One year in. A deep look at quantum computing's transformative potential for supply chain management.
5 min read · August 2024
Good Morning, Good Evening, and Good Night — wherever you're reading this. Welcome back to the Daiiv Journal.
August 2024 marks exactly one year since the inaugural Daiiv Journal. What started as a personal challenge has grown into something I'm genuinely proud of. This month, we go deep on quantum computing — a topic building in the background since June.
Quantum annealing solves Vehicle Routing Problems intractable for classical computers — minimizing transportation costs while satisfying all delivery constraints simultaneously.
Quantum algorithms dynamically balance overstocking and understocking across entire supply networks, making chains more responsive and cost-effective.
Process vast datasets to identify demand patterns invisible to classical methods — especially powerful for seasonal, weather-sensitive, or trend-driven products.
Optimize facility location, fleet size, and distribution center placement simultaneously — finding the globally optimal network, not just local improvements.
Quantum processing enables truly real-time digital twins — virtual models that update instantaneously. Combined with the digital twin work from May, this creates unprecedented operational visibility.
IBM, Google, IonQ, and others are making steady progress, but fault-tolerant quantum computers capable of running commercial supply chain applications at scale remain 5-10 years out. The companies building understanding and readiness today will have a decisive first-mover advantage.
"The race for the first practical quantum computer is a marathon, not a sprint. But the prize is worth training for."
"One year in. Twenty-nine journals to go. The best supply chain insights are still ahead of us."
— Daivik Suresh, 1-Year Anniversary Edition · August 2024-DAIVIK SURESH-
Supply Chain + Business Analytics Enthusiast · August 2024Not financial advice. All opinions are personal. Investing involves risk including potential loss of principal.