Divergence: bid estimates vs planning estimates 

​Fixed price bids need to control scope, and make assumptions to meet that bid.

Fixed price bids never survive contact with reality.

The first thing I do with those assumptions when delivering a project is pull those assumptions onto the plan, because every one is an unanswered question that needs to be validated, and each one probably has more assumptions behind it. If it’s hosted on the customer site, what version of Windows and SQL server will it run, what ports will be available, what libraries can we install, …? If we host it, What availability and resilience requirements does the customer have? What are the SLAs?

There are ways to model these in bids, but each one represents a waypoint where scope will change, sometimes our assumptions will be correct, often they will need to adapt to unforeseen information.

Ultimately, the public procurement process is not designed for change, despite the improvement GDS is driving. (possibly private too, but I’m in no place to comment). Trying to estimate for everything up front has always been a fools game, but attaching money to them makes estimates even more of a negotiation, turning them into notional numbers dependent on a massive pile of assumptions that only Mulder would believe. 

Treat assumptions as dependencies, and don’t trust any estimate, or requirement that depends on them. Test your assumptions. Always. And test yourself to know what assumptions you’ve made implicitly. 

And stop wasting time estimating

4 replies on “Divergence: bid estimates vs planning estimates ”

I have been accused of being Mulder, and I don’t believe fixed estimates are ever a good idea [though I concede that they are still mandated in many scenarios]. In far too many cases the only viable choice is to inflate the price to account for contingencies, resulting in the customer/client paying more (sometime much more) than they should.

I 100% agree with “test your assumptions” and to do this accurately requires data, such as that gathered in a robust ALM environment with effective unified tooling.

However, I disagree on the premise (in the linked article) of “stop estimating” and that accurate estimates can not be achieved at the lower (story) levels [IMPO the big picture problem is that stories get added/removed/altered to such a degree that even if the estimates were perfect, the total outcome would still be radically different]

Liked by 1 person

I’m trying the no estimates approach at the moment, but the work is far more research based, where I think it makes sense.


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