In the last post I talked about the downfalls of using simplified approaches to complex issues. This usually means inadequate or flawed analysis, or decision-making based on gut feeling or wishful thinking. Intuition isn’t always bad – it’s quite helpful in framing problems and developing hypotheses. But, intuition is best served when backed up with analysis of cold, hard data.
So there’s that word again. Analysis. Let’s take a look at what this means in a project development context.
Concrete and steel are hard (and expensive) to undo. So in the capital project world, it’s important to get it right the first time. In this context, analysis is the evaluation of different options to support informed decision making.
Simple enough so far, but let’s get more specific to why this matters to projects, and then dig into an example.
Project decisions typically focus on cost and schedule implications.
[Sidebar 1: decisions are often made irrespective of cost and schedule implications, such as with health and safety, community, and environmental matters.]
This means that project analysis includes the traditional areas of project controls, cost and schedule. We’ve talked before about how cost and schedule are the two big levers to project value, so decision-makers usually want to understand their options based on their cost and schedule implications.
A few years ago I was the Project Controls Manager for construction of a large mineral processing plant. The longest-lead piece of equipment was a grinding mill, a large piece of equipment that cost about $10M and took 2 years to manufacture. Midway through manufacturing this equipment, the project owner found another similar piece of equipment on the used market that he thought could save us some time. Convinced that this would reduce his schedule and improve his project economics, he was ready to pull the trigger on purchasing the used equipment. He asked us to take a look to confirm what his gut told him was a good idea.
Guess what? Our analysis found that his gut feeling was wrong. Without getting into the details, he would have spent an extra few million dollars to achieve, at most, three weeks of schedule improvement. A simple time-cost tradeoff showed that even under the best-case scenario, there wasn’t enough schedule reduction to justify the extra cost. And that was the best possible outcome…what if things hadn’t gone as well as we’d hoped?
[Sidebar 2: we’ll talk about this in the future, it’s called the planning fallacy and it basically means that we like to engage in wishful thinking. All the time.]
Considering the amount of construction rework and extra engineering that would have been done to accommodate the new mill, we were introducing a large amount of risk and uncertainty that we didn’t totally understand.
Time to step back for a second and take a look at two words I used there: Risk and uncertainty. The analysis I described above was pretty straight-forward – a time-cost trade-off between two different scenarios with different cost/schedule parameters. One scenario involves sticking with the equipment that was already engineered and purchased, another goes with new equipment that requires substantial redesign. Stay with the way we originally planned, or go with a large change? A simple cost and schedule analysis can’t answer the question of which of these scenarios introduces more risk and uncertainty.
We’ll talk a lot more about tools and methods to incorporate risk and uncertainty in our analyses in the coming months. Hit me up with an email if you have specific questions you’d like me to cover.