Feeding The Cognitive Enterprise: Nestlé Pushes AI, Predictive Maintenance and Robotics
Day One of Informa Tech’s AI Summit in London saw Nestlé’s global product director for new generation technologies provide an in-depth look at AI’s potential to transform the multinational corporation.
Carolina Pinart, the lead for Nestlé’s AI program, said intelligence was driving progress toward the corporate’s three key strategic objectives: enhanced efficiency, digitized operations and sustainability. The latter target is with a view of achieving Nestle’s goal of net zero carbon emissions by 2050.
“If we look into Nestlé’s progress last year, we made really solid progress on our structural savings program across all areas of manufacturing, procurement and administration, with massive opportunities for automating and AI,” said Pinart.
Pinart stressed that all three initiatives had enabled Nestlé to leverage AI, predictive maintenance and robotics to support factory automation and customization on the assembly line.
Nestlé is also striving to expand the flow, accessibility and utility of real-time data as it is collected from operational technology networks, both in supply chain management and procurement operations.
“These efforts support our drive to enhance consumer and customer centricity, which is a paramount objective for our company, as well as manufacturing, flexibility, agility and also transparency and traceability across the supply chain,” Pinart explained.
Since 2019, Nestlé has sought to transform its business into a “cognitive enterprise”, with unbiased machine learning tools that can be extensively used to help automate, respond, react and decide business outcomes.
Through machine learning, the mission statement set out by the company underscores its commitment to derive more value for its employees and customers, as well as society and its shareholders.
By 2025, Nestlé aims to be fully data-driven and cognitive in its approach. It is currently working to define corporate directives for AI as part of its global program, which also covers topics such as ethics, organization, technology, education and communication.
“Without the global program, we might get there eventually but certainly not at the speed that we want.”
The global program runs together with multi-year strategic initiatives to automate operations and improve the experience of its workforce, through data, analytics and other technologies.
“These programs leverage AI and machine learning where appropriate as a toolbox to solve business challenges,” Pinart explained.
Pinart believes deployment of AI in Nestle’s global supply chain must start with a strategic analysis of the intended outcomes, followed by work to identify real use-cases where AI can be prioritized, deployed and scaled.
Also vital for Nestle’s implementation strategy was identifying the foundational data for AI to be trained on as well as other tech capabilities.
Pinart said: “We are working on creating data assets and having the right platforms in place to really support the strategy and use-cases.
“[Another] question is around organization and talent – that varies depending on what we’re trying to do with AI. We don’t have a single operating model – but the question is, what is the right operating model to run all of this.”
“Finally governance, AI raises concerns on people. So both consumers and business leaders are employees as well, right? So how do we address those concerns.”