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SAS
Penske AutomotivePenske Automotive Brings Feature Pipelines onto SAS
Penske Automotive, a consumer discretionary organization in the United States, uses SAS Customer Intelligence from SAS to support applied machine learning for data scientists and ML engineers.
Penske Automotive standardized feature pipelines on SAS instead of keeping parallel copies.
“Inside Penske Automotive, applied machine learning used to depend on whoever still had the latest file.”
“Data scientists and ML engineers needed a system that would still make sense after the original project team moved on.”
Independent write-up. Figures come from public sources or are illustrative.
Value results
| Category | Value result |
|---|---|
| Productivity | Fewer stalled items because feature pipelines has a clear owner |
| Risk and compliance | SAS Customer Intelligence is the governed place data scientists and ML engineers use for applied machine learning |
| Capability | New joiners can see how applied machine learning actually runs |
Story
Inside Penske Automotive, applied machine learning used to depend on whoever still had the latest file. That pattern is common in consumer discretionary groups working out of the United States. Data scientists and ML engineers needed a system that would still make sense after the original project team moved on.
Penske Automotive uses SAS Customer Intelligence from SAS as the working layer for feature pipelines. SAS provides analytics and AI software used for statistics, risk, customer intelligence, and decisioning in regulated industries. The practical change is simple: applied machine learning has a home, and reviews happen there instead of in a forwarded thread.
Nothing in this writeup invents a savings number. What Penske Automotive gets from SAS is a durable place to run applied machine learning and a way for data scientists and ML engineers to see the same feature pipelines at the same time.
