Man talks Machine: a group of downstream industry leaders discuss how AI is shaping the market

Asia engineer stand holding hand touch of smart phone on oil and gas refinery plant background, Engineer planning work concept, Professional technician monitoring of petrochemical industry plant

Artificial intelligence is revamping the downstream industry. ML is streamlining manpower. Algorithms are predicting unplanned downtime.

But how much is digitalisation really driving business decisions? And how can you equip your workforce – from engineers to senior management – to adapt to the new digital normal? Asian Downstream Insights and moderator Hari Govindahari, Associate Partner, at McKinsey & Company, Singapore, brought together a group of international business leaders from Shell, Nayara Energy, Reliance Industries and Chennai Petroleum,  to discuss digitising downstream industry.  

Active ownership of AI (ROI)

Digitalisation may be the talk of the market, but when it comes to putting your money where your mouth is, how can refiners use AI to boost profitability? 50% of respondents in an interactive poll agreed that the key was in “selectively engaging deep on critical items”.

For Vikas Deshmukh,VP Technology, Hydrocarbon business at Reliance Industries, the most critical item on his agenda is knowing business issues in advance.

“We are in an era of predictive analytics”, he explained. “I can see the business value across the entire business value chain, in terms of prices abnormality and equipment related failures”.

Surendra Pandey, MD of Chennai Petroleum agreed that less downtime equals more on the bottom line. “Technologies can help to predict [and] reduce downtime”, he states assuredly. And reduced downtime is money”. Leading operators across the market are already showing results, with ADNOC recently announcing its new first-phase predictive maintenance platform is expected to deliver maintenance savings by up to 20%.

One thing is clear, that when it comes to driving digital decisions, who gives the message is as important as the message itself. 20% of poll respondents believed that AI should be a number #1 management agenda, with active ownership.

“Any decisions driven by tech team will be hard for the business”, admitted Vikas Prabhu, CIO of Nayara Energy. “If it is driven by business owners, they see it as their own and they will try and drive it”.

Getting senior management on board is a key part of unlocking digital value, and the panel agreed that a key question operators need to be asking themselves is ‘how strong is my top management in driving this initiative?

With the right narrative – and the right narrator – proving the business value of digital initiatives should be a simple equation. As Govindahari summarised, “ROI should not be a big concern as long as it is framed right in the value story”

AI at scale

As Govindahari joked, In an era where there are “more pilots than Lufthansa”, scaling a digital initiative from inception to full implementation is still a work in progress for most of the downstream community. With almost a third declaring themselves in “pilot purgatory”, the panel agreed that growth was a growing concern for downstream digital pioneers.

Pandey believes that scalability means having an agile strategy that will evolve, depending on where the organisation is on its digitalisation journey.

“Each organisation is at different stages”, he explained. At the beginning you will put your money where you think the most value will be on the bottom line. (Later on) you will look at a more integrated solution”.

“[Scalability]is tough”, Oliver Wotton, Head of Manufacturing IT at Shell, conceded. “But I also think we get a bit hung up on it. No two assets are the same [and] differentiation is often the value. What’s important from a scaling perspective is that the platforms are scalable. The underlying platform needs to be the same. We need to agree on certain definitions for data”.

He added, “It’s an extremely hard piece of work, but getting it right, means you only need to invest once [in the right platform]. Good data is better than more data. And more good data is better than AI”.

Clean data driving transparency

When it comes to AI driven value it’s not just profit that counts. “Ultimately bottom line is important, but so are other issues”, stressed Pandey.

ESG and sustainability were two major factors driving innovation investment, the panel agreed. As the lack of clear environmental governance frameworks across all industries drives global demand for data, AI can help provide and streamline this information, to provide much needed transparency as stakeholder scrutiny mounts.

For the downstream industry, where many of the top operators have publicly pledged carbon net zero-goals within the next thirty years, this can help them measure, and prove, the sustainability of their business.

“Now, all the biggest units, their emissions have visibility”, added Pandey. “Who is polluting, what are the emissions?”

Deshmukh agreed that “emissions – will be a major concern [and there will be a] lot of stringent measures. [The] good news is here also digitalisation is going to add value. A real value [that] AI can add is managing multiple assets and… the capacity to look at the business as a whole”.

A human approach to AI

Digital progress means that, as Prabhu puts it, “these technologies are already giving more than previous technologies to the organisation”. But as innovation accelerates, operators need to empower their workforce to keep up. This, Wotton believes, is where the real value lies. “Getting your engineers to understand what is essentially a black box to them”, he described.  “That’s where we are focusing, embedding AI into the work processes. We need to think a bit more long-term.”

“There will be a lot of change management”, agreed Deshmukh. “It will take some time to implement into the organisational concept”.

Managers need to ensure that digital initiatives are user friendly, and their implantation is accessible. At the same time, the workforce needs to be agile and open to adapt. “You need to have a culture that thrives on change”, insisted Wotton.  “Everybody needs to get on board with this. The whole process is going to change and that requires a much bigger investment in understanding… that’s where you want to spend your emotional and cerebral capital”.

As the era of refinery 4.0 gathers pace, it is not the latest solution, or shiny box, but this emotional and cerebral capital which will be the industry’s most valuable investment. It is the combination of artificial intelligence and human knowledge that will forge the fastest path to success.