Read more about the general principles of Value estimation here.
alh-optional:isAggregatingValue
Accumulate Value
Value estimates can be set directly for the alh-replace:typeepic/alh-replace, even if they are only intended as preliminary estimates on a high level.
You can manually control when this preliminary original estimate should be replaced with accumulated estimates. It is recommended to accumulate value, when the alh-replace:typeepic/alh-replacehas been decomposed and all stories and epic below have been sufficiently estimated.
Before choosing to accumulate value, you can click Preview Accumulated Value to preview the result of accumulating.
When the numerical value is accumulated, the original estimate is preserved and still visible in the overview. Should you choose to revert to not accumulating value, the original value can be inserted.
alh-optional:enableKano,enableIsMustHave
Note that the alh-replace:typeepic/alh-replace may still be be classified according to the chosen value classification system even though it accumulates value. Therefore, the alh-replace:typeepic/alh-replace can be set as a Must-have and accumulate value at the same time. Read more about working with Must-haves here.
/alh-optional
/alh-optional
alh-optional:aggrValueAlgorithm
Accumulation Method
The accumulated expected value of the alh-replace:typeepic/alh-replaceis the simple sum of the expected value of all stories/epics beneath it.
However, deriving the accumulated worst-case value is not as simple. It depends on whether you assume all the children to be mutually independent (i.e. if one story turns out to have less value, this does not necessarily affect the others) or if you assume the children to be mutually dependent (i.e. if one story turns out to have less value, so will all probably). Based on this assumption, the worst-case value can be derived using either of the two methods:
- Root-sum-squared for mutually independent children – more than a simple sum of worst-case estimates: expected – √(∑(worst – expected)2)
- Simple sum of worst-case estimates for mutually dependent children
/alh-optional
alh-optional:kanoClass
Kano
The customer satisfaction of the alh-replace:typestory/alh-replace can be classified using the Kano model. Read more about the categories in Kano classification.
If the alh-replace:typestory/alh-replace is classified as a Must-have (or Reverse/Indifferent) it cannot at the same time have a numerical value. Read more about working with Must-haves here and how the Must-have state is inherited to children of epics.
If the alh-replace:typestory/alh-replace is classified as a Satisfier or Exciter the numerical value can be set (unless value is accumulated).
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alh-optional:mustHaveState
Must-have
The alh-replace:typestory/alh-replace can be classified as being either a Must-have or not a Must-have. If it classified as a Must-have it cannot at the same time have a numerical value.
Read more about working with Must-haves here and how the Must-have state is inherited to children of epics.
/alh-optional
alh-optional:bValueExpected
Value
Numerical value is the quantification of how much value is obtained by completing the alh-replace:typestory/alh-replace. Whether value is estimated in story points or some other unit is optional in Agemba. Depending on the circle configuration, value is either set from a number series or set freely.
Until a value estimate is set, the alh-replace:typestory/alh-replacewill count as having no – unless a provisional/default estimate is set for this circle. This estimate will be shown in brackets e.g. (2) until a real estimate is set.
alh-optional:isAggregatingValue
Value can only be set directly, if this alh-replace:typeepic/alh-replace does not accumulate value from its children.
/alh-optional
alh-optional:bValueWorstCase
Value is estimated with both an expected and worst-case estimate. The expected is what you believe is a realistic estimate with 50% certainty (it should not be confused with an optimistic best-case estimate). The worst-case estimate represents a realistic estimate with a 90% certainty. The worst-case value estimate cannot be higher than the expected.
Together these two estimates are used to derive the certainty in percentage. The higher the difference between the two, the higher the uncertainty. Read more about working with uncertainties.
/alh-optional
/alh-optional
