Written by Tamr
Tina Porter of the analytics company AnyData Solutions had an interesting post last week on procurement analytics, observing that with “overarching corporate KPIs now includ[ing] procurement … procurement analytics are now fundamental to the ongoing management of sourcing and handling of market pressures.”
We were particularly struck by her insight about how procurement data has connective properties across the organization:
Cross-function and collaboration capability through data [drives] Procurement departments and staff to not only engage with non-procurement departments like Production and Quality Management, but factor in impact on other functions like Sales and Marketing … with an emphasis on Resource Management. This naturally links with Finance, Logistics and Supply chain through top-down data connectivity.
We’ve seen these very same connective properties of data in our work with procurement customers as well as on our customer data integration and biomedical data integration solutions. Simply put, the best version of integrating data not only connects sources, it also connects people — breaking down data and organizational silos alike to unify the enterprise on its most critical business needs.
This idea is at the core of Tamr’s machine-driven, human-guided design pattern. Advanced machine learning algorithms automatically match attributes and entities across the enterprise’s range of data sources, whether large or small; structured, semi- or unstructured; internal or third party. Our “machines” often accomplish up to 90% of the necessary unification without human intervention. When human intervention is necessary, Tamr generates questions for data experts across business units and departments, aggregates responses and feeds them back into the system. Instead of requiring programmers to intervene, Tamr immediately feeds this expert guidance into the system – without a complex or costly implementation to maintain.
This machine learning plus human guidance approach to helping businesses “make better decisions every single day” is what Co-Founder and CEO Andy Palmer has described as Tamr’s “secret sauce”:
The machine by itself doesn’t get you the kind of precision you need. You absolutely have to have people in the loop. And the careful weaving together of this machine learning capability with a very collaborative and very social process of curating data is really the secret sauce of Tamr.”
This collaborative and social process of curating data can have a transformative effect on how the organization does business across departments, systems — and silos. Again, procurement offers a compelling example.
One of Tamr’s customers runs sourcing for a large global manufacturing company with thousands of suppliers spanning dozens of semi-autonomous business units. The company has hundreds of ERP systems and each business unit has its own idiosyncrasies within supplier systems. The customer saw great value in being able to break down these silos and generate a unified view of its suppliers across businesses, engaging with common suppliers across the business units to negotiate part pricing and payment terms.
The company first used Tamr to identify supplier overlap within two of its core businesses, whose supplier spend totaled billions of dollars when combined. Tamr was able to identify that, on average, approximately one-third of suppliers used within each of these two businesses had a relationship with at least one other business unit. Tamr’s ability to provide this unified view of suppliers allowed the customer to negotiate more favorable part prices and payment terms, driving millions of dollars of cost savings per year.
That’s a significantly more unified way of looking at information and doing business in procurement — driven by a human/machine approach that breaks down organizational silos as well as data silos.
To learn more about Tamr’s human/machine solution for procurement spend optimization: