Nike Customer Success Story

Nike Client Success Story

Industry/ sector:

Supply chain

Consultant name:

Sandeep Makhija

Customer name:

Nike

Location:

Hilversum, Netherlands

Website of the customer:

https://www.nike.com/nl/en/

Software solution implemented:

Lead DevOps Consultant

Project start date:

01-05-2019

Project end date:

14-12-2021

Client Business

Nike is a multinational corporation known for its extensive range of high-quality sports footwear, apparel, equipment, and accessories. As a market leader in the athletic and sportswear industry, Nike focuses on innovation in product design and development, catering to both professional athletes and casual fitness enthusiasts. Their business extends into digital realms, including e-commerce and digital platforms, aimed at enhancing customer experiences and engagement.Working alongside Nike’s data scientists, we identified the need for dynamic machine learning models capable of evolving and adapting over time. The initial challenge was to develop these models to accurately analyse customer data and provide relevant recommendations. However, the larger, ongoing task was to ensure these models could adapt to changing customer behaviours and preferences, thus requiring continuous monitoring, testing, and refinement.

Challenges

Nike faced challenges in managing and processing their extensive data, crucial for informed decision-making and customer engagement strategies. Their existing data infrastructure was not fully capable of handling the scale and complexity of the data they were accumulating, leading to inefficiencies in data handling and analytics. Additionally, Nike needed to improve their data-driven insights to enhance product development, marketing strategies, and customer experiences.

Working alongside Nike’s data scientists, we identified the need for dynamic machine learning models capable of evolving and adapting over time. The initial challenge was to develop these models to accurately analyse customer data and provide relevant recommendations. However, the larger, ongoing task was to ensure these models could adapt to changing customer behaviours and preferences, thus requiring continuous monitoring, testing, and refinement.

Why BCG solutions

To address these challenges, our solution involved creating a self-service infrastructure for data engineers and data scientists using a microservices architecture and development in AWS. This allowed for more flexible and scalable data processing capabilities. We implemented a series of AWS tools, including AWS Glue for data integration and Snowflake for data warehousing, to streamline data processing and analytics. Additionally, we focused on automating deployments using Jenkins and managing Kubernetes (k8s) charts with Helm, facilitating continuous delivery and improved operational efficiency.

Benefits

The implementation of this solution brought several benefits to Nike. The new data infrastructure significantly enhanced their ability to process and analyse large datasets efficiently, providing quicker and more accurate insights for decision-making. This improved data processing capability allowed Nike to better understand customer behaviour and market trends, leading to more informed product development and targeted marketing strategies. The use of AWS and microservices architecture also provided the flexibility and scalability needed to support Nike's continued growth and innovation in the dynamic sports and fitness industry.

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