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Shelf Life: Expert Voices from the Consumer Goods Industry - The Potential & Pitfalls of AI in the Consumer Goods Industry with Lasse Holmstedt

The Potential & Pitfalls of AI in the Consumer Goods Industry with Lasse Holmstedt

05/09/24 • 25 min

Shelf Life: Expert Voices from the Consumer Goods Industry

AI in supply chains isn't just about crunching data—it's about creating bridges between complex info and everyday decision-making.
In this episode, Lasse Holmstedt, VP of Engineering at Alloy.ai, joins us to discuss the dynamic role of generative AI and large language models within the consumer goods sector. Throughout the conversation, we delve not only into the innovative application of AI technologies that encompass forecasting and data harmonization but also highlight the critical importance of maintaining clean and accurate data for AI effectiveness.
Listen in for a deeper understanding of the potential and pitfalls of using pre-trained AI models. Along the way we’ll also explore strategies to safeguard sensitive business data and discover how AI can transform sales and demand planning processes.
Three Key Takeaways:

  • Explore leveraging textual and qualitative data in addition to numerical approaches to enhance decision-making processes while mitigating risk
  • Consider applications of AI for enhanced visibility and predictive capabilities in inventory management, forecasting, and cross-platform product matching for more efficient operations
  • Establish a clear data governance framework to ensure that data fed into AI systems is accurate, up-to-date, and free from errors, laying a solid foundation for reliable AI outputs
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AI in supply chains isn't just about crunching data—it's about creating bridges between complex info and everyday decision-making.
In this episode, Lasse Holmstedt, VP of Engineering at Alloy.ai, joins us to discuss the dynamic role of generative AI and large language models within the consumer goods sector. Throughout the conversation, we delve not only into the innovative application of AI technologies that encompass forecasting and data harmonization but also highlight the critical importance of maintaining clean and accurate data for AI effectiveness.
Listen in for a deeper understanding of the potential and pitfalls of using pre-trained AI models. Along the way we’ll also explore strategies to safeguard sensitive business data and discover how AI can transform sales and demand planning processes.
Three Key Takeaways:

  • Explore leveraging textual and qualitative data in addition to numerical approaches to enhance decision-making processes while mitigating risk
  • Consider applications of AI for enhanced visibility and predictive capabilities in inventory management, forecasting, and cross-platform product matching for more efficient operations
  • Establish a clear data governance framework to ensure that data fed into AI systems is accurate, up-to-date, and free from errors, laying a solid foundation for reliable AI outputs

Previous Episode

undefined - The Mindset and Tactics that Drive Growth for Consumer Brand Startups with Ember's Zach Horton

The Mindset and Tactics that Drive Growth for Consumer Brand Startups with Ember's Zach Horton

In this episode, we’re joined by Zach Horton, Senior Director of Logistics and Supply & Demand Planning at Ember Technologies, Inc. From handling Ember's exponential growth to integrating cutting-edge technology into the heart of their supply chain, Zach shares invaluable insights on the role of AI, the essence of culture, and the art of innovative product development.
Tune in to learn not just how to plan for the future but to shape it with wisdom, agility, and the invaluable FIO (figure it out) mindset. Because in today's fast-paced world, it's not just about the product—it's about the people you serve and the team that drives you. Stay ahead of the curve with us, right here, on the Shelf Life Podcast.
Three Key Takeaways:

  • The implementation of a robust sales and operations planning process is pivotal for successful startup growth, promoting transparency and accountability
  • AI holds the promise to revolutionize planning and analysis, offering a glimpse into future consumer products industry advancements
  • F.I.O - Figure It Out: champion a proactive work culture and encourage your team to embrace challenges with an innovative spirit

Next Episode

undefined - Easy Ways to Use POS Data to Sell More and Avoid Inventory Problems with Alloy.ai's Manfred Reiche

Easy Ways to Use POS Data to Sell More and Avoid Inventory Problems with Alloy.ai's Manfred Reiche

What comes to mind when you hear the words ‘sales data’?
Alloy.ai’s resident expert on all things related to retail data, Manfred Reiche, says there’s a whole realm of information you’re likely missing out on when it comes to the sales data bucket. In this episode, we delve into the intricacies of point-of-sale data and its transformative impact on the consumer goods industry.
Listen in as we explore the critical role of data analysis in uncovering regional problems, managing inventory, and enhancing decision-making across various company sizes. From the importance of granularity in data to the necessity of breaking down silos within organizations, this discussion promises to shed light on how businesses can leverage vast data sets to drive success.
Three Key Takeaways:

  1. Accumulating data isn't enough, the key is to convert it into insights that drive action and that’s where granularity and AI play pivotal roles
  2. Encourage cooperation between different business units - breaking down silos can lead to more synchronized decision-making and better use of POS data
  3. Transition from traditional methods to using real-time POS data for forecasting to better predict market behaviors and enhance supply chain decisions

Shelf Life: Expert Voices from the Consumer Goods Industry - The Potential & Pitfalls of AI in the Consumer Goods Industry with Lasse Holmstedt

Transcript

Speaker 1

From Alloy AI . This is Shelf Life .

Speaker 1

Is generative AI really a game changer for the industry , or is it mostly hype ? What are the strengths and or is it mostly hype ? What are the strengths and shortcomings of AI platforms ?

Speaker 1

How risky is it to share your company's data with an AI platfor

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