Digital Supply Chain Lexicon

The leaders in supply chain management are all focused with intensity on achieving the promise of Supply Chain Digitization.  Use this glossary of terms to better understand the terms and ideas being put forward by the early adopters of the amazing new technologies being applied to supply chain management today.

AI – Artificial Intelligence; the simulation of human intelligence processes by machines, especially computer systems.  Harnessing today’s unprecedented (and still growing) computing power, AI for supply chain crunches all the data collected by the disparate systems that comprise the supply chain management tech stack to arrive at optimal decisions for supply chain management without the need for human intervention.

Blockchain – A decentralized peer-to-peer computer network used to maintain an un-corruptible ledger/recording of transactions.  Originally designed to support crypto-currency transactions, the blockchain technology has enormous potential for applications managing supply chain activity. Blockchain tech can be used to provide “one version of the truth” with respect to freight movements, and other supply chain functions.

Demand Planning – Using forecasts and data captured via prior business experiences to estimate demand for various items at various points in the supply chain. If forecasts are accurate, demand planning helps an organization prepare supply chain activities so as to optimize efficiency upstream and downstream in the process of production through delivery.

Fourth Industrial Revolution – A transformation in production and automation was brought on first by steam and water power (Industry 1.0), then by electrification (2.0), and more recently by the digital computer (3.0). Industry 4.0, digitization, is about companies orienting themselves to the customer through e-commerce, digital marketing, social media, and the customer experience.

Predictive Analytics – the application of mathematics, statistics, predictive modeling and machine-learning techniques to find meaningful patterns and knowledge in order, shipment and transactional and sensor data.  Leveraging the data captured in supply chain applications like ERP, TMS, WMS, YMS and others to arrive at accurate predictions for more efficient, effective supply chain operations.

Supply Chain Ecosystem – Departing from the traditional concept of supply chains existing as a linear “chain” the supply chain ecosystem is comprised of the network of companies, geographies, industrial clusters, financial and human resources, delivery infrastructures  including logistics, IT and knowledge of the industrial environment. Addressing supply chain management from a perspective that includes all the relevant components of the broader ecosystem helps organizations achieve configurations of people, processes and technologies that effectively serve their unique and particular enterprise.

Supply Chain Digitization – the practice of engaging and integrating supply chain software solutions to build a “tech stack” effective at complete integration of an organization’s supply chain ecosystem so that it is fully transparent to all the players involved from suppliers of raw materials to transporters of finished goods and the customers at the point of fulfillment.

Tech Stack – is a term describing a combination of computer programming languages, frameworks, tools and applications developers use to build a digital supply chain management program. The two main components of any app are client-side (front-end) and server-side (back-end). Each layer of the application is built atop the one below, thus creating a stack.