The adoption of machine learning in enterprise technology is becoming the next arms-race for many vendors. Supply Chain Planning technology is currently experiencing a major step-change in its evolution. The point of no-return has been reached.

This is an exciting time with major benefits to be realized. Many companies sitting on a gold mine of data are set to realize its value. The only bad machine learning plan is no plan at all. Machine learning is a crucial part of a comprehensive digital transformation strategy.

One does not need to look far to find confirmation that supply chains are changing dramatically. At the present time we observe three forces of change in global supply chains: consumer-driven forces, geopolitical changes, and technology and the digitalization of supply chains.

Agile supply chains exist almost as the antithesis of efficient supply chains. Agility requires the ability to detect, analyse and execute the best possible business decision regardless of traditional sources of supply and demand.

Emerging digital technologies and the consequent need for new capabilities are disrupting all aspects of business: people, process, and technology. Today’s supply-chain operating models are being challenged to deliver unprecedented levels of agility and economic value.

A value management program is an important tool for keeping a supply-chain planning transformation initiative on track.

The notion of a platform holds the key to building true end-to-end supply chains, says Roddy Martin, chief digital supply chain officer with TraceLink.

For all stakeholders in traditional supply-chain ecosystems, and specifically in life-science supply chains, enormous digitally enabled breakthrough opportunities lie ahead.