VIDEO | Advanced Auto Parts VP of Enterprise AI: We Leverage AI for Cost Saving and Efficiency

(US and Canada) Yvonne Li, VP of Enterprise Artificial Intelligence, data Engineering and Decision Science at Advanced Auto Parts, speaks with Michael C. Fillios, Editorial Board Member, Founder & CEO, - IT Ally, in a video interview about leveraging data and AI in the automotive industry, the impact of using data for prediction, and provide personalized customer experience.

Li begins by shedding light on her educational background in organizational behavior and psychology and taking additional machine learning and AI courses during her Ph.D. She adds that her passion for data led her to the field of data and AI while her background adds a different perspective when interpreting results. Li mentions that leveraging data to explain and predict human behaviors and outcomes fascinates her.

Commenting on her current role at Advanced Auto Parts, she states that there is great potential to drive forward new initiatives with data and artificial intelligence. Additionally, she looks forward to advancing the transformation of the organization while leveraging data and AI. Delving deeper, she discusses the duties of the current role which involves resetting the function's purpose and understanding how it adds value. She adds that she is constructing the function from the ground up.

Further, Li reveals that her company leverages data and AI to precisely predict shipment volumes arriving at distribution centers. This helps the business plan its labor better, saving costs and boosting productivity across all 45 distribution centers in the U.S. She asserts that the results have been positive so far, and the company is pleased with the cost savings and efficiency it provides.

Li opines that modernizing the company has changed how the industry is viewed and understood. She recommends using data and AI for supply chain management and personalization, and shares that the team performed a test to predict customer purchase habits. The test allowed them to send personalized messages to entice customers when they needed certain items.

Li has figured out that customers appreciate personalized messaging, respond positively, and eventually become loyal customers. She also mentions leveraging data to suggest additional products customers may need to complete a task.

Then, Li explains that her team focuses on providing customers with the best car care expertise and knowledge possible. She affirms that advanced technologies such as natural language processing (NLP) can help improve customer satisfaction by providing more tailored store assortments according to purchase decisions.

Concluding, Li advocates deploying this approach as it enables customers to get what they want as and when they need it. It equally proves the significance of using data-driven strategies to serve customers better.

CDO Magazine appreciates Yvonne Li for sharing his insights and data success stories with our global community.