As supply chains in Asia grapple with challenges such as surging consumption, talent shortages, financial strains, and the need for sustainability, the spotlight is increasingly turning to AI as a transformative solution.
In the region, Southeast Asia has emerged as an attractive location in this evolving landscape as companies look to manage supply costs and mitigate risks.
However, operating AI in isolation can lead to highly efficient but disconnected processes. To truly make an impact, AI must be aligned and integrated seamlessly across the entire supply chain, from end-to-end.
Technology offers a promising solution to supply chain challenges, particularly through advanced analytics and data-driven insights. But is AI the solution?
DigiconAsia sought out some insights from Yogesh Punde, Senior Industry Principal, Supply Chain Planning, Kinaxis, on the potential of AI in resolving supply chain woes, and how companies in Southeast Asia are leveraging real-time data from various supply chain sources to proactively identify and anticipate potential disruptions, empowering them to make well-informed decisions and implement proactive measures to mitigate risks.
How is the supply chain landscape in Southeast Asia evolving?
Yogesh Punde (YP): Southeast Asian countries are already major hubs for manufacturing. Countries like Vietnam, Thailand, and Malaysia have appeared as key players in the supply chain.
This region is still attractive regarding cheap, lower-skilled labor, low-cost manufacturing, availability of raw materials, better infrastructure, and tax incentives. Local governments in this region are supporting with continuous reformation of legal and trade policies to improve the ease of doing business.
With post-COVID disruptions in China, many companies are shifting their supply chains to Southeast Asia (SEA), and this trend will only continue. No company wants to entirely rely on one country and diversify their supply chain to Southeast Asia from a risk-mitigation perspective.
Even many Chinese companies are setting up their factories in SEA so that they can reduce costs, mitigate supply chain disruptions, and remain competitive in the global market.
Many companies in SEA have started to adopt digital technologies (AI, ML, and analytics) to strengthen their positions. The shift in technology adoption is widely seen in consumer goods, electronic manufacturing services (EMS), and agro-based industries.
What challenges has the evolving landscape posed?
YP: While the companies in SEA have started to adopt digital technologies, they are still behind compared to companies based in the US or Europe and run their supply chain in silos or in a cascaded way.
They often lack visibility into the end-to-end supply chain, use multiple disparate systems for supply chain management, and lack of single data model. Without real-time and accurate data, these companies find it difficult to forecast demand with reasonable accuracy and have challenges responding to supply chain hardships due to lack of agility and resilience.
Further, sustainability goals are often overlooked. It is also becoming hard to retain supply chain talent due to stress from continuous high workloads and disparities in pay.
How are industry players addressing these challenges?
YP: Industry players have understood the need to have a single platform for end-to-end supply chain management, that provides them with real-time visibility, better analytics, and the Command and Control Tower to get early insights on exceptions and alerts on possible hardships in the supply chain.
Companies are getting ready for digital enablement and adopting the “Digital Twin” model for supply chain. To remain competitive and meet ever increasing customer demands, a KPI-driven scorecard for supply chain performance is getting traction, Simulation capabilities, better control on inventory, reducing excess and obsolescent inventory, and optimizing transportation costs are the ways companies are trying to address these challenges.
Carbon emissions are also part of supply chain metrics, as increasing sustainability is becoming more challenging.
What is the transformative potential of AI and advanced analytics in supply chain management?
YP: As mentioned earlier, talent is a major challenge in the supply chain, Often, planners spend time on non-value-added tedious tasks, work with old technology and look for data maintenance. If we take a use case of demand planning and forecasting, it’s beyond the human cognitive ability to find patterns and make predictions at the enterprise level and this is where AI can help do such tasks e.g. flag forecast outliers so that planners can work on exceptions only, AI can process external demand signals and increase forecast accuracy.
Advanced analytics can help detect shifting data patterns, predict changes in demand, and automatically update and optimize forecasts by adding signals beyond sales history. AI & analytics can:
- Optimize decision support
- Help respond to business challenges in real-time
- Optimize costs and achieve critical KPIs for the organization
Could you provide some real-world examples and success stories of technology-driven supply chain optimization in the region?
YP: CPG companies in the alcoholic beverages industry having manufacturing facilities in Malaysia were able to successfully transition from a manual demand and supply planning process to a single platform based on concurrent planning.
Benefits include:
- Single-source of truth for planning
- One data model
- Improved planner efficiency
- Ability to rapidly respond to demand changes
- Better forecasting
A leading manufacturer of semiconductor devices based in Singapore successfully implemented technology-driven supply chain optimization. From Excel-based, disconnected systems to unified single solutions for demand and supply planning, better collaboration among internal and external stakeholders.
Benefits include:
