AI Optimization at O-I Glass: Better Quoting KPIs and Increased Sales Team Adoption

At O-I Glass, Inc. (NYSE: OI), they love glass and are proud to be one of the leading producers of glass bottles and jars around the globe. Glass is not only beautiful, it’s also pure, healthy, and completely recyclable, making it the most sustainable rigid packaging material. Headquartered in Perrysburg, Ohio (USA), O-I is the preferred partner for many of the world’s leading food and beverage brands.

They have a history of transforming how the world stores food and beverages – of making glass more accessible to more customers and consumers. They reimagine how glass is made and sold by innovating production techniques, pioneering recycling and sustainable technology, and unleashing the iconic, brand-building potential of this packaging that is the kindest material for the planet and its people.

Since 2018, they've been using Pricefx Quoting, and Analytics. The complete pricing solution was implemented globally, with a region-by-region rollout.

The effective implementation of AI in the pricing process is crucial for every business, and O-I Glass is no exception. They hadn’t used AI for the pricing process before, marking the beginning of their ongoing AI pricing journey.

The quoting process was identified as the most suitable area for AI implementation, as O-I Glass frequently engages in large and complex negotiations with major customers, demanding significant time and resources. Therefore, the primary benefit observed was that the AI models could be more robust, taking more attributes into consideration and achieving better results when optimizing quotes to better reach negotiations' goals. Before AI implementation, the models mostly used costs.

The initial challenge tackled at O-I Glass was the lack of differentiated pricing strategies during negotiations. It was noted that sellers across regions were not consistently implementing the company’s value-based pricing approach. This inconsistency led to missed opportunities to maximize profit and align prices with the perceived value of the products.

O-I Glass combined their own science with Pricefx Optimization  and workflow capabilities. They added internally developed AI/Statistical Pricing and Costing models, which run in real time within Pricefx.

They developed models to mathematically reflect its value-based pricing strategy, using Pricefx’s model workbench via “Bring Your Own Science” approach.

Using  machine learning models with various factors to gain visibility and calculate costs for new products in real time positively affects the day-to-work in quoting process.

The Pricing and Costing models use variables  such as volumes, product, and manufacturing attributes.

Sales teams preparing for negotiations can run various price optimization scenarios and see the real-time impact of changes on profitability.

The use of AI/ML models within Pricefx enables price optimization and ensures consistency for negotiation preparations. O-I Glass handles a mix of spot price decisions and long-terms customer agreements, using the same approach for both. Integrating in one place the outcome of multiple variables for price optimization helps. This would be much more complicated if every salesperson would use their own approach or use manual models or methodologies.

Effective pricing combined with AI is a game-changer for their businesses. O-I Glass ensured long-term adoption by sales teamsthrough a transparent AI-based solution. The glass box approach enhanced transparency for sales teams, providing visibility into pricing decisions compared to optimal pricing and real-time margin implications. This allows teams to see outputs from the model during quoting transparently to ensure long-term adoption and adequation with O-I Glass’s pricing strategy.

The high flexibility of the algorithm resulted in optimized margins.

The model was implemented quickly, and delivering value swiftly and having a direct impact on the bottom line. Additionally, models can be easily updated within Pricefx thanks to “Bring your own science” approach.