In an era where digital transformation is crucial for competitive advantage, few companies have embraced artificial intelligence with as much fervor and measured success as Avery Dennison. Under the guidance of CIO Nick Colisto, the company has strategically woven AI into its operations, achieving significant productivity and financial gains. Today, we’re discussing this impressive journey with Vernon Yai, a data protection expert who deeply understands the need for robust frameworks in deploying cutting-edge technologies like AI.
Can you explain Avery Dennison’s culture-first approach to AI adoption? What were the key elements that contributed to its success?
Avery Dennison’s culture-first approach truly set the foundation for its AI transformation. They focused on integrating AI into the existing company culture by emphasizing training and the concept of “humans in the loop.” By ensuring employees understood and embraced AI, it wasn’t just about adopting new technology but also about enhancing collaboration and engagement with AI projects across all levels of the organization.
How did Avery Dennison engage its executives and employees in AI pilot projects? What strategies were used to encourage participation?
Participation was encouraged by involving both executives and a large number of employees—over 250 executives and 1,000 employees—in AI pilot projects. This was achieved through targeted strategies like executive-driven initiatives and direct engagement during training sessions and workshops. By launching 20 AI pilot projects, employees could see firsthand the tangible benefits and feel a personal investment in AI’s success.
What does “humans in the loop” mean in the context of your AI strategy?
“Humans in the loop” is crucial for maintaining oversight and adding value to AI processes. It ensures that AI serves as a tool to augment human decision-making, rather than replace it. In the context of Avery Dennison, this meant creating systems where human judgment is an integral part of AI outcomes, thus fostering trust and acceptance among users.
Could you share some examples of the AI innovations developed in-house and the financial benefits they have brought to Avery Dennison?
Avery Dennison developed several impactful AI innovations, such as enhanced inventory forecasting and predictive maintenance. These innovations have significantly contributed to financial savings by optimizing processes, reducing errors, and decreasing operational costs. For instance, their tailored demand forecasting system greatly improved accuracy, which directly translated into cost reduction for inventory management.
Avery Dennison has achieved a 10-hour monthly savings per employee with Google Gemini. What processes or tasks were optimized to achieve this?
With Google Gemini, Avery Dennison optimized a variety of routine processes across the company. This included enhancing productivity tools used in day-to-day tasks and incorporating AI-driven solutions into workflows, which saved each employee an average of 10 hours per month. This efficiency gain underscores the value of deeply integrating AI tools into daily operations.
How did you manage to achieve a 37% adoption rate initially, and how has this rate grown since then?
The initial 37% adoption rate was achieved through strategic rollouts of AI training, creating awareness, and demonstrating quick wins to build momentum. Over time, as the company witnessed real impacts and benefits, the adoption rate naturally increased, driven by growing internal demand and continued education and support.
Could you elaborate on Project Loop and its impact on AI implementation at Avery Dennison?
Project Loop emphasized the importance of maintaining human oversight in AI processes, reinforcing the “humans in the loop” concept. This initiative led to the development of numerous AI projects, earning Avery Dennison significant recognition and awards. It facilitated the integration of AI in a structured manner, ensuring that employees remained central to AI-driven changes.
What role did education, training, and collaboration play in driving AI adoption across the company?
Education and training were pillars of Avery Dennison’s AI adoption strategy. By establishing the Digital Innovation Center of Excellence (DICE) and offering a comprehensive IT Academy, the company equipped its workforce with the necessary skills. Collaboration was encouraged by fostering an open environment where ideas could be shared and developed into actionable projects.
How did the Digital Innovation Center of Excellence (DICE) and IT Academy contribute to upscaling your workforce for AI readiness?
DICE and the IT Academy were instrumental in preparing the workforce for AI implementation. They provided employees with the knowledge and tools necessary to understand and leverage AI, enabling them to participate actively in AI projects and contribute to the company’s digital transformation objectives.
What was the significance of ideation sessions and brain “writing” exercises in identifying viable business use cases for AI?
These sessions and exercises were crucial in unlocking creativity and identifying potential business cases for AI. By generating and refining ideas collaboratively, Avery Dennison was able to pinpoint, prioritize, and develop projects that aligned with real business needs and opportunities for innovation.
Can you describe some of the generative AI pilots during 2024 that were impactful to business processes?
In 2024, Avery Dennison launched various generative AI pilots that had significant impacts, including enhancing maintenance, operations, customer engagement, and workplace safety. These pilots improved productivity across the board and provided substantial value by streamlining processes and reducing costs.
How did Avery Dennison leverage commercial-grade AI tools from Google and other major AI partners?
Avery Dennison strategically partnered with major AI platforms like Google to leverage their commercial-grade tools. By utilizing proven technologies, the company avoided the complexities and risks associated with developing in-house AI solutions, allowing it to rapidly implement effective AI tools across its operations.
What is the rationale behind the strategy of leveraging established platforms instead of developing AI solutions in-house?
Leveraging established platforms allows Avery Dennison to benefit from extensive research and development investments by leading tech companies. This approach minimizes risk, accelerates deployment, and ensures access to cutting-edge technology without the overhead of developing and maintaining proprietary systems.
Can you share insights on Project Prophesy and how it improved demand forecasting at Avery Dennison?
Project Prophesy exemplifies Avery Dennison’s innovation in demand forecasting. By integrating diverse external data sets, the custom AI application significantly reduced forecasting errors and optimized inventory management. This project was pivotal in improving efficiency and reducing financial exposure due to stock imbalances.
What specific external data sets contributed to the success of inventory forecasting optimization, and how were they integrated?
The success of the forecasting system hinged on integrating diverse external data, including shipping data, weather forecasts, and economic indicators like GDP statistics. These data sets were carefully selected and fed into the AI models, enhancing their predictive accuracy and providing actionable insights for inventory management.
How have improvements in inventory forecasting translated into financial savings for the company?
The improved forecasting capabilities have led to substantial financial savings by reducing overstock and stockout situations. Accurate demand predictions allowed for better inventory management, which decreased excess inventory costs and improved cash flow by optimizing stock levels company-wide.
Which regional AI pilot projects have driven measurable operational improvements and customer engagement?
In regional AI pilots, Avery Dennison achieved notable successes such as in India and Latin America. In India, predictive maintenance minimized downtime, while in Latin America, customer engagement improved through advanced purchase prediction models, increasing revenue predictability and enhancing customer relations.
Could you discuss VelocityEHS ergonomics platform and how it impacted workplace safety?
The VelocityEHS ergonomics platform proved a crucial element in enhancing workplace safety at Avery Dennison. By identifying high-risk tasks and mitigating injuries before they occurred, the platform contributed to a safer work environment while simultaneously improving productivity by minimizing work disruptions.
What are the plans for scaling successful AI solutions globally at Avery Dennison?
Avery Dennison plans to scale successful AI solutions by expanding their implementation across global sites. This involves not only broadening the reach of proven models but also continuing to innovate to adapt these solutions to different regional needs, enhancing consistency and efficiency across the organization.
How does Avery Dennison measure the outcomes of its AI initiatives and ensure ongoing innovation?
To measure outcomes accurately, Avery Dennison establishes clear metrics for success and closely monitors performance against these benchmarks. Continuous innovation is encouraged through a culture of experimentation, feedback loops, and an iterative approach to project development, ensuring solutions evolve with business needs.
Do you have any advice for our readers?
In the realm of AI, adopting a culture where continuous learning and adaptation are prioritized is crucial. Companies should aim to integrate AI in ways that complement and enhance human capabilities rather than replace them, ensuring that technological investments support long-term strategic goals.
