“AI and ML pipelines can now create and strengthen a continuous self-learning knowledge system”
CEO & CO-FOUNDER, GEP
“Top performing companies are accelerating the creation and deployment of AI and ML to run their supply chains, mitigate risk, build resilience, minimize the impact of inflation, drive sustainability and diversity, and improve profitability“
Nearly every company discovered that they are ill-equipped to manage their just-in-time, multi-geography supply chains in the face of supply-side uncertainty, labor shortages, and climate disruptions. Moreover, inflation, price volatility, tariffs, trade wars, cyberattacks, chronic component and raw material shortages, and sky-high logistical costs exist. We’re entering an arms race, and the company with the most tangible data set will win the race to global supply chain dominance. Top performing companies are accelerating the creation and deployment of AI and ML to run their supply chains, mitigate risk, build resilience, minimize the impact of inflation, drive sustainability and diversity, and improve profitability.
Many companies tend to view technology as a product. It adversely affects their bottom line, as they are often caught in the endless vortex of ERP upgrades to meet mismatched business situations. Instead, it is useful to leverage data and analytics to transform their supply chain technology. The key to success can be achieved through:
Combining Quantitative Methods with Qualitative Analysis: Companies must deploy AI and ML on higher-quality data to improve demand and price forecasting accuracy and enable better collaboration with suppliers. AI and ML pipelines can now create and strengthen a continuous self-learning knowledge system augmented with external data feeds such as news, customer sentiments, supplier risk profiles and other publicly available information.
Tracking Impact and Drive Sustainability: Use ML-based recommender algorithms to incorporate company-specific goals and drive compassionate and sustainable value like carbon net-zero product recyclability rate, water consumption per ton, product produced, packaging materials recycling rate, and waste recycling rate.
Enabling Agility Through Digital Twins and Scenario Planning: Establish AI-powered control towers as single sources of truth with end-to-end real-time data connections across multiple systems, raw material flow, warehouses, logistics, people and processes.
Deploying Conversational Virtual Agents (CVAs): Use CVAs to streamline supply chain operations, beginning with guiding routine purchases, completing purchase requisitions, and providing contextual guidance.