Faster to update product hierarchy
managed daily
Region: EMEA
Industry: Retail and Consumer Goods
Department: IT
Company Background:
Amway is an American multi-level marketing company that sells health, beauty, and home care products. The company was founded in 1959 by Jay Van Andel and Richard DeVos and is based in Ada, Michigan. Amway and its sister companies under Alticor reported sales of $8.9 billion in 2019.
Data Stack: Google Cloud, Google Cloud Dataprep, and BigQuery.
Amway manufactures over 450 different nutrition, beauty, personal care and home products, each of which needs to be carefully categorized and organized in its product hierarchy. Updates to the hierarchy need to be made daily as categories expand, business lines evolve, and new products develop. However, Amway’s original desktop-based model was complex and required numerous manual updates, ultimately proving itself slow and unsustainable. Amway smoothed out some of these kinks after switching to a virtualization solution, but the solution’s SQL-based transformations required too much hand-holding 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.
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—whereas 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. Plus, 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.
Amway was able to reduce time spent making changes to its product hierarchy from 2-3 days down to 5-7 minutes
Amway’s engineering team has been freed up to focus on more complex deliverables instead of responding to data requirements
Amway analysts can now obtain data at different hierarchy levels and, using their unique business knowledge, remodel the hierarchy for the most profitable option
Amway is the world’s largest direct selling company* ($8.8B reported sales, 2018). It manufactures and distributes nutrition, beauty, personal care and home products, which are exclusively sold in 100 countries through Amway Independent Business Owners (IBOs).
Supply Chains to Data Pipelines: Modern Retail Analytics
We can update daily—it’s allowed us to reduce that time-to-insight as far as making changes. Because as you know, the product hierarchy needs to be updated daily. We have new items coming in and new changes to items, and, through this process, we can allow this to happen in a rapid way. … We don’t have to rely heavily on any technical staff to make this happen.
Kevin Schaefer
Sr. Data Engineer
Amway
Region: EMEA
Industry: Retail and Consumer Goods
Department: IT
Company Background:
Amway is an American multi-level marketing company that sells health, beauty, and home care products. The company was founded in 1959 by Jay Van Andel and Richard DeVos and is based in Ada, Michigan. Amway and its sister companies under Alticor reported sales of $8.9 billion in 2019.
Data Stack: Google Cloud, Google Cloud Dataprep, and BigQuery.
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