Providing the right products at the right time with machine learning

Summary:
Kraft Heinz uses AI and machine learning to optimize supply chain operations and better serve customers in the CPG sector. Jorge Balestra, their head of machine learning operations, emphasizes the importance of well-organized and accessible data in training and developing AI models. The cloud provides agility and scalability for these initiatives, and partnerships with companies like Infosys help bring in expertise and skills for their digital strategy. The company focuses on adaptability and agility to leverage technology in achieving its mission of delighting people via food.

End of summary.

 Providing the right products at the right time with machine learning

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AI Solutions for Middle Managers

AI Solutions in Consumer-Packaged Goods (CPG) Sector

Whether your favorite condiment is Heinz ketchup or your preferred spread for your bagel is Philadelphia cream cheese, ensuring that all customers have access to their preferred products at the right place, at the right price, and at the right time requires careful supply chain organization and distribution. Amid the proliferation of e-commerce and shifting demand within the consumer-packaged goods (CPG) sector, AI and machine learning (ML) have become helpful tools in enabling efficiency and better business outcomes.

Deploying Machine Learning Operations (MLOps) with Data

The journey toward successfully deployed machine learning operations (MLOps) starts with data. Curating well-organized and accessible data means enterprises can leverage their data volumes to train and develop AI and machine learning models. A strong data strategy lays the foundation for these AI and machine learning tools to use data to detect supply chain disruptions, identify and address cost inefficiencies, and predict demand for products.

Challenges in the CPG Sector

Data within the CPG sector is often incomplete given the inconsistent methods for consumer habit tracking among different retailers. Deploying AI and machine learning tools at scale requires turning to the flexibility of the cloud to allow for much-needed data accessibility while mitigating compute power.

Practical Use of Cloud for AI and Machine Learning

Using the cloud can allow for much-needed data accessibility while mitigating compute power. The agility of the whole thing increases exponentially because what used to take months, now can be done in a matter of seconds via code. This explosion around analytics and AI is possible because of cloud powering all of these initiatives.

AI and Machine Learning in Action

AI and machine learning tools can help in detecting supply chain disruptions, identifying and addressing cost inefficiencies, and predicting demand for products in the CPG sector. They play a crucial role in ensuring the right product is available at the right price and the right location for consumers.

Partnerships for AI Success

Partners like Infosys are key enablers, bringing in new ideas, new technology, and the right level of expertise. An expert ecosystem is necessary for success in deploying AI and machine learning solutions.

Preparing Data for AI Projects

The potluck approach for data has been successful, where individual projects contribute to the larger data strategy without being a burden. This has helped Kraft Heinz to make enterprise data more accessible and eventually reuse it for various projects.

Future of AI in the CPG Sector

Adaptability and agility will be crucial for the future of AI in the CPG sector. Leveraging existing and future technology to get the right product at the right price, at the right location is the focus for Kraft Heinz.



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