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During a lunch conversation last week, I offhandedly mentioned that Monte Carlo analysis should be a risk management tool for only the most mature of organizations. My remark led to an interesting conversation which leads to this tip.
What’s Monte Carlo anyway? In project applications, Monte Carlo simulation takes the uncertainty of your project task durations and costs, and then calculates possible project delivery dates and costs along with their corresponding probabilities. Monte Carlo was invented by the same smart dudes who built the first atomic bombs. It’s namesake is the casino town Monte Carlo, Monaco. My thoughts about Monte Carlo in this article are based primarily upon using Pertmaster, which is now Oracle’s Primavera Risk Analysis as well as some dabbling with Full Monte and Palisade over the past 11 years or so. You’ll notice I speak in the past tense–I don’t mess with Monte Carlo much these days.
Years ago, as a program manager at Oceaneering, I figured out how to do detailed Monte Carlo analyses for the $20 million BOP control systems that we were developing and manufacturing. I would take duration estimates given by the experts, past material and labor costs, and some of the higher ranking risks from the risk register and disappear into my office for days on end to do the modelling. Few people knew what it was all about, and even fewer were convinced that it was value-added work. This funny conversation actually took place during that time:
Me: “Please don’t give that date to the customer. It’s not based on anything rooted in reality.”
Boss: “The client is screaming for a date, I gotta give him one, dammit!”
Me: “I just need a few more days and I’ll give you a date. I have to finish the Monte Carlo analysis.”
Boss: “MONTE?!? You tell that stupid sonafabitch–”
Me: “No, no, no, it’s a not a person. It’s a … never mind. It’s not important. I’m working on a date based on good estimates that we’ll all be comfortable agreeing to. I will get it to you before the end of the week!”
After Oceaneering, I applied Monte Carlo simulations to our budgeting and sales/revenue planning process at Axon with a home-brew Excel simulator I built based on a book I read. It worked exceptionally well: we consistently maximized shop utilization and exceeded revenue and profit targets. Plus, it was kinda fun for us to watch the probability for our max bonus payout increase as the year progressed.
Anyway, back to my lunch conversation. My point was that only a handful of oilfield organizations would find it useful to mess around with Monte Carlo simulations on their projects. I don’t think there’s any point investing in Monte Carlo tools and training unless you’re already doing the fundamentals of project management well. Just like the guy who pops a Dexatrim with his cheeseburger, organizations that aren’t good at project management but try to incorporate Monte Carlo will be in for great disappointment. The opportunity lies with practicing and honing the fundamentals first.
Don’t get me wrong–Monte Carlo is a great risk management tool that has served me extremely well over the years. But I’m convinced that you have to be good at doing the fundamentals first. Otherwise, you’re just simulating garbage. Focus on doing all of these well: project charters, stakeholder analysis, clear scope definition, detailed WBS, scheduling, detailed cost and budget, participative risk management (start with collaborating on and maintaining a risk register), contingency and management reserves, proactive/anticipatory management and communications, change management, and frequent lessons learned activities.
Like Peter Drucker said: “The best way to predict the future is to create it.” Don’t rely on Monte Carlo to predict your future, create it by doing the fundamentals well. Once you get good at the fundamentals, roll out Monte Carlo to fine tune your results.
