CEOs Increasingly Talk Up Supply Chain Data Mastery. But the Question Is Still “How”
Our research reveals a 13% surge in CEO discussions of data-driven supply chain strategies, yet 68% of line-of-business leaders don't track data value. We explore how companies like Danone are translating data mastery into measurable business wins.
The Data
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Zero100 analysis found that 36% of CEOs are discussing data-driven supply chain strategies (a 13% YOY increase between January 2022 and July 2024).
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87% of technical leaders say AI advances make data management a higher priority and 95% emphasize an increased need for trustworthy data.
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Salesforce research found 68% of line-of-business leaders fail to track data monetization value and 41% report misalignment between data strategy and business objectives.
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Walmart, Pokka, and Danone illuminate “the how” of putting data strategies into practice through the use of AI and prioritizing talent buy-in.
Data Drives Performance
Technical leaders, such as chief technology officers and IT directors, are prioritizing data management as AI capabilities expand. According to a Zero100 survey, 95% of these leaders believe trustworthy data is needed now more than ever before. And, unsurprisingly, CEO engagement mirrors this trend: Our analysis shows a 13% YOY rise in data strategy discussion between January 2022 and July 2024.
Recent earnings calls highlight concrete results: PVH cut inventory by 22% YOY through data-driven product development, while 3M leveraged data analytics to streamline customer service operations. Despite this, Salesforce research shows 68% of line-of-business leaders neglect data monetization tracking and 41% report minimal alignment between data strategy and business goals. So, what exactly are the companies seeing results doing to close the gap between talk and progress?
Mindset, Tech, and Talent
Companies winning at data execution in supply chain focus on three key areas:
1. Cross-functional Integration: Procter & Gamble CEO Jon Moeller champions an "unsiloed" approach, pushing beyond functional optimization toward end-to-end supply chain integration with retailers. Walmart's SKY project demonstrates this in action through AI implementation.
2. AI-Powered Data Enhancement: Companies now deploy AI to generate and validate training data, improving foundational models. Pokka mapped carbon footprints across 5,000 SKUs with 95% accuracy in under 100 minutes using AI algorithms.
3 . Talent Engagement: Danone transformed low participation in master data management training by rebranding it as an "Analytics Bar,” combining coffee and data analysis to boost program enrolment.
The Takeaway
Success demands action across three fronts:
Technology: Deploy AI tools strategically, whether through vendor partnerships or internal capability building. Prioritize data governance and cybersecurity while experimenting with AI for data cleansing, collection, and process optimization.
Mindset: Build cross-functional data integration capabilities. Secure leadership buy-in and establish connected organizational structures to enable advanced processes like Regenerative Business Planning.
Talent: Develop human-machine teams through targeted training. Use side-by-side AI simulations to demonstrate concrete performance improvements and build data fluency across the organization.
Methodology
Zero100’s proprietary data and analytics are a combined effort between our data scientists and research analysts. We provide data-first insights matched with our own research-backed points of view and bring this analysis to life via real-world case examples being led by supply chain practitioners today.
For this study, we surveyed the Zero100 community and analyzed 1,9343 earnings calls transcripts from 215 global brands companies between January 2022 and July 2024.