A highly scientific method of compiling a feature set

I have been working on the new feature set of ORF recently and invented a proprietary method of compiling a feature set.

First I carefully harvested all major feature requests from our 2005 survey data (yes, your voice is heard :) and compiled a nice OpenOffice.Org Calc table. The rows consist of the following:

  • relative weight (determined from the number of requests)
  • estimated cost
  • realistic estimated cost (optimistic cost multiplied with the very optimistic number of 1.8)
  • relative price/value ratio (calculated from cost/weight)
  • feature name

Now I am at the second step, which means that I am considering to throw away the rating part of my highly scientific table and trust myself that I can pick up the features needed by the users, just likely I did previously. Tables just do not seem to work, even if they are beautified and professional-looking, because they barely have any intuition.

Anyhow, estimations were useful. For example, I have learned that I will need 593 optimistic and 949 realistic days to implement the features requested, which means that we can complete all requests in 3 to 5 years.

Cool! Impossible is our business, I cannot wait to get started :)

3 thoughts on “A highly scientific method of compiling a feature set

  1. Peter Post author

    Are you sure? :) Remember the scene when Scotty tried to communicate with a 20th century computer by _talking to the mouse_ :)

  2. Pingback: Vamsoft Insider » Roadmap Update

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