On Supply Chain Management. Q&A with Mark Holmes

“Generative AI has been used in a number of supply chain scenarios with promising results. The biggest use cases will likely revolve around analyzing large sets of historical data to help with demand planning, forecasting, and replenishment.”

Q1. Supply chain management is a complex task that involves coordinating multiple processes and stakeholders across the entire supply chain. How did the business of supply chain management change in the course of the last years? 

Supply chain management has become top of mind for consumers recently, especially given the highly publicized product shortages during the Covid pandemic. An influx of next-generation technology, transparency into supply chain-related processes, constant unpredicted disruptions and overall globalization of supply chains has changed the business over the last few years.

Q2. With increased volatility and uncertainty in the global market, what challenges supply chain businesses face at present? 

Global supply chains are becoming increasingly more complex. This is due to ongoing disruptions (natural disasters, geopolitical conflicts, transportation issues, demand volatility, labor shortages, new regulations, etc.), the growing number of systems and partners, and heightened expectations and demands from customers. 

Q3. What components of supply chain management are particularly affected? 

Four key components of supply chain management are affected by market volatility and uncertainty.

• Planning: balancing supply and demand amid constant disruptions is increasingly challenging.
• Sourcing: more and more companies are implementing alternative sourcing strategies due to raw material shortages or geopolitical unrest.
• Production: disruptions to raw materials or critical components, coupled with labor shortages impact production planning.
• Distribution: labor shortages across transportation and warehousing, combined with limited capacity, impacts OTIF and on-shelf availability.

Q4. According to a study of Gartner enabled customers are 2x as likely to repurchase, but only 23% of supply chains focus on enabling their customers. Why this? 

Enabling customers is very difficult for supply chains. The number one way to enable a customer is to ensure that the product is available in the desired channel at the desired time. Continued global disruptions makes this incredibly challenging. More and more customers are using real-time visibility solutions for more accurate ETAs, but a lack of good data hinders this process.

Q5. What are the main elements to build a robust supply chain orchestration system in place? 

Companies need to power their supply chain application ecosystem with healthy data for end-to-end visibility, insights, and better decisions to achieve the agility and resilience needed to cope with supply chain disruptions both today and in the future. From a technology standpoint, this includes control tower capabilities, end-to-end supply chain visibility, and predictive and prescriptive capabilities that transform supply chain performance and agility.

Q6. Specifically how do you manage the growing amount of data generated from disparate sources and how do you navigate thousands of touch points? 

Supply chain practitioners across industries struggle with accessing unified, accurate, timely data spread across applications, data feeds, data warehouses, data lakes, data marts, and business entities. Often, a request for data triggers a long development cycle to provide secure and robust unified data for business needs.

InterSystems Data Fabric Studio helps alleviate these challenges. The solution takes a new and unprecedented approach to accessing data, delivering the right data to the right data user at the right time in a secure and controlled environment. The supply chain module is a fully managed cloud-based self-service data gateway utilizing a smart data fabric to transform disparate data into a single unified source of actionable information. This low-code environment with an easy-to-use web interface includes end-to-end data integration, harmonization, task automation and data cataloging

Q7. What about predicting and mitigating disruptions in real-time? Who does it? and how? 

Decision intelligence represents a fundamental change in supply chain management. It marks a shift towards intelligent, data-driven decision making that pushes companies towards greater efficiencies, agility, and resilience. An AI-enabled decision intelligence platform can predict disruptions before they occur and optimally handle them when they do. This enables you to be ready to manage the unexpected with confidence.

Q8. What are in your opinion the biggest technological trends in procurement and supply chain? In particular, how will AI impact supply chains? 

InterSystems Supply Chain Orchestrator  provides a real-time connective tissue to unify disparate data sources, and a set of next-generation solutions that complement existing technology infrastructures and accelerate decision making and time to value to drive efficiencies throughout your supply chain.

For optimized fulfilment, we help you adapt to order changes, supplier availability issues, and demand spikes, increasing productivity, revenue, and customer satisfaction.

For optimized real-time demand sensing, we help you improve forecast accuracy, supply and demand planning, and product availability.

For inventory optimization, we help you reduce working capital while eliminating stockouts and overstocks.

Q9. It seems that early use cases of generative AI in supply chains prove its worth in delivering cost savings and a simplified user experience. (Source EY) What is your take on this? 

Generative AI has been used in a number of supply chain scenarios with promising results. The biggest use cases will likely revolve around analyzing large sets of historical data to help with demand planning, forecasting, and replenishment. Additionally, there is the opportunity for gen AI to be used the generate a list of all possible supply chain risks a company could face and develop risk mitigation plans. We are still the early stages of using gen AI within supply chains, but the use cases are likely to grow.  One area we are finding results is the use of using GenAI for Co-Pilot.  Once Supply Chain Orchestrator provides the most optimized real-time decision option, the LOB can challenge how the decision was arrived using human language interface to provide a level of confidence to the LOB for “decision with confidence”.

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Mark Holmes, Senior Advisor, Global Supply Chain | InterSystems

Mark Holmes Senior Advisor for Supply Chain – InterSystems Mark Holmes brings more than 25 years of experience in consulting, manufacturing operations, and software development from such organizations as Dow Chemical, GS1 (Brussels), Aspen Technology, and GSI. He specializes in working with manufacturers and retailers/CPG to solve their most difficult supply chain issues through digital transformation with a modern data fabric architecture. Breaking down data silos and leveraging artificial intelligence and machine learning to drive actionable insights throughout an organization’s global supply chain, Mark has delivered value to companies like Tyson Foods, Ferrero Roche, TJX Companies, Hard Rock Café, and Albertsons. Mark joined InterSystems in 2021 to broaden InterSystems global market in supply chain. Holmes has been a board member for the Association for Supply Chain Management and is APICS certificated in Transportation, Logistics and Distribution (CTLD) from the same organization. He earned a BS degree in business administration from Indiana University in Bloomington, Indiana, and an MBA from Bentley University in Waltham, Massachusetts.

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