Why ‘Quality Data’, Not Big Data Is Critical For Process Efficiencies
The article emphasizes that quality data, rather than sheer volume of big data, is essential for achieving process efficiencies in industrial sectors. Experts from companies like Repsol, Versalis, and Engro Fertilizers highlight that reliable, business-relevant data drives effective AI and agile decision-making. High-quality data supports digital transformation, sustainability, and operational resilience in industries ranging from refining to fertilizers.
- ▪Industry experts argue that high-quality, business-relevant data is more valuable than large volumes of randomly collected data.
- ▪Nuno Pacheco of Repsol stated that AI models trained on poor-quality data produce unreliable results, undermining digital initiatives.
- ▪Adriano Alfani of Versalis linked quality data to a strategic shift toward biochemistry and circularity in response to economic pressures.
- ▪Muhammad Zaghum Riaz of Engro Fertilizers emphasized that quality data is mission-critical for advancing AI-driven autonomy in industrial operations.
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MoneyMarketsWhy ‘Quality Data’, Not Big Data Is Critical For Process EfficienciesByGaurav Sharma,Senior Contributor.Forbes contributors publish independent expert analyses and insights. Gaurav Sharma is a London-based analyst who covers energy & ESG.Follow AuthorMay 16, 2026, 06:08pm EDT--:-- / --:--This voice experience is generated by AI. Learn more.This voice experience is generated by AI. Learn more.Illustration: Getty CreativesgettyIn a software-led global industrial complex that’s going strong on digitalization, the mention of ‘big data’ has become routine. But process industries say it is ‘quality data’ and not randomly gathered digital data mountains that make the difference.
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