When you think of Fortune 500 titan GE, what comes to mind? Innovation? Technology? Engineering and design? One thing that probably isn’t top of mind is data. But just imagine the incredible amount of data a company of GE’s size and stature acquires daily.
The Data Problem: Data is Siloed and Plagued with Inaccuracies
If you’ve worked with data before, you know that it comes from many sources and in varying formats, making it a challenge to merge, organize, and verify for accuracy. This is especially challenging when you’re dealing with 8 or so different business units spanning across various locations and all with distinct product lines like GE.
It’s easy for there to be many duplicate data entries for the same product, especially when name variations come into play. For example:
“two centimeter brushed ball bearing” vs “2cm bb”
The above is just one example of the same product having two different names, thus appearing in the data as different records when they should be combined into one.
This seemingly harmless data discrepancy is actually a big problem for a company like GE that relies on economies of scale to optimize spend with their suppliers. The more units they purchase, the less each unit costs. But their data told a fragmented purchasing story and they weren’t able to understand their purchasing history.
The Data Solution: Data Unification Through Machine Learning
With the help of Tamr, GE was able to unify and fully make sense of their data for the first time. Tamr’s platform processes siloed, “unclean” data records and identifies the discrepancies:
“Tamr was able to take hundreds of thousands of GE supplier records and identify where multiple records were actually from the same supplier,” Emily Galt, Vice President of Technical Product Management for GE Digital Thread told Fortune.
The secret to Tamr’s magic lies in machine learning. Machine learning relies on human expertise, especially in the beginning as it gets up and running. GE appointed a business expert that worked closely with Tamr to teach it the correct way to process various nuances in the data. The results were pretty incredible.
Once GE was able to have an accurate, 360 degree view of their data, they found an abundance of opportunities to save money and optimize their spending. And the amount of money they’ve saved is pretty staggering:
$80 million dollars (and counting) in savings through leveraging data to renegotiate contract terms
The big lesson learned is that businesses are missing out on an enormous opportunity to optimize processes and improve their bottom line. With a product like Tamr, cleaning, unifying, and mastering data is simple and easy to do.
Want to learn more about how Tamr can help with data unification? Check out our case study.