Technology key for manufacturing industry to optimize supply chains, says report

by Inside Logistics Online Staff

In a recently published blueprint focused on enhancing operational efficiency, predictive maintenance and supply chain optimization, Info-Tech Research Group outlines actionable strategies for IT leaders in the manufacturing industry to leverage advanced technologies to improve productivity, innovation and customer engagement.

Founded in London, Ont., Info-Tech Research Group highlights in its report, Priorities for Adopting an Exponential IT Mindset in the Durable Goods Manufacturing Industry, that manufacturing companies must embrace exponential technologies to improve competitive positioning, with IT leaders playing a key role as valued business partners in this transformation. The new research-backed blueprint provides manufacturing and IT leaders with strategic insights and actionable plans to predict market shifts, enable proactive technology investments, and drive modernization through Exponential IT, ensuring they maintain their competitive edge and avoid disruptions.

Info-Tech’s recently published blueprint emphasizes the strategic use of advanced technologies, such as AI and data analytics, for predictive maintenance, supply chain optimization, and customer experience personalization. This approach not only safeguards sensitive data but also leverages it to fuel innovation and boost overall business performance. The firm advises that by prioritizing these technological advancements, manufacturing organizations can develop more flexible and responsive operations, ensuring sustained success in the dynamic manufacturing landscape.

In the resource, Info-Tech outlines four key priorities that manufacturing IT leaders must consider as they adopt an Exponential IT mindset:

  • Fund exponential value creation: As the market and IT’s roles evolve, IT budgets will need to shift significantly toward innovation. This includes focusing on efficiency, sustainability, cost reduction, and faster product quality enhancement. More funding should also be directed toward advanced human-machine technologies that improve employee safety.
  • Team up DataOps with ModelOps: Companies are increasingly recognizing that data is their most critical asset. While data has always been important, the rise of AI and machine learning has further elevated its significance. These advanced technologies are essential for rapid decision-making, but poor-quality data can lead to poor decisions. Integrating DataOps with ModelOps ensures data integrity and effective model management.
  • Transform infrastructure and applications into utilities: Shifting towards a utility-based model for infrastructure and applications promotes a collaborative and innovative approach to IT asset management. Leveraging cloud solutions and low-code/no-code platforms gives organizations greater control over their outcomes and agility to respond to market changes.
  • Let AI take over core operations: The growing importance of data, driven by AI and machine learning, is transforming core operations. AI can enhance system efficiency, accelerate incident detection, and boost automation productivity. Ensuring high-quality data is crucial, as poor data can lead to poor decisions. Proper integration of AI in core operations allows for rapid, accurate decision-making and improved overall performance.