It’s National Retirement Security Week which is a dedicated effort to raising awareness and helping individuals take concrete steps towards a secure retirement. While most people are thinking about pensions, 401(k)s, and IRAs, we at Minitab can’t help but think about Monte Carlo Simulation.
Why? Because whether you’re designing a new product, optimizing a process, or planning for retirement, the question is the same: “What happens if things don’t go exactly as planned?”
That’s exactly what Monte Carlo simulation helps you answer easily, visually, and quantitatively.
What Really is Monte Carlo Simulation?
If you’re an engineer, you’ve already lived through the chaos of uncertainty: tolerances stack up, temperatures drift, materials vary, and deadlines move faster than you’d like. Monte Carlo simulation takes that uncertainty and turns it into clarity.
Instead of assuming one “perfect” value for each input, Monte Carlo lets you model a range of possibilities and then runs thousands of virtual trials to show how those variations affect your outcome. Thankfully, Minitab lets you run a simulation in 4 simple steps.
On-Demand Webinar: See the Unknown with Monte Carlo Simulation
Monte Carlo Simulation is Used by Most Financial Planners
Have you ever spoken to a financial advisor about retirement? You might have heard something like, “There’s an 80% chance your retirement savings will last to age 90,” or in my case, “There’s a 0% chance your retirement savings will be enough if you sit around writing blogs all day.” Jokes aside, they’re running a Monte Carlo simulation. They’re just using dollars instead of dimensions.
Don’t have a financial advisor? No problem. Nearly all online wealth managers (like Vanguard, Fidelity, Charles Schwab, Merrill Lynch, Morgan Stanley, and Edward Jones) have tools that leverage Monte Carlo to produce “probability of success” percentages. Even newer platforms (like Betterment, Wealthfront, Personal Capital (by Empower), Facet, and Ellevest) provide “retirement readiness” dashboards and projection sliders that use Monte Carlo as well.
Looking for Ways to Get Started? Here are Everyday Applications
Monte Carlo isn’t just for finance or advanced research. Engineers use it daily to:
1. Quantify Process Capability Under Uncertainty:
Imagine that a process engineer wants to assess the capability of a machining process but knows that tool wear and temperature fluctuations cause variation beyond standard assumptions. By using process inputs such as cutting speed, feed rate, and ambient temperature with realistic probability distributions, you can model and simulate thousands of production runs to estimate the distribution of process outputs. Then calculate simulated Ppk/Cpk values and defect probabilities for better quality.
2. Assess Risk in Product Tolerances (Also Known as Tolerance Stack-Up Analysis): While most engineers understand tolerances for particular parts, many don’t consider tolerances as a combined finished good. While many perform Tolerance Stack-Up using a worst-case approach, Monte Carlo simulation provides a more realistic analysis.
3. Cost and Schedule Risk in Engineering Projects: Imagine that a project engineer wants to forecast the probability of completing a project under budget and on time (what engineer doesn’t!). By defining uncertain cost and duration inputs for key project tasks, you can use Monte Carlo simulation to simulate thousands of potential project outcomes and generate probability curves for cost and time. Read about a specific example in this blog I wrote.
Better Your Retirement Outlook by Improving Your Engineering Skills
To save for retirement, you need to generate more income. What better way to do it than to develop and progress your career as an engineer. Add Monte Carlo simulation to your own personal toolkit and use Minitab’s Monte Carlo resources to expand your skills. The next time your financial advisor starts talking about probabilities, just smile, nod, and use it as motivation to find even more uses for your newfound love of Monte Carlo simulation.
