AI Case Study
General Electric has saved $80 million over the past few years by integrating supplier data across business units using machine learning
GE has leveraged machine learning technology from Tamr, to integrate supplier data and records across business units. The company's goal is to identify products that are priced under different names from the same supplier in order to achieve better purchasing power and pricing. GE claims that the TAMR machine learning software has enabled GE to save $80 million over the past few years. According to Emily Galt of GE the use of Tamr has helped the company save $80 million over the past few years.
Consumer Goods And Services
Personal And Household Goods
'What is a ‘two-centimeter brushed ball bearing’ over there may be known as a ‘2-cm bb’ over here. There are different names for the same things,' said Andy Palmer, co-founder and CEO of Tamr. 'Our system understands the meanings behind all the data.'
Tamr’s software takes in huge amounts of “unclean” data and uses machine-learning technology to clean it up and make it more useable. At that point, GE can use other analytics and visualiation tools to see what is really going on.
'Tamr was able to take hundreds of thousands of GE supplier records and identify where multiple records were actually from the same supplier,' said Emily Galt, vice president of technical product management for GE Digital Thread, which is the name for the company’s overall effort to modernize its acquisition processes." (Fortune)
According to Emily Galt, vice president of technical product management for GE Digital Thread, "the use of Tamr in this project across a few GE divisions helped save the $80 million over the past few years."
Tamr’s software takes in huge amounts of “unclean” data and uses machine-learning technology to clean it up and make it more useable.
According to Forbes, "it’s easy for suppliers to charge different prices for the same product when you can’t compare them across business units."
As Fortune reports "GE, which could be seen as seven or eight separate businesses all carrying the same logo–buys its tons of materials and products from many suppliers. The problem is that these different operating units often source the same part from the same supplier, but don’t know that others are doing so, and therefore can’t always get the best pricing.
The fact that all these units also operate in so many places further complicates the buying process, where volume purchases should, in theory, lead to the best price. It also doesn’t help that the same supplier might call one product by several different names."
GE supplier records