[Posted on LinkedIn]
Here is the article: http://www.adweek.com/digital/blinded-by-data-science/
I bet Nike accelerated ROI from their customer data by years by buying Zodiac.
Here’s the typical path…
Execs read that Data Science is hot, so they start to build out a small team. Some value is seen, but putting models into production, specifically ones with high data volume, velocity, and variety (e.g., Customer-related data) poses a significant engineering challenge. It’s hard.
It’s why Uber built Michelangelo, their ML platform. Putting this apps into production is hard. It seems to have taken Uber ~1.5 yrs to build Michaelangelo and I’m sure it’s constantly evolving, as it has a dedicated product team assigned to it.
By acquiring Zodiac, Nike inherits a Data Science platform or toolset centered around Customer data. Plus they get some (presumably good) data science talent, which is seemingly scarce. They’ve accelerated initiatives by a year+.
“Before analysts can crunch the data, apply machine learning and deliver new insights, brands need engineers who know how to store, manage and clean the data. And they need tech-savvy communicators who can take that analysis and translate it into business reality, Purcell says.”
SYNTASA can help you with this in less than one month!