## 29 January 2012

### The Shape of a Sample Distribution

When I'm writing about sample distributions, I realize that I throw the 'shape' and 'order' terminology around assuming they're understood in this context. What I've never done is a proper treatment of either one, so here's 'shape'.

The use of the term shape comes from its informal use in statistics, referring to the characteristic shape of the graphs used to picture various probability distributions. A distribution’s shape refers to the relationship between values and their probabilities. The normal, or Gaussian, distribution has its characteristic bell shape, the power law distribution has its ski-hill shape, and so on. That also applies to sample distributions, but they just are what they are – we don't give them names.

There are a bunch of things you can say about a sample distribution's shape:

## 26 January 2012

### Risk is not discovered, it's chosen

Every so often I get a thought that puts an edge on one of my knives, and "Risk is not discovered, it's chosen" is one of them.

When you tell a stakeholder, "This project will be done in seven months," are you honest enough to tell her that there's a risk of not meeting that target, but she shouldn't worry about it, that you've made the decision about how much risk is acceptable on her behalf?

Given whatever method you use for estimating, do you even know what the probability of missing the target is?

Risk is a choice. The big question to ask is, "Has the choice been made knowingly? – And by the right person?"

## 13 January 2012

### Bake Risk Management into the Plan

How do you manage the risk in a project? The default is a risk management program that's essentially out of band. The project and the risk management are separate tracks, often staffed with different people.

The first problem this creates is synchronization - making sure that changes in the project are reflected in the risk management plan and vice versa. The next problem is that there are two different groups of people with diverse objectives - and only one of them is focused on a successful project.

## Integrated Risk Management

The probability management solution to this is to bake the risks into the plan with everything else. This way, there's one plan, one process, one team, one manager executing the project.

What does that mean? It means that we include risk events and responses as elements of the plan along with the tasks and milestones.

## 04 January 2012

### Simulation the Probability Management Way

Let's start at the beginning:

## Modeling with Uncertainty

We use computer models to help us foresee the course and consequences of decisions we might make. As it is with all science, the goal is clairvoyance.

If it's well-designed, a model is faithful to the real-world process the decisions will affect; it tells us what's likely to change in the real world if we make this decision or that assumption.

Modeling a process when the inputs are assumed to be correct and exact – using a formula that puts out The One True Answer as a result – is relatively straightforward. It's what we do when we calculate what will happen to our bank balance if we decide to buy an expensive toy. It's also what we do to estimate projects with CPM or PERT, assuring optimistic estimates that help get projects approved.

But it's not always so simple; sometimes a scalar mathematical model won't give us what we need to make an informed decision. This is the case when some of the input assumptions are uncertain variables.