The expansion of global supply chains has meant an increase in the risk of disruption to those networks. Larger supply chains mean more vulnerabilities. There are risks of disruption from catastrophic events, variabilities in transportation and communication infrustructures, and risks in lean manufacturing.
How do organizations account for these risks? Many organizations turn to sophisticated risk analysis and risk management techniques for supply chain management, including Monte Carlo simulation.
In SupplyChainBrain magazine, Palisade's Fernando Hernández explores the use of Monte Carlo simulation in supply chains in "Monte Carlo Simulation Means Quantifying Logistics Risks Doesn't Have to Be a Gamble."
Hernández examines how a Monte Carlo risk analysis model in Microsoft Excel can answer supply chain questions such as: "What is the probability this critical part will arrive on time?" and "What are the chances of failure at this point in the process?", or "What is the profitability of entering into a new regional market, provided likelihoods of major vendor disruptions and major uncertainties of demand?"