Herewith I propose a data driven approach using JIRA: The most important thing is to have enough issues in place to make statistical analysis meaningful, let's say at least 30 issues. After that, we need to make sure that we close issues faster than we create them. Only after we satisfy these two conditions can we talk about reasonable finish time estimations.
Below is my proposed project status page that updates whenever issues change, i.e. you do not need to ask people about when the project will finish or what the completion percentage is, it is all done instantly and automatically. The manager will always have up to date estimations. Only after your team has sufficient practice with this system should you worry about velocity/burndown etc. charts.
Calculation of parameters:
Enough issues = Total nb of issues > 30 ? Green : Red
Issues decreasing = (nb of closed issues in last 3 months) > (nb of created issues in last 3 months) ? Green : Red
Avg. nb of issues closed per month = (nb of issues closed) / (nb of months passed from project start)
Months required to finish project = (nb of open issues)/(avg. nb of issues closed per month)
Estimated finish date = Todays date + Months required to finish project
Estimated completion = (nb of closed issues) / (total nb of issues) *100
2 comments:
Merhaba Samil Bey, cok ilginc bir yontem :) ortalama süre hesabı oldugu icin dogru sonuclar vermez gibi geliyor ama hic dogrulama sansiniz oldu mu bu yontemi? Tesekkurler.
Sonuçların doğruluğu girilen issue sayısına bağlı. Elbette varyasyon olacaktır ama bugüne kadar uyguladığımız tüm yöntemlerden daha başarılı olduğunu söyleyebilirim.
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