A data-driven supply chain is on the rise: How reinvention might happen sooner than you think
In times of disruption, trustable real-time data can help boost global supply chain resilience
Supply chain leaders are seeking new strategies to deal with geopolitical turmoil, labor challenges, inflation and climate change. Continuous supply chain disruptions could threaten any signs of recovery in manufacturing, semiconductors, and automotive industries. Many are now preparing for a slower recovery with uncertain terms due to a variety of events that have had an impact on pricing and availability.
New and complex challenges require new approaches. Supply chain leaders used to strive for perfection. Today, agility and resilience are the mantras of supply chain leaders. The ones who have a leg up on digital acceleration will not lose their focus. They must build operating models that can be both proactive and predictive to prepare for and anticipate problems.
Cloud and AI are crucial to transformation
Maersk, a shipping giant, already benefits from hosting applications such as container trackers on the cloud. It’s not surprising that AI applications will be the largest areas of investment in digital operations for supply chain leaders over the next three year, reports IBM’s Institute for Business Valu.
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While supply chain leaders recognize that AI is key to their future, a recent McKinsey survey found that three quarters of their business functions still depend upon spreadsheets and only one quarter of them are using AI in planning. However, urgent matters of chaos or volatility are not easily resolved. Traditional planning applications don’t suffice.
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Virtuosos want to fully transform all functions, including production scheduling and distribution. This will help manage supply and demand volatility. Today’s AI tools make it easier to allocate labor resources efficiently and effectively. can even be paired with “cobots“, which interpret data from potentially dangerous environments to ensure that humans are safe at work.
Trusted Data to Improve Model Risk and Opportunities
A recent IBV benchmarking study revealed that 71% shared demand and supply data in real-time to a substantial extent. This means that as supply chains change, the need for reliable data to be used in machine-learning models will increase. Organizations can digitize their supply chains by integrating a trusted, secure data fabric which brings together data processes, tools and people.
Machine learning can use more reliable data to build models. It can also draw powerful insights from operational data and weather updates in order to track and predict supply chain disruptions. They can also suggest alternative actions such as new routes to cut through uncertainty.
Operators can use digital twins and visualization to help them execute by simulating extended supply chains and showing where risks and bottlenecks are. When integrated across multiple data sources, process mining can also help to optimize supply chain processes and identify inefficiencies. The cloud allows organizations to extend these benefits to all of their supply chain partners and not just the ones within the organization.
Learn five strategies that will help you build a more resilient supply chain. These include digital transformation and improved sustainability. Download “Forging a future of supply chains: A guidebook of five essential strategies”