A highlight of the Tomorrow Show 2024 in Oslo was keynote speaker Pascal Bornet, a pioneer in Intelligent Automation. He articulated the importance of decision intelligence, noting a staggering 95% correlation between effective decision-making and financial performance. “A company’s value is the sum of its decisions” Bornet remarked, underscoring the critical need for structured decision metrics. In a landscape flooded with information, organisations must recognise and mitigate cognitive biases that can obstruct effective choices.
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Bornet highlighted that too much information leads to decision paralysis emphasising the need for clarity in the decision-making process. He introduced the three modes of decision-making—decision support from AI enhanced clarity, decision augmentation to improve human-computer decision quality, and decision automation—which provide a strategic framework for how companies can leverage AI to various degrees in their decision-making processes.
Many companies face the pitfalls of siloed information, where fragmented data can hinder collaboration and efficiency. Bornet asserted that collaboration is key to maximising the benefits of data analytics. By breaking down these barriers, organisations can foster an environment where teams work together more effectively, enhancing overall operational efficiency.
At the Tomorrow Show in Oslo, customers and partners demonstrated how they leverage AI and digital twin technology to break down silos and enhance decision-making. Kognitwin enables organisations to visualise and analyse data in real time, streamlining operations and facilitating swift, informed decisions. As more companies adopt this innovative approach, the potential for increased collaboration, scalability and efficiency in heavy asset industries continues to expand.
In a panel discussion concerning the industry outlook, Haavard Oestensen, Chief Commercial Officer at Kongsberg Digital, emphasised the transformative potential of AI in enhancing decision-making. He stated that AI should be viewed as a booster for human capabilities, not a replacement, highlighting that successful AI integration relies on adoption and a culture that embraces it’s use.
Oestensen explained that AI can significantly improve decision quality by contextualising relevant data and providing decision-making frameworks. “AI helps elevate the right data into the right context, guiding execution,” he noted. He also pointed out that organisations often focus on complex use cases while neglecting the optimisation of lower-frequency, high-impact tasks, highlighting that by leveraging AI for these tasks frees personnel to tackle more complex challenges.
Ultimately, Oestensen underscored that the goal of adopting AI is not just efficiency but also enhancing the quality and impact of decisions, emphasising that as we embrace AI, we must remember that its role is to augment our decision-making capabilities.
Aker BP aims to become the first truly data-driven oil and gas company, with a strategy centered on integrating data across various engineering applications. Arnfinn Grøtte, Chief Engineer of Drilling & Wells, noted that to solve this challenge we need to come together as an industry and cross-domain. By utilising the OSDU standard for data sharing, Aker BP fosters collaboration among subsurface, drilling, and subsea teams, ensuring that all stakeholders have access to the same information. The company leverages digital twin technology to create real-time visualisations that allow engineers to assess risks dynamically and streamline decision gate reviews by digitising engineering work across business units.
Grøtte emphasised, “We now have the possibility to start to build cross-domain workflows and automation not possible before,” underscoring the efficiency gains from this integrated approach. By incorporating AI and machine learning, Aker BP aims to enhance decision quality. He pointed out, “If we’re going to use AI for engineering, it means we need to start to collect the data.” This commitment to data-driven decision-making positions Aker BP as a leader in the digital transformation of the energy sector, showcasing the potential for AI and digital twin technology to revolutionise industry practices.
For Yara, managing data across 26 production plants in 140 countries is a daunting task, with each site generating vast amounts of information, including maintenance records, production metrics, and engineering documents. Historically, this data has been stored in disparate systems such as SAP databases and paper archives, making timely access slow and cumbersome. This inefficiency has hindered decision-making and overall operations. Sustainable industrial growth relies on the ability to integrate and share data at all organisational levels.
Yara’s digital twin solution is set to break down silos and unlock opportunities for cross-disciplinary collaboration. Different teams—such as production, maintenance, and engineering—will work from a single source of truth, enhancing decision-making efficiency. For example, when production teams identify potential bottlenecks, they can collaborate with maintenance and engineering teams in real time, using shared data to resolve issues quickly.
As the energy landscape continues to evolve, embracing AI and digital twin technology is no longer optional but essential for future-ready organisations. By transforming decision-making processes, breaking down silos, and enhancing personnel efficiency, companies can position themselves to thrive in an increasingly complex environment.
