agile backlog analyzer
Enter Your Velocity:    
Upload Data File:    

[ Download Sample: Data File (.txt) | Excel (.xls) ]     [ View Screenshots ]

how does this tool work?
Step 1: You will need to create a TAB delimited file (.txt extension only) representing your Product Backlog containing the following columns:
  • Story ID (integer value)
  • Story Name
  • Estimate (using the scale from 1-8 defined below)
  • Theme
  • Milestone ID (integer value)
  • Milestone Name

Please Note: MS Excel is capable of exporting a spreadsheet into a TAB delimited text file (Save As, then select "Text (Tab Delimited)")

Step 2: You will need to estimate your backlog using the index schema in the following table:

Index Best Case Worst Case
1 1 2
2 2 3
3 3 5
4 5 8
5 8 13
6 13 20
7 20 40
8 40 100
Step 3: Enter your Scrum Team's current Velocity
Step 4: Upload your file and view the results, including the Expected Outcome value. This represents the most likely work effort, based on applying a Monte Carlo simulation 5,000 times to each User Story in the supplied Product Backlog. The Expected Outcome value is the average of the simulation results across three different probability distributions.

credits & acknowledgments

I would like to thank Sanzio Castor for publishing "Estimation with no historical data: a Monte Carlo approach" on the Scrum Alliance website. This article provided enough basis surrounding how one might apply Monte Carlo simulation to estimating Product Backlogs.

Also, I used the formulas published by Microsoft (which are also used by SPSS), for calculating the Kurtosis and Skew values, primarily so that when importing and exporting data from this tool your calculations will match exactly what Excel or SPSS outputs.. I learned more about the Monte Carlo simulation theory based on reading Estimating Project Costs, by Duncan Haughey. I brushed up on basic statistics by reading Mean, Mode, Median, and Standard Deviation . Thank you to all of these sources for providing enough information for me to build this tool and I hope everyone finds it useful!