A core principle of One Network Enterprises is that reducing information latency – even eliminating it, if possible – is fundamental to how it brings value to its customers, and it now has the science to back it up.
A study recently released by the University of North Texas (UNT) as part of a funded project between the school and the company has demonstrated that One Network Enterprises’ Real Time Value Network for leveraging a new inventory management strategy called the Science of Theoretical Minimums (STM) that minimizes inventory by reducing physical and informational lead times from the customer back through the entire value chain.
One Network Enterprises, which has established itself as a LinkedIn-type business network with a platform that supports business solutions to customers and helps them connect with each other in real time, wanted to see scientific validation of its business model, said senior vice president of products Adeel Najmi in an interview with EBN. “No one had really spent the time understanding the value of information and information flows,” he said. “We wanted to see some scientific validation for our hunches.”
The company had also been getting exposed to its customers’ digital transformation efforts, prompting One Network Enterprises to partner with UNT about 18 months ago so that an “academic and scientific lens” could be applied to the company’s models, said Najmi. The work was done with UNT’s Center for Logistics Education and Research and Jim McNatt Institute for Logistics Research.
The UNT study essentially found that One Network Enterprises’ Real Time Value Network effectively embraces the Science of Theoretical Minimums (STM) that minimizes inventory by reducing physical and informational lead times from the customer back through the entire value chain.
The Real Time Value Network transforms the supply chain by enabling all parties to focus on the customer and lowering costs by eliminating information delays across the extended supply chain.
The latest findings from the ongoing research partnership between UNT and One Network has, for the first time, identified how organizations can apply a quantitative approach to incorporate information lead times in supply chain designs to drive innovation and achieve digital transformation objectives.
STM provides a methodical approach and accompanying governance structure that enables managers to uncover fundamental latency and the costs that result because those delays. The key to STM is the development of a method to define supply chain-specific minimum resource requirements such as time, inventory, transportation and correlate those requirements using an advanced algorithm based tool to potential cost avoidance.