Case Study: How AI is Transforming Procter & Gamble’s Global Operations


Procter & Gamble (P&G), a global leader in consumer goods, has been at the forefront of integrating modern technology into its operations. With over 120 manufacturing sites in over 40 countries, the company’s digital journey commenced approximately seven years ago. Jeff Kent, the vice president of Smart Platforms Technology & Innovation, along with other key leaders, has been steering the company towards full-scale digitalization.

Key Takeaways

  • P&G’s digitalization drive aims at major operational improvements: increasing staffing efficiency, slashing maintenance and QA costs, and enhancing overall manufacturing processes.
  • The company has introduced the WISE initiative and the SmartBox, an edge device, to harness AI and machine learning at the equipment level.
  • AI, in collaboration with data simulations and partnered platforms like Microsoft, has significantly improved P&G’s manufacturing processes, most notably in the production of Pampers.

Deep Dive: How AI is Transforming Procter & Gamble’s Global Operations


Procter & Gamble has acknowledged the profound potential of AI and machine learning as pivotal elements in production digitalization. This recognition paved the way for the inception of the WISE initiative and the deployment of the SmartBox edge device, central pillars in the company’s AI implementation strategy. Alongside these advancements, the company instituted the Manufacturing Machine Learning (ML) Lifecycle, a structured approach designed to seamlessly integrate and optimize AI applications in their operations.


Procter & Gamble employs the SmartBox device to amass data from a myriad of controls and equipment, ensuring that information flows in real-time and is seamlessly integrated with cloud applications. This adoption of technology is accentuated by the company’s collaboration with industry forerunners, such as Microsoft, in their endeavor to craft robust AI models. In a notable application within Pampers manufacturing, these AI models are adeptly trained using an amalgamation of both genuine and simulated data, maximizing their efficiency and accuracy.


Procter & Gamble has witnessed remarkable advancements in its manufacturing operations, most notably an impressive 80% reduction in glue-related waste during the production of Pampers. This transformation is bolstered by the incorporation of real-time alert systems, allowing for an immediate response to any manufacturing anomalies, thereby ensuring the consistent quality of the product.

Challenges and Barriers

In P&G’s journey towards manufacturing excellence, certain challenges have emerged. Although production errors had high associated costs, they occurred infrequently, resulting in their underrepresentation in the training data. This posed a significant hurdle for the AI-driven approach. Additionally, the limitations of the traditional Purdue model in the system architecture necessitated a move towards a more open and communicative structure. One of the intricate challenges included maintaining flawless consistency in intricate processes, such as the 40 distinct glue streams essential for manufacturing Pampers.

Future Outlook

P&G is set on transforming its architectural approach by moving away from the constraints of the traditional Purdue model, aiming for a more open and interconnected system. Central to this transformation is their continued emphasis on OPC UA, recognized for its crucial role in bridging the communication between OT and IT. Ambitiously, P&G has its sights set on implementing these advancements across all 120 of its factories within the span of a year.


Procter & Gamble’s commitment to AI and machine learning showcases the transformative potential of these technologies in manufacturing and operations. By integrating cutting-edge solutions and moving beyond traditional paradigms, P&G stands as a testament to the power of digital innovation in reshaping industries. Through continuous collaboration, research, and dedication, the company sets the stage for a brighter, more efficient future in the realm of consumer goods.

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