The Future Of Supply Chain Technology: A Shift Toward Intelligent Systems

As supply chains become increasingly digital, manufacturers and other supply chain stakeholders gain the ability to react quicker and make smarter decisions. These capabilities rely on data, which creates obstacles for organizations that don’t collect good data. The rise of generative AI solutions is helping to even the playing field in the supply chain by making data collection, cleaning, and analysis more accessible than ever before.

In the world of supply chain management, the winds of technological change are blowing stronger than ever. It’s becoming more evident that purpose-built intelligent applications are increasingly shaping the future of supply chain technology, especially in the functional area of MRO and indirect materials management. This represents a wholesale departure from the monolithic and project approaches of the past.

With multiple lessons learned over the past three years, purpose-built intelligent applications are creating the connective tissue that solves specific problems by weaving together disparate systems of records and transactions such as ERP, EAM, and P2P. Most importantly, by removing the need for perfectly clean MRO data, intelligent “systems of routine” can help organizations drive optimization and increase collaboration across internal teams and external supplier networks.

The trend of integrating business data repeats a bit of important history in the greater ERP industry, where in the late 1990s, a wave of well-financed “middleware” companies, including Active Software, BEA Systems and WebLogic shaped the eBusiness trend, transforming the enterprise application and service-oriented architecture (SOA) to great success, using the software as central brokers to tie together data from many apps and data types into one cohesive system.

For today’s supply chain, new software engines powered by GenAI, deep learning and natural language processing (NLP) can process exponentially larger datasets than previous forms of machine learning. They can analyze complex variables, including MRO inventory and spending data, far quicker. These smart applications can help build data links between businesses’ various ERP software platforms to manage their day-to-day operations and associated procurement needs.

By removing the prerequisite of “clean” data, these intelligent “systems of routine” will allow enterprise manufacturers to use their current MRO data, creating value faster than ever. This will help drive demand signals and cross-entity optimization with supplier networks.

Purpose-Built Intelligence

The days of siloed supply chain systems are numbered as the industry enters the era of purpose-built intelligent applications. A new report from KPMG on supply chain trends for 2024 notes that generative AI “has the potential to revolutionize supply chain management, logistics, and procurement.” The report’s authors call on businesses to “re-evaluate your current supply chain analytics team and prepare for an AI upgrade.”

Today’s new supply chain business intelligence capability provides an actionable data-driven experience, such as interactive reports and dashboards, for procurement, operations, and reliability teams, from senior management to front-line workers.

This benefits both sides. Procurement managers can use verified demand signals to gain data insights around lead times, costs, delivery timing, efficiency, and quality assurance. Line managers can also easily see any types of gaps in performance and take measures to correct those. With increased clarity and MRO materials visibility, decision-making leads to improved business performance and bottom-line savings.

Among other areas, GenAI is capable of:

  • Procurement and Regulatory Compliance: Helping companies to adhere to procurement guidelines and regulatory standards.
  • Manufacturing Efficiency: Streamline production workflows, optimize processes, and reduce human errors. These factors contribute to overall efficiency.
  • Virtual Supply Collaboration: Working with virtual assistants to handle routine inquiries, provide quick responses, and keep the supply chain communication flowing seamlessly.

It’s an exciting time to be working in the intelligent supply chain universe. Get ready because the smart supply chain is about to redefine the rules of the game.

Data Liberation from the Shackles of “Clean” Data

Earlier this year, I wrote in this column about AI’s role in supply chain data cleansing and how AI understands “dirty” and incomplete data significantly grows trust in outcomes presented across the enterprise. Buyers and suppliers can rely on a “single source of truth” for data.

A purpose-built solution can apply data techniques that enrich and standardize procurement and operations data across systems. Ensuring that all parties operate from the same trustworthy and consistent data source eliminates the need for pricey traditional data cleanses.

This is crucial because the more business is automated, the more we must depend on the data that drives it all. Mistakes may arise in MRO inventory if the data is incomplete or your team enters the MRO material information under different names.

The way to get around that is in purpose-built intelligent AI applications. In the supply chain model, these applications can read descriptions, identify items, and confirm quantities. Further, smart intelligence systems also offer user recommendations to:

  • Confirm inventories
  • Identify duplicate materials
  • Identify materials to be shared among facilities
  • Recommend ideal storage locations
  • Revamp outdated stocking policies
  • Recommend order patterns by consumption and lead time

With these systems, a ‘trusted supply’ forms, with increasing trust in MRO data and collaboration between partners, buyers, and suppliers.

Resilience and Agility

If you’re a manufacturer with indirect and MRO inventory, you’ll recognize how poor or incomplete MRO data could result in inventory discrepancies that result in excess materials or critical shortages. These discrepancies create downtime on your factory floor due to the unknown and inconsistencies. This leads to line bottlenecks and possible production shortfalls.

This is why manufacturers must look to AI software to transform their supply chain operations. The future supply chain isn’t just about efficiency and resilience. Organizations must adapt swiftly, with greater visibility and traceability, to control risk.

The future of supply chain lies in technological advancement. It’s time for your business to enhance its existing tech stack with purpose-built intelligent solutions and inject better outcomes into its existing supply chain operations. Allowing a neural network to process the data, analyze it, and recommend action is likely a more secure and definitive plan to reduce costs, build value, and improve shareholder value.


This article was written by Paul J. Noble from Forbes and was legally licensed through the DiveMarketplace by Industry Dive. Please direct all licensing questions to