Last week’s Boston Business Journal piece on the growing relationship between GE and Tamr did a fantastic job of profiling how we have been teaming up to deliver successful projects for quite some time. It also highlighted how GE is expanding its application of Tamr’s agile data mastering capabilities from suppliers to other entities like customers. The supplier mastering initiative alone saved GE $80M and has been described by Chief Digital Officer Bill Ruh as “a big win” (see this article in Forbes). However, the details about the customer mastering initiative mentioned in the BBJ article hint at the potential for even bigger value creation.
Large enterprises undertaking enterprise-wide analytic or operational initiatives know that complete, trusted data fuels good decisions. Without visibility and trust in their data, business users will likely reject whatever results or conclusions are delivered. That is why data mastering – creating a single, trusted view of entities (suppliers, customers, products, etc.) in an organization – is being increasingly demanded by enterprises with large data infrastructures like GE.
However, the complexity of the data environments at large companies with decades of operating history pose major obstacles to delivering these trusted master views. With dozens of systems containing pieces of the data puzzle, the traditional deterministic, rules-based approach to integrating data silos is ill-suited to deal with the challenge. For a more technical discussion of this challenge, download Dr. Michael Stonebraker’s whitepaper on Scalable Data Curation and Agile Data Mastering.
Companies like GE realize that to master data in an ever-growing and increasingly complex data environment, new approaches to data integration are required. Probabilistic models powered by machine learning (as opposed to deterministic rules built and maintained by developers) are needed to attack the magnitude of the challenge they face. That’s why they’ve turned to Tamr for new data mastering initiatives.
As outlined in the BBJ article, GE executive Cate Gutowski is leading the digital transformation of the company’s global sales force across all business units. She describes Tamr’s agile data mastering value when discussing how it allowed GE to clean up 1.5 billion customer information logs scattered across the company and consolidate the information down to 350,000 neat customer groupings that 25,000 sales reps can now access in seconds.
This is a remarkable accomplishment by GE – especially given the size and growth of their data environments. Results like this were attained because GE thought differently about their customer mastering problem. They believed in the power of a bottom-up, machine learning-based approach to mastering entities as opposed to the inflexible, rules-based systems that have historically dominated the Master Data Management (MDM) landscape. It’s their willingness to try new approaches to long-standing problems that makes them an innovator and a digital transformation success story.