![]() ![]() Spreadsheet plugins - the most popular Excel plugins are and Crystal Ball. There are two ways to use Monte Carlo simulation in practice: Great - how can we actually run simulations like these? Monte Carlo simulation in practice ![]() Supply chain management - you want to stock enough inventory to be confident that you won’t run out, but you don’t want to overstock.Company budgeting - each department has an uncertain estimate for their budget requirements, and the CEO needs to decide how much cash to set aside overall.Retirement planning - you need to find a rate of withdrawal that makes your nest egg last as long as you need.Outside of your next dinner party, Monte Carlo simulation is useful whenever there’s uncertainty involved in decision-making, and different risks associated with different outcomes: If we go through this list and find the threshold such that 50% of times are above, and 50% of times are below, then we’ve found the real average buffet time. Some will be low - a lucky simulation could have every dish taking under 60 minutes. Some of these will be high - an unlucky simulation could have a dish taking 75 minutes. When we’re done, we’ll have a list of 1,000 possible buffet times. Each simulated buffet is ready when the final simulated dish is prepared. We could run 1,000 simulations, in which we pick a random time between 45 and 75 minutes for each dish. Suppose each dish takes 45–75 minutes to prepare (still 1 hour on average). This is the core idea behind Monte Carlo simulation - exploring “alternate futures”, or simulations, to understand the full range of possible outcomes. Strange: Fourteen million six hundred and five. To see all the possible outcomes of the coming conflict. Recall the following dialogue in the 2019 blockbuster Avengers: Endgame: As we’ll explore in a future article, this style of scenario planning is fated to underestimate risk in some settings, and overestimate risk in others. ![]() Unfortunately, this doesn’t quite cut it. Many companies do this when planning and forecasting. What can we do about this? Overcoming averagesĪverages are misleading because they ignore the uncertainty that comes with the real world.Ī common way to account for this uncertainty is to make estimates under 3 different scenarios: average-case, best-case, and worst-case. ![]()
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