-builts, as well as external information such as local weather hazards.

This restricted data flow prevents operators from having the kind of comprehensive and current picture of energy grid health that was critical during lockdown when millions were housebound.

Less frequent trips to the office means that distributed and mobile geospatial information is needed to share data across the field workforce to help field engineers find up-to-date information on the position and condition of nearby network assets.

We are increasingly seeing geospatial data on network assets being made available to employees on company tablets, smartphones and even personal devices and employees managing network assets from homes or temporary offices.

Using mobile geospatial technology, they now attend callouts using personal devices without even visiting central offices. It is becoming for common for companies to allow workers to monitor and manage outages and run geospatial network applications from home or in the field.

Field engineers can use a combination of mobile apps and Google Maps technology to rapidly view critical network information, or for greater situational awareness when monitoring network assets.

Mobile network data makes it simple for field engineers and construction teams to find unfamiliar locations and nearby assets, targeting repairs efficiently and effectively.

Erosion of workforce divides

We are seeing steady erosion of traditional departmental silos as organizations democratize and decentralize network data and decision-making.

Increasingly, separate disciplines such as survey, construction, maintenance, sales, and customer service are now sharing network data underpinned by an integrated end-to-end geospatial strategy.

This maximizes collaboration between different teams and increases operational efficiency which streamlines all processes across the customer lifecycle.

When call-center staff can access the same network information as field engineers, it creates more joined-up and collaborative customer service that helps to reduce unwarranted truck rolls or engineers attending the wrong location with the wrong equipment.

This not only facilitates remote working but creates smarter, more predictive networks, it means everything from the location of customer callouts to equipment defects can be instantly overlaid onto a geospatial network view to identify the site and source of problems.

A real-time integrated overview means that lessons learned in one part of an organization can also be quickly captured and cross-pollinated. For example, data on how a storm affected wind turbines in one area could be used to protect turbines in other areas against similar hazards.

The key to this digital transformation is to create systems capable of absorbing knowledge from the ‘edges’ of an organization and make this information available to all departments, employees, and even customers.

With an increasingly remote workforce, energy companies need remote and real-time visibility of their network assets. We are now seeing energy companies with the ability to capture, integrate and share real-time geospatial network data from across the world.

Some companies are implementing geospatial systems that integrate live data from sensors or smartphone apps in the field to create a real-time overview and ‘digital twin’ of their network accessible across their network lifecycle.

Automation of processes

Even before COVID-19 there has been a general decline in the number of utility employees at the while networks are expanding, and this trend may well be accelerating.

This reality is driving the need for greater process automation as limited human resources stretch further. This has included innovations such as one-click payment, webchats, WhatsApp, and even self-service.

A good example of increasing automation is how smart geospatial data is being merged with customer complaint data to proactively prevent incidents such as outages in particular areas and create more remote, targeted, and predictive maintenance of networks.

This is being incorporated with ‘open’ geospatial information systems updated in real-time by field workers on mobile apps so that call-center staff can instantly see live, location-based information on recent as-builts, damage, hazards, or upgrades.

Geospatial information systems capable of absorbing data from many sources and making it instantly cognitively available across a network in real-time creates the possibility of holistic, responsive, and even automated customer service.

A combination of live, location-based network data and local metrological, ecological and infrastructure data can fuel machine-learning systems capable of anticipating and averting customer complaint hotspots or even power cuts before they occur.

In future, geospatial data could even be made directly available to customers, for example, to tell affected customers about areas that are due for an infrastructure repair or likely to be affected by a power outage and explain the remedial action being taken.

Digitalizing, decentralizing and synthesizing data from across a network not only helps augment the human workforce but will ultimately fuel autonomous customer service and even ‘self-correcting’ energy grids.

Future smart grids will integrate geospatial network data from ‘Internet of Things’ sensors with real-time weather or consumer demand data to predict customer call hotspots or hazards and take remedial action.

While it goes without saying that COVID-19 has presented innumerable challenges to industries across the board, it has also undoubtedly accelerated the arrival of a ‘new normal’ for utilities.

Detailed, real-time information is becoming increasingly decentralized and democratized, maximising collaboration within and between teams for increased efficiency and agility.

Increased automation of business processes has also empowered firms to deliver more holistic and responsive customer service, bringing about a much needed and long overdue digital transformation for the industry.

Jay Cadman is Senior Vice-President of Enterprise at geospatial software company IQGeo