Digital Supply Chains Compress Time… Both Cycle Time and Customer Time to Value
Digital supply chain solutions are redefining the market in so many ways, and time to value is one of the most significant.
What is it about these solutions that make it possible to deliver value in such a short timeframe?
A high amount of today’s ERP and advanced planning systems were built on a 1990’s and early 2000’s technical stack, now requiring multiple smaller acquisitions (such as database licenses, integration software, third-party embedded software, etc.) in order to make all the point applications interoperate.
Fortunately, today’s digital supply chain solutions were born in the cloud and run in the cloud. They require very little hardware, software, or back-end setup to provision a new customer instance.
In many cases, the source data of legacy supply chain solutions is incomplete or inaccurate, so it must be enhanced, cleansed, and normalized, forcing customers to spend large chunks of time and money on unique integrations while paying for the same integration multiple times.
TransVoyant digital supply chain solution has already done the hard work of identifying, collecting, cleansing, normalizing, and ingesting massive amounts of global real-time Big Data for you.
An important value of a digital supply chain solution is its ability to collect, analyze and unlock the intelligence that is buried in the data from a customer’s extended physical and logical supply chain; data from its upstream and downstream partners; and data about the dynamic events surrounding its supply chain across the entire globe. Therefore, digital supply chain solutions are constructed as platforms first.
APIs and integration layers of today’s digital supply chain platforms are extremely flexible and powerful. As an example, the integration layer within our Continuous Decision Intelligence™( CDI™) platform includes API framework that enables us to pull in over 1 trillion Big Data events around the world every day, ingest streaming data from our customers’ ERP and supply chain systems, and pass predictive insights and prescriptive recommendations back to those systems for execution.
Digital supply chain solution employs self-learning and human-assisted algorithms that analyze the data inputs; identify patterns, behaviors, and outcomes; and from that logic, generates insights.
Over time, as our platform watches the performance of customers’ supply chains, including in-node performance, it also begins to understand lead time, capacity, and throughput variability for the customer’s unique supply chain at a nodal, lane, or route level. This enables us to continuously feed planning and scheduling systems with granular and dynamic insights that enable our customers to meet service level requirements while simultaneously reducing inventories.