Planning Fallacy, Optimism Bias and Illusion Control

00:02 Remember Jimmy from the previous lesson and the planning fallacy I mentioned? Of course you do.

00:07 So let's discuss.

00:10 Because, well, Jimmy isn't actually terrible at timekeeping, or at least any more terrible than most people.

00:18 So what exactly is it? Let's think about this for a minute.

00:23 Jimmy says that 20 minutes is the minimum amount of time in which he can make it to the office. Let's trust Jimmy on that one.

00:31 We can say that 20 is a solid minimum, no traffic, shortest route and feathering the speed limit.

00:39 Now let's consider the maximum.

00:43 Jimmy says the longest it could take him to get to the office is 40 minutes.

00:48 But what if it's raining or snowing? Mondays usually have heavier traffic too.

00:54 Did he think about this when estimating? What if Jimmy's searching for a parking spot around the office for 10 minutes? Now, less probable, but still possible.

01:05 What if he meets a friend he hasn't seen in ages and they go for a quick coffee before work? What if he punctures the tire? What if aliens invade? There are many things that may slow him down, even if they aren't as probable as just getting stuck in a traffic jam.

01:20 They are still possible and if taken into account will affect the range Jimmy originally estimated.

01:30 So with this new knowledge in mind, we need to readjust the graph we made last time. All these possible slowdowns he forgot when doing the estimation need to be added to the right of our graph so it reflects reality better. If you look at the graph now, you will notice that 40 minutes is really nowhere near the maximum time it could take.

01:51 Jimmy So if you stretch the graph to account for the delays Jimmy could have as well as the likelihood of those things happening.

01:59 It will look something like this with the average time of Jimmy's journey sitting further to the right also.

02:07 But like I said, this is not really Jimmy's fault.

02:11 In fact, he's not the only one who fails to see things like this is general human behavior. So why do humans fall for the planning fallacy? Let's discuss.

02:23 The planning fallacy is a phenomenon in human behavior discovered by Daniel Kahneman and Amos Tversky in 1979, who stated that predictions are often wrong as people underestimate the actual time needed to complete a future task. They believe things will work out well due to the optimism bias. The optimism bias is a term used to describe the behavior whereby people believe they are less at risk of something than somebody else.

02:52 Think of the age old.

02:54 I never thought it would happen to me.

02:57 This is an almost universal cognitive function.

03:01 Therefore, the optimism bias is an understandable reason why people would neglect to think of every worst case scenario when planning.

03:09 Another factor impacting our ability to plan well is the illusion of control.

03:15 This is just what it sounds like in the broadest of terms.

03:19 People often overestimate their ability to control events, focusing on the things they can control rather than the things they can't.

03:27 Think of gambling behavior.

03:30 For example, when people participate in dice games, they tend to throw the dice harder for high numbers and softer for low, as if that's going to make any difference. Okay.

03:41 So what this journey into human cognition teaches us is this.

03:46 People are generally bad at planning and they often fall victims to the planning fallacy, underestimating the time or resources they need to complete a task.

04:00 So let's get back to project management now.

04:04 The project manager is the person who must be aware of these human biases.

04:09 One effective way the project manager can try to make themselves aware of events that may slow a task down is to perform a SWOT analysis.

04:17 So on top of taking all available opportunities and working off the strengths, a project manager can also limit weaknesses and protect against threats to creating a realistic plan.

04:29 In conclusion.

04:30 Estimation takes a lot of deliberate thought and information.

04:34 It's nowhere near as simple as Jimmy's first guess.

04:37 Right? Oh, and one last thing.

04:42 If the project manager is really, really stuck, they can use the following formula.

04:50 The three point estimate.

04:52 But remember, a project manager should rely on their skills and experience first.

04:58 But if they need to, they can think of each task as having three time estimates. The optimistic time estimate will call O, the most likely or normal time estimate will call M.

05:12 And the pessimistic time estimate.

05:14 P. The expected time T is estimated by putting the values into the following formula.

05:23 Plug the numbers in and you get a time estimate.

05:27 Although the average is a good point to put an estimate.

05:30 If you think about it, there is a 50% chance of finishing before our estimate and 50% chance of going beyond it.

05:38 So would you feel comfortable presenting a project schedule and saying to the team in the kickoff meeting, we have about 50% chance of succeeding with the plan I have created? Probably not.

05:50 So that's where the next lesson comes in, where we will be talking about buffers. See you there.