Industries

Energy & Utilities

Intelligent energy and utility solutions for a sustainable future.

Turn transformative insights into operational gains. Our strategic and technological expertise will help you realise step-changes in efficiency to prepare your organisation for a transition towards NetZero.

Why is technology so important to the energy industry?

We can deliver social and economic impact by leveraging digital technologies to conserve energy and preserve natural resources through smart energy management of commercial and consumer demand from connected vehicles, smart cities, buildings and homes.


Digital technology can empower us all to conserve energy, cut emissions, and preserve natural resources. Whether it’s AI driven energy management, connected cities, technology can help you create a vision and support your organisation transform.

What are the problems the energy sector faces?

Regulations

Regulations are well established in energy and utilities. Resources are a valuable commodity with risks in their mismanagement. The industries and governments around the world provide significant attention to avoid incidents which are enforced with a network of regulations.

The basic effect of this is that change is measured and slow - an antithesis to the iterative culture advocated in digital technology.

Supply Chain Management

An extensive array of subcontractors compose this industry. Whilst manufacturing is king of the deep and complex supply base, energy and utilities organisations are highly collaborative. This means changes in one organisation must be accepted or interoperable with their partners.

Whereas utility companies tend to be national, energy companies are often involved in global operations. The legal and regulatory environments are subsequently varied, and services such as internet connectivity are occasionally compromised.

Data Sharing

Due to the size and nature of these global organisations, data sharing and utilisation is often strained, meaning coordinating large scale changes can be hugely complex. 

For modern industrial and energy companies, the ability to work with big data is a key competitive factor. This requires the implementation of applications for data analysis, including those based on artificial intelligence.

How can technology help remove these barriers?

Internet of Things

Predictive Maintenance

Using industrial IoT Edge systems to schedule predictive maintenance for assets and value based systems can become data driven. Remote workers can review realtime asset health and statistics, leading to informed decisions thus reducing the need for unnecessary stoppages in supply chains.

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Data

System Integrations

Through cloud based applications, system data can be integrated from an organisation wide level, allowing step-changes in knowledge sharing and efficiency practices.  Leading to possibilities such as workforce, technician and operations management systems, including digital work instructions and frictionless traceability applications.

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Exciting Opportunities

Optimisation

Software driven optimisation of energy efficiency and operations through autonomous load-balancing and synchronisation of distributed energy sources via bespoke digital twins, will allow organisations to extract the best possible returns for their assets, customers and reputation.

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Jamie Hinton

Jamie Hinton

CEO

Some of the reasons that energy and utility companies have struggled to achieve digital transformation is that they are inherently physically oriented businesses - highly valuable, capital-intensive assets that are subject to the laws of nature and sophisticated management and maintenance processes.

This means that technology investments have to be well-established and low-risk for integrating into these operations.

Explore our client stories

Energy and Utilities businesses experiencing real change

Digital Transformation

Using Prediction For Sales Growth

As the business scales, the successful aspects get amplified and so do the not so successful. But what if we could use historical data to provide the sales team with a suggested sale price that keeps the business profitable.

View the case study