Uncertainty continues to impact global supply chains after the pandemic. Unpredictable economic situations, inflationary issues, and a lack of raw materials have made supply chain planning more important than ever. Data management is essential to proactively predicting and preparing for supply chain disruptions so they don’t upend operations.
Manufacturing and logistics organizations face increasing labor shortages. Supply chain managers must rapidly expand automation and the use of robotics. Quality data management cannot solve all shortages. But it supports automation, maximizing available human labor and technical innovation to improve productivity, efficiency, and resiliency.
Following cybersecurity attacks that disturbed supply chains, governments and corporate boards are imposing new rules scrutinizing managers' actions responding to threats. To counteract risks from intellectual property theft and compromised materials and product components, supply chain managers need secure data management practices to protect asset data and ensure business continuity.
AI will soon become integral to supply chains. AI can help prevent product disruptions, increase data-driven decision-making, and foresee problems before they arise. Supply chain managers need reliable data management and a partner like Infoverity to build effective AI models and leverage new technologies.
Gartner found that only 1% of supply chain organizations say they have no plans to invest in emerging technologies over the next five years while the vast majority of companies cite multiple reasons for doing so; additionally, only 10% of companies believe that technology is not a source of competitive advantage.
Gartner predicts that by 2025, three out of five smart factory initiatives will fail due to a lack of supply chain integration, resulting in significant cost constraints and customer service issues.
