SUNNYVALE, Calif.--(BUSINESS WIRE)--LevaData, the company that helps global enterprises improve gross margins by reducing supply chain costs, has announced its inclusion in the list of “Cool Vendors,” in Cool Vendors in Strategic Sourcing Applications, by Patrick Connaughton, Magnus Bergfors, Desere Edwards, Will McNeill, and Kaitlynn Sommers, 2018,1 a report published this week by Gartner, Inc.
The company’s flagship product, Leva™, is an AI advisor built on a proprietary Cognitive Sourcing™ Platform that guides organizations through sourcing risks and savings opportunities, providing supply chain professionals with a new way to create value for their organizations.
Leva™ constantly scans changes in enterprise spend and market intelligence and reviews over 5,000 news sources for insights that help provide proactive guidance and optimized decision-making to improve outcomes from sourcing events. Leva also delivers predictive modeling and machine learning capabilities that assess over 40 “levers” for procurement teams and recommends the best negotiation strategies to use, based on context, timing and sequence. Additionally, Leva offers personalized insights by job role – including procurement, finance, manufacturing and engineering – for optimized decisions in the face of complex sourcing issues and large data sets.
“Selection as a ‘Cool Vendor’ by Gartner is truly an honor and a powerful validation of our strategy,” commented Rajesh Kalidindi, Founder and CEO of LevaData. “We believe that giving strategic sourcing organizations both the insights and tools to be more effective is the path to more tightly integrated and effective supply chains, with the benefit of saving clients both time and money.”
Why LevaData is ‘Cool’
According to the report, a reason that LevaData received the “Cool Vendor” designation is because it improves agility – reducing the time spend analysis and negotiation strategy development, noting that one customer’s sourcing team now prepares for sourcing events in just a few hours, as opposed to a month. Gartner also cites Leva™’s AI-powered ability to gather market data and provide dynamic recommendations – as well as the ability to rapidly generate a Request for Quote (RFQ) – as key ways in which the LevaData solution helps companies respond much faster to the changing needs of the business.
And Who Should Care?
In terms of “who should care” about LevaData, Gartner observed that direct materials strategic sourcing and commodity management teams at manufacturing organizations in industries like automotive, medical devices and high-tech should examine LevaData’s offering. Gartner further stated that sourcing and procurement professionals with a goal of moving from discrete sourcing events to a continuous category management model should look to Leva as a possible solution.
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Gartner does not endorse any vendor, product or service depicted in our research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
About LevaData
LevaData helps global enterprises improve gross margins by reducing supply chain costs, with a focus on delivering measurable and accountable supply chain solutions and strategies that transform companies and markets. The unique LevaData Cognitive Sourcing Platform allows customers to sense, recommend, act, and learn. Customers include leaders in the top global supply chain organizations, as well as medium-sized OEMs seeking to achieve best-in-class direct materials sourcing practices. LevaData is privately held and headquartered in Sunnyvale, Calif. For more information, visit www.levadata.com.
1 Gartner “Cool Vendors in Strategic Sourcing Applications” by Patrick Connaughton, Magnus Bergfors, Desere Edwards, Will McNeill, and Kaitlynn Sommers, 2018.
