Charlie Brown loved sport.
Despite all experience he ran up to the ball believing that this time, for once, just this time, Lucy would not pull the ball away.
Oh dear. His behaviour is a classic example of optimism bias. One of several types of bias that slant our decision making.
Optimism bias is the demonstrated systematic tendency for people to be overly optimistic about the outcome of planned actions. This includes over-estimating the likelihood of positive events and under-estimating the likelihood of negative events.
There is a specific type of this bias which affects planning – it is known as the Planning Fallacy, used in the sense of a project planning fallacy, a tendency to underestimate how is needed to complete a task, even when they have past experience of similar tasks over-running.
The term was first proposed in a 1979 paper by Daniel Kahneman and Amos Tversky.
In 2003, Lovallo and Kahneman proposed an expanded definition where the planning fallacy results in not only time overruns, but also cost overruns and benefit shortfalls (Lovallo, Dan; Daniel Kahneman (July 2003). “Delusions of Success: How Optimism Undermines Executives’ Decisions”. Harvard Business Review: 56–63).
Hofstadter’s Law: it always takes longer than you expect, even when you take into account Hofstadter’s Law.” — Douglas Hofstadter, cognitive scientist and Pulitzer Prize–winning author of Gödel, Escher, Bach: An Eternal Golden Braid
The term ‘fallacy’ implies that it is a logical fallacy – which it is not. I prefer to think of it as the optimistic planning bias.
There is even a concept called the rule of pi, which is to multiply time you think something will take by pi. (this was invented by Nasa scientist von Tiesenhausen, who invented the lunar rover, as a half joke – perhaps from having to run around in circles).
So what should a project manager do then, add a buffer of X2 or X3.1597…… to each task? The problem is this is the very worst thing you can do.
Eliyahu M. Goldratt is one of the key thinkers has how to make things run on time and on budget. His solution is ingenious and ill look at in fully in another lecture For now only deal with the issue of estimation.
Goldratt noticed that whilst project managers tended to be overoptimistic, those specifically responsible for tasks tended to be pessimistic, was there a connection between the two? The connection of course is blame avoidance.
As Steve Jobs has observed you cant make excuses the closer you get to vice-president, that privelege is only for lowly workers.
If someone thinks a task might take a day, they might estimate for it to take longer in the project plan. But this creates problems. Goldratt noticed that it led to people starting to fully apply themselves to a task just at the last possible moment before a deadline – wryly he called this the Student Syndrome. And of course there is parkinsons law – work expands to fill the time available – to create the impression they are invaluable. Economists would also say this is because the undervaluing of the cost of time leads to demand meeting supply.
Effectivley people are adding a buffer before each task. What then if someone starts a task early, if they do the buffer can be wasted, especially if the project planner doesnt know this and cannot assign a new task.
There is also an equivalent to student syndrome with costs – Parkinsons Law of Finance ‘work expands to fulfill the available budget’.
It is not then a simplistic solution to say that things have gone wrong because we have underestimated – if the ‘solution’ of overestimating can lead to things going badly wrong.
One of the problems is that the longer an estimate is, the more uncertainty it contains. You are asking someone to give a single point estimation on a probability distribution, with a fixed minimum period (zero) and an unknowably long tail.
A brillaint solution to this is to play what is called ‘Planning Poker’ – this involves a pack of cards using the fibbionoci sequence – 0, ½, 1, 2, 3, 5, 8, 13, 20, 40, 100, which represent days for a task. Players in a team secretly make an estimate for task length, then reveal their card, and defend it even if the task is not theirs.
This avoids Anchoring – someone saying ‘”I think this is an easy job, I can’t see it taking longer than a couple of weeks” and none wanting to disagree. The seqence of numbers through clever maths deals well with the uncertainty issue. Estimation is also a learnable skill and as with anything else social learning is quicker than individual learning.
Molokken-Ostvold & K. Haugen, N.C. (13 April 2007). “Combining Estimates with Planning Poker–An Empirical Study”. IEEE – found that that estimates obtained with this method were less optimistic and more accurate, than estimates obtained through atomic self assessments for the same tasks.
Better estimates does not however mean that these should be translated into targetted task lengths in a project plan – for the reasons we have discussed.
Estimates are not committments, they are not plans to meet a target. Decoupling the two, and adopting new tecniques to ensure committments is often the key to solving this dilemma. You can only make an accurate commitment when you know you can deliver.
One important technique now widely used in infrastructure planning, to avoid optimism bias in estimating the economic benefits of projects is called Reference Class Forecasting developed by Daniel Kahneman and Amos Tversky, and helped Kahneman win the Nobel Prize
The idea is that a reference class of past, similar projects is used and studied, taking an outside view helps avoid the optimism bias of those designing a scheme, as those designing it are understandably biased to stress its benefits.
In America it is now officially endorsed by the APA.
“APA encourages planners to use reference class forecasting in addition to traditional methods as a way to improve accuracy. The reference class forecasting method is beneficial for non-routine projects … Planners should never rely solely on civil engineering technology as a way to generate project forecasts” (the American Planning Association 2005).”
It has been used in the uk to estimate the true benefits of the proposed Edinburgh Tram.
It could be used far more, for example to estimate the true infrastructure costs, and true time to completion for different housebuilders in different areas, in looking at the deliverability and phasing of major housing sites.