Whether you’re a Project Manager or any other interested party in the project (aka Stakeholder) you MUST understand the difference between an Estimate and a Guesstimate.

On the surface they both look the same as, in a project context, they would normally be represented using some quantitative measures assigned to time or cost variables.

Where they differ is their respective dependency on prior actual observation.

An estimate is a quantitative approximation based on previously observed data. The more relevant the data is, the higher will be the expectation that the approximation will be close to the true outcome (and the lower would be the uncertainty associated with this approximation).

A guesstimate is a quantitative approximation NOT based on previously observed data – and is rather based on gut-feel and a guess. Naturally this will attract a higher level of uncertainty.

Knowing the basis for your project’s cost and schedule approximation is crucially important and should be clearly communicated to all relevant stakeholders.

Think about it!

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  9. Shim,

    A brief but stimulating post.

    I do think that there is often confusion between the two. In fact, in practice, we may be forced to use both. The trouble with estimating techniques (e.g. in software development) is that it attempts to “parameterise” everything, without necessarily recognising the interaction between these variables. For example an approach such as COCOMOII has (from memory) around 17 variables which can calibrated independently of each other, though there may be some sort of relationship between them. Also, those actual cause-and-effect relationships may not be that clear.

    We are also taught that each project is unique and therefore there will be a limit to the relevance of a past project to the work being estimated. One aspect may correlate very well, but others may not. This is not to say we such not use “estimates” but they are underpinned by assumptions (in relation to their relevance to the work at hand).

    Whilst I agree that “guesstimates” are not based specific upon previously observed data, they do have a role to play. Heuristics / rules-of-thumb do provide a starting point at least – for example we can look at a range of schedule durations based upon estimated person-months’ effort: we might subconsciously consider this to represent 2 standard deviations from the mean. Of course, this is not very ‘scientific” but it might be argued that over-reliance upon “estimating” using models which have assumptions that differ (in nature or value) from the current work can also mislead.

    In both (but probably more in “guesstimating”), we also need to caution against biases (such as anchoring or availability) – the things against which Kahneman and Tversky have cautioned.

    I am sure your post will attract comments which are more informed than mine, but I thought I would start the ball rolling.

    Terry

    Reply

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