**Cambridge**: At the Crossroads 2025 event, MIT experts and industry leaders discussed the pivotal role of data quality in harnessing AI for supply chain transformation, featuring insights from GE Vernova, Procter & Gamble, and Walmart on their innovative practices and technologies.
At the recent Crossroads 2025 event hosted by the Massachusetts Institute of Technology’s (MIT) Center for Transportation and Logistics, artificial intelligence (AI) was a focal point of discussion as researchers and supply chain executives explored its transformative potential in the supply chain sector. The event, which took place last Tuesday, revealed a consensus among industry leaders: effective supply chain transformation hinges on robust data management and quality.
Dan Garceau, chief supply chain officer of GE Vernova, emphasised that the company’s most impactful initiative has been its emphasis on lean manufacturing principles rather than on cutting-edge technology. By adhering to these principles, GE Vernova has enhanced the stability and predictability of its processes and data. This solid foundation has subsequently facilitated the effective use of AI-enabled tools within the company.
Procter & Gamble (P&G) is another notable organisation prioritising data quality as a cornerstone of its Supply Chain 3.0 initiative. According to Michelle Eggers, vice president of North American market operations and global logistics purchase at P&G, the initiative revolves around the concepts of “seamless data, touchless flow.” This approach involves integrating data from various sources to create a unified perspective while automating processes to eliminate manual interactions. Eggers outlined that achieving automation requires laying groundwork by improving data quality.
Johnson & Johnson (J&J) shares a similar focus on data management with its initiative to establish a “common data layer,” as described by former chief procurement officer Shashi Mandapaty. This common data layer acts as a foundation for utilising generative AI to enhance quality and comply with regulatory standards across over 100 countries. Mandapaty pointed out that this system allows for continuous monitoring of regulatory changes globally, affirming that human oversight remains integral to the process.
Enhanced AI capabilities have enabled GE Vernova to leverage historical engineering data effectively, utilising AI to examine decades of engineering drawings to locate per- and polyfluoroalkyl substances (PFAS)—chemicals that persist in the environment. Garceau noted the significant time savings achieved through AI analysis, freeing engineers from labour-intensive reviews of older documentation.
At P&G, the progress towards a unified data system and shared language with customers and suppliers is paving the way for autonomous processes, such as intelligent planning and touchless ordering. Eggers mentioned that these initiatives have facilitated uninterrupted operations at three manufacturing sites and one distribution centre.
Contrasting these perspectives, Michael DeWitt, vice president of Indirect Spend Management at Walmart, argued against the notion of waiting for perfect data before implementing new technologies. He stated, “Nobody’s data is good,” expressing that reliance on subpar data can hinder technological deployment. DeWitt highlighted the potential for technology to enhance data quality over time, citing Walmart’s experiences in employing AI for procurement, which include automating low-value contract negotiations through negotiation bots. Launched four years ago, these bots handle a large volume of negotiations, completing them in an average of 11 minutes. DeWitt noted that over 80% of suppliers prefer negotiating with bots, appreciating the less emotional, more fact-based nature of these interactions.
The consensus among these industry leaders underlines a critical understanding: establishing a solid data foundation is indispensable for unlocking the full potential of AI in supply chain transformation. As companies continue to adapt to the advancing capabilities of AI technologies, prioritising data management remains a strategic approach for achieving sustainable and impactful outcomes in the sector.
Source: Noah Wire Services
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