Whether it’s to optimise processes, increase efficiency, reduce emissions or design new processes, data is a key resource for asset-intensive companies for the foreseeable future, Craig Smith tells OGN

For almost as long as there has been industry, there has been data.

Beginning with handwritten paper records of readings collected from different equipment or records of production output, by the 1990s and the advent of digitalisation, data was collected automatically by suites of sensors capable of recording dozens of measurements multiple times per second.

Today, data is an invaluable resource. Companies can tap for insights on everything from the condition of their physical assets, to how to increase efficiency, to monitoring and analysing emissions.

AspenTech's new regional HQ in Al-Khobar houses a dedicated training facility

"As companies work to extract the most value from that resource, many are now turning to what’s been dubbed an industrial data fabric, allowing companies to collect data from across their operations and – perhaps most importantly – contextualise and analyse it for actionable insights," says Craig Smith, General Manager and Senior Strategic Planning Director, KSA, Aspen Technology.

For companies with the forward-looking vision to implement it, a data fabric can deliver a deep and rich data stream that can help drive continuous improvement across operations, from optimising processes and increasing efficiency to fostering innovation and enabling industrial AI, all of which can help drive increased profitability.

To enable more companies to realise those benefits, Saudi Arabia in taking a leading role in developing industrial AI technology across the region.

In late 2024, the Kingdom announced plans to invest up to $100 billion in its AI initiative, Project Transcendence, to support new data centres, startups and other infrastructure.

As the world and our region work to transition to a new energy system, such investments will be crucial for helping companies understand the role data will play in helping implement sustainability measures and meet net-zero targets.

CONTEXT IS KEY

In 2023, the global industry generated as much as 130 zettabytes of data

As the energy transition progresses, asset-intensive companies are facing increasingly complex technological and environmental challenges, challenges that data – by itself – won’t be able to overcome.

To innovate going forward, companies will need a more holistic understanding of the data they have and the data they collect.

In short, context is key and a data fabric makes it easier than ever to deliver it.

While it’s often referred to as a data management framework, that only captures part of the data fabric picture.

At its core, a data fabric simplifies the process of collecting, aggregating and contextualising data from across the enterprise.

Beyond that, a data fabric allows companies to create a virtual layer to house that data and give employees access to the data they need for everything from analysis and decision-making to the construction of new industrial AI models.

That virtual layer, essentially a ‘single source of truth’ for data across a company’s operations is particularly critical, because the sheer volume of data means many companies often don’t fully know what data they have.

Companies are collecting data from across their operations and contextualising and analysing it for actionable insights

Studies have shown that the average company collects data from as many as 400 different sources, with one in five companies monitoring 1,000 or more sources.

Worldwide, estimates from the World Economic Forum suggest that industry generated as much as 130 zettabytes of data in 2023.

To put that in perspective, if the average iPhone has 128GB of storage, 130 zettabytes is equivalent to more than 1.15 trillion iPhones.

Despite collecting such vast amounts of data, relatively little is actually used to generate business intelligence.

According to a Forrester Research study, just 12 per cent of the data companies have is used for analysis, and less than 30 per cent of companies say they can translate the data into action.

One reason why can be traced back to the fact that data is often highly siloed, collected and stored across different locations, in different formats and described or tagged in different ways, making it difficult to coordinate how it is used.

To improve companies’ ability to take advantage of their data, AspenTech has opened its new regional HQ, complete with a dedicated training facility to support competency development among customers in the region.

Located in Dhahran near Aramco and King Fahd University of Petroleum and Minerals (KFUPM), the new facility comes just two years after AspenTech signed a multi-year agreement to provide technical training and competency development programmes on process and asset optimisation technologies and operational analytics to students and staff in the university’s Chemical Engineering Department.

SUPERCHARGE INDUSTRIAL AI

There should be no doubt that data and industrial AI are inextricably linked. Without data, AI models could not be trained, would be unable to identify patterns, make predictions or adapt to new situations.

Around the world, asset-intensive companies are today already using data to develop AI models that can be applied to a host of questions, from monitoring and analysing emissions to locate areas for improvement, to increasing energy efficiency, to optimising the integration of renewable energy resources into the grid.

For companies hoping to truly supercharge their industrial AI programmes and create more meaningful, sustainable AI models, however, an industrial data fabric is critical.

For decades, the adage ‘garbage in, garbage out’ has served as a warning about the risk of building AI models using the wrong or incomplete data.

By making it easier to access data and find the information they need, a data fabric can help simplify the process of designing those models and even help engineers design better ones.

By eliminating the chances of a model getting bogged down searching through a large amount of data to find the right information, a data fabric can theoretically help create models that can be trained and can operate faster than others.

Those improved models can then be applied to complex problems which might otherwise be difficult to model if engineers were uncertain about the quality and accuracy of their data.

As industrial AI use continues to grow, so too will the value of data, and the security challenges that surround it.

With data collected into a single point of truth, companies only need to secure a single resource rather than data that is potentially held in different locations around the world. In addition, security threats can be quickly patched as they arise, with updates propagating through the fabric automatically.

ADAPT TO CHANGE

As the world works to remake global energy systems for a low- or no-carbon future, in the years to come a changing business environment isn’t just a possibility, but a certainty.

Adapting to those changes will be a challenge for companies around the globe, and those in the Middle East will be no different.

Fortunately, the region is already working to ensure companies have the vision and skills needed to properly collect and analyse their data to understand, prepare for and overcome those challenges.

Whether it’s helping to optimise existing processes, identifying ways to increase efficiency, pinpointing opportunities to reduce emissions or informing the design of new processes and innovations, data is – and will continue to be – a key resource for asset-intensive companies for the foreseeable future. The challenge ahead will be in how to use it.