- Consumer Packaged Goods
- SKU Optimization
- Data Science
SKU Rationalization, also known as SKU Optimization or SKU Reduction, is a continuous process in the CPG industry used to assess product portfolios with the aim to decrease complexity, prioritize profitable items, and increase space for innovation. With the massive expansion of rich market dataset availability and a proliferation of powerful data and analytic tools, we can use Machine Learning at-scale to be smarter, more responsive and more data-driven in approaching SKU Rationalization.
In this recorded webcast, Thorogood Consultants Deb Lee and Ben Dunmire outline our experiences with SKU Rationalization Machine Learning initiatives to appreciate the key business drivers and key technology approaches that enable effective implementations. They discuss the value of reliable data pipelines built upon a deep understanding of data and business operations, the role of Machine Learning and AI, and common approaches to grow and nurture data solutions.
What we cover:
Drawing from client experiences, we explore:
- Common architecture design patterns featuring data engineering, data science, and data visualization components.
- Key business drivers and how we can ensure alignment to business operations when delivering decision-making systems.
- Our approach to using data and analytic technology and methodologies to help customers leverage Machine Learning in SKU Rationalization and other initiatives.
Is it for you?
- Are you looking to start or recently started a SKU Rationalization initiative and establishing a vision?
- Have you been exploring modern technologies and techniques to revamp your SKU Rationalization system?
- Would you like to learn about the business value of SKU Rationalization, and how Machine Learning at-scale can support decision making?