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how_can_we_scale_our_estimating_approach_beyond_a_team [2019/01/21 09:08] – Reading enhancements hpsamioshow_can_we_scale_our_estimating_approach_beyond_a_team [2021/12/08 13:47] (current) – external edit 127.0.0.1
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 What this means is that in most places I have worked, organizations end up with the Pure Feature and Epic Points approach where Feature Points are the Fibonacci numbers times 10 (10, 20, 30, …, 130) and the Epic points are the Fibonacci numbers times 100 (100, 200, 300, …, 1300). The other thing that organizations do is limited the highest number to 13 or 20, no 100’s etc, with the idea that this encourages people to split the work up if it gets to this level. So if there is a Feature Point estimate of “this is more than 130”, the discussion is “Perhaps this is an Epic? Or perhaps we need to split the work so that it will fit in a quarter.” This is a good discussion to have. What this means is that in most places I have worked, organizations end up with the Pure Feature and Epic Points approach where Feature Points are the Fibonacci numbers times 10 (10, 20, 30, …, 130) and the Epic points are the Fibonacci numbers times 100 (100, 200, 300, …, 1300). The other thing that organizations do is limited the highest number to 13 or 20, no 100’s etc, with the idea that this encourages people to split the work up if it gets to this level. So if there is a Feature Point estimate of “this is more than 130”, the discussion is “Perhaps this is an Epic? Or perhaps we need to split the work so that it will fit in a quarter.” This is a good discussion to have.
 +
 +One final note on this. Many organizations I've worked with like to abstract estimation one step further by using t-shirt sizes for estimates. For many it is easy to say "in comparison to this small piece of work, this is a large"; it helps because since there are no numbers, you don't think about time. Once they have the t-shirt size, organizations usually settle on a mapping between these t-shirt sizes and Feature or Epic points. The following diagram shows a sample mapping that might be put in place:
 +
 +{{ ::sample_mapping_of_t-shirt_size_to_points.png?400 |}}
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 +Note that the mapping and the numbers would be validated to ensure that there is in fact a meaningful mapping between a feature we call "small" and the actual story points needed to complete that feature.
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 +One final note. Some organizations I’ve worked with step back from an either or approach and work a both and approach. When little is know about the Feature, say when it is still being analyzed, they use a Feature point scaling based on S, M, L t-shirt sizing. They then equate the t-shirt size to numbers, so a S might be a 3 Feature Points, M might be 8, and so on. Then, as they learn more and understand the kind of work they have they move to a summated story point approach to Feature size; a second estimate, if you like.
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 +====== Want to Know More? ======
 +
 +  * [[https://www.mountaingoatsoftware.com/blog/why-the-fibonacci-sequence-works-well-for-estimating|Why the Fibonacci Sequence Works for Estimating]] - Weber’s Law approach from Mike Cohn
 +  * [[http://www.yakyma.com/2012/05/why-progressive-estimation-scale-is-so.html|Why Progressive Estimation Scale is So Efficient]] - Information theory approach from Alex Yakyma
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 {{tag>Team Estimates Forecast FAQ Scaling Points}} {{tag>Team Estimates Forecast FAQ Scaling Points}}
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