Technology Category
- Infrastructure as a Service (IaaS) - Cloud Databases
Services
- Cloud Planning, Design & Implementation Services
About The Customer
Amway is the world’s largest direct selling company with reported sales of $8.8 billion in 2018. The company manufactures and distributes nutrition, beauty, personal care, and home products. These products are exclusively sold in 100 countries through Amway Independent Business Owners (IBOs). The company is known for its vast range of products, each of which needs to be carefully categorized and organized in its product hierarchy. This hierarchy is dynamic and requires daily updates as categories expand, business lines evolve, and new products are developed.
The Challenge
Amway, a multi-level-marketing company, manufactures over 450 different nutrition, beauty, personal care, and home products. Each of these products needs to be meticulously categorized and organized in its product hierarchy. The hierarchy requires daily updates as categories expand, business lines evolve, and new products develop. However, Amway’s original desktop-based model was complex and required numerous manual updates, proving itself slow and unsustainable. Amway attempted to smooth out some of these issues by switching to a virtualization solution, but the solution’s SQL-based transformations required too much involvement from the engineering team. Analysts and engineers had to communicate back and forth about data requirements until, days later, the outcome produced was as expected. Neither solution allowed for flexibility nor agile changes to the product hierarchy.
The Solution
Amway migrated its data to Google Cloud BigQuery and centered its product hierarchy around Dataprep. The transition to a cloud-based, self-service data engineering technology has dramatically reduced time-to-insight. Before, Amway would have to wait two to three days before a change could be realized, now it’s a matter of minutes. Much of this acceleration is credited to Dataprep’s ease of use. Analysts can easily obtain product hierarchy data and make direct changes without communicating back-and-forth with engineers. Additionally, Dataprep has improved visibility into the product hierarchy with clear audit trails and data lineage. The result is a more streamlined and agile product hierarchy that can quickly respond to new changes each day.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.