Amid disruption, trusted real-time data can boost global supply chain resiliency

Supply chain leaders are looking for new strategies to cope with geopolitical unrest, labor challenges, inflation, climate change, supply challenges and cyber-attacks. Any sign of recovery in industries in industries such as manufacturing, semiconductors and automotive, are at risk from ongoing supply chain disruption. With a churn of events  impacting pricing and materials availability, many are now bracing for a longer recovery on uncertain terms.

New and compounding challenges demand new approaches. If supply chain leaders once aspired for perfection, resilience and agility are now today’s mantras. Those who got a head start on digital acceleration are in no position to lose focus. They need to aggressively build operating models that are both predictive and proactive to anticipate and prepare for issues seen and unseen.

From planning and risk mitigation to value creation, cloud and AI are key to transformation

Shipping giants such as Maersk already benefit from hosting business applications like container trackers on cloud. For supply chain leaders, it’s no surprise that AI applications will also be the biggest areas of investment in digital operations over the next three years, reports IBM’s Institute for Business Value.

Supply chain leaders know AI is the key to their future, but according to a recent McKinsey study, three-quarters of their business functions still depend on spreadsheets, with only a quarter now using AI in some areas of planning. But urgent matters of chaos and volatility have no clear end. And that means traditional planning applications are not enough.

Virtuosos are looking to implement full scale digital transformation across all functions to manage demand volatility and supply constraints, even production scheduling and distribution. With today’s AI tools, allocating labor resources can be done much more efficiently and effectively — even paired with “cobots” to interpret data from risk-prone environments so humans stay safe.

Trusted data to better model risk and opportunities

A recent IBV benchmarking study revealed that 71% of organizations shared supply and demand data in real time to a significant extent. In other words, as supply chains transform, their need for available trustworthy data used in machine learning models will become even more critical. An integration of a trusted and secure data fabric that brings together people, data processes and tools is a way forward for organizations digitizing their supply chains.