Making data work when managing utility assets

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by Igor Sadimenko EY Asia – Pacific EAM Regional Lead

The way electricity is generated and consumed is changing irreversibly toward a more distributed model. The future of our system is decarbonised, decentralised, digitised and democratised. The way we manage energy assets and asset data is also having to fundamentally change – and it’s happening faster than we think.

Igor Sadimenko EY Asia –
Pacific EAM Regional Lead

This distributed model requires a significant level of digitisation in order to work efficiently and effectively, as it relies much more on ‘many-to-many’ transactions between a growing variety of service delivery assets – from solar array and storage to smart meters and sensors.

Across the power and utilities sector, the shared digital architecture is being reconfigured and businesses will need to transition to a more inclusive and far reaching digital infrastructure, capable of far deeper levels of asset inclusion.

Driving intelligence and value

The Internet of Things (IoT), the proliferation of distributed energy resources, behind-the-meter connected devices and electric vehicles (EVs) are generating vast quantities of unstructured data. At the same time analytics and artificial intelligence (AI) – machine learning, image recognition and deep learning in particular – are transforming how asset data is collected, collated, analysed and leveraged.

AI can remove the need to start from a hypothesis – a common requirement in traditional analytics that has constrained thinking, making evolution an incremental and slow process – and instead look for and find new insights in well-worn data sets.

Image recognition, for example, can help identify anomalies, manage and predict the performance of grid assets. Whereas machine learning and deep learning can synthesise and model the impacts of numerous new technologies (EVs, batteries, drones, advanced metering systems to mention just a few) deploying in a far shorter time-frame than before.

Making the data work for you

Data informs every management decision throughout the asset lifecycle and supply chain. It needs to flow effectively and lead to actionable insight. The more an organisation values data and information as a strategic asset and a differentiator in its own right, the greater the efficacy of its asset management and the likelihood of maximising ROI.

Today, utility incumbents are often data rich but intelligence poor, collating vast amounts of asset data in asset registers, without necessarily linking it back to an asset strategy designed to support long-term business goals. This takes its toll on utility asset decision-making, often resulting in lackluster return on (asset) investment and value leakage.

Exercising tight planning and controls to manage data quality makes organisations far better equipped for timely, cost-effective interventions. But collecting and managing the right data throughout the asset lifecycle requires robust organisational discipline, particularly where large asset fleets are concerned, as these demands increase with the exponential growth in data volumes.

To turn asset management into asset excellence, leading organisations need to incorporate the following three considerations into their asset strategy:

  1. Treat data as an asset class. Data and data culture need to be key priorities for the organisation. Data has strategic significance, can be leveraged and monetised, and requires appropriate management — so it should be valued as an asset in its own right. This means identifying, collecting and standardising asset data critical to decision-making; establishing governance and processes to manage information — how it is acquired, cleansed, stored, secured and evaluated; creating a data-driven culture with accountability around data; and taking a commercial view of data that prioritises investment and balances short and long-term costs and benefits.
  2. Seek out opportunities to exploit data across the whole organisation. Data should be integrated across platforms — such as operational technology, finance and asset systems — to unlock additional insight and promote truly joined-up thinking. Where appropriate, organisations should partner with specialists to gain cost-effective access to new data and analytical capabilities
  3. Pursue insight through enabling  technologies and analytical capabilities. Organisations need to commit to consistent investment and development of enabling technologies (such as analytic, AI, augmented
    reality, blockchain, etc.) across the P&U value chain.

Disruptor, not disrupted

Digital disruption and technology innovation provides not only the motivation but also the means for utilities to make the data work for them and reinvent the way energy assets perform in a sector undergoing rapid transformation.

Those that embrace digital asset management as a gateway to better decision-making and a fundamental driver of utility value will gain competitive advantage and outperform their peers. Those that don’t face a widening capability and stakeholder expectation gap on performance, service and cost, because with disruption also come new entrants – often from other sectors – that are tech savvy, agile, aggressive and cash rich.

For that reason, asset excellence must be prioritised on the board agenda to enable the appropriate cultural, strategy and policy changes across the business. For asset intensive P&U businesses, harnessing the power of data and asset management has never been more important to reinvent themselves as a disruptor, not the disrupted.

The views expressed in this article are the views of the authors, not Ernst & Young. This article provides general information, does not constitute advice and should not be relied on as such. Professional advice should be sought prior to any action being taken in reliance on any of the information. Liability limited by a scheme approved under Professional Standards Legislation.

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