This presentation shows how to apply Monte-carlo simulation to Scrum and Kanban project models, and then use that model in a variety of ways for experimentation. The results can be used to build a date, staff and cost forecast for projects, and to find what development factors (defects, scope-creep, etc.) are causing the most impact. If you hate estimation, this session demonstrates how to mine data from an existing lifecycle management tools, and then model your process to determine what estimates will make the biggest difference in forecast, allowing you to eliminate other (un-necessary) estimation effort. Agile teams and Executive Management of larger enterprises are often at political odds when it comes to needing estimates, delivery forecasts and the impact of outsourcing. Through the use of modeling and simulating Agile projects as described in this session, you have techniques for quickly answering tough management questions without overburdening the development teams. Modeling and simulating potential project outcomes hundreds of times (using estimate ranges rather than single values) achieves a higher degree of outcome certainty leading to accurate forecasts, and well-informed management decisions. Finding insight from cycletime and other metrics that can be automatically extracted from lifecycle management tools makes modeling and simulation more accessible than ever before. During this session, the process to answer and solve the following questions will be explained - 1. How to reverse engineer and interpret historical data from lifecycle management tools. 2. Does it make economic sense to outsource development or testing? 3. What is the dollar cost of poor quality code (defect leakage)? 4. Do I manage the added-scope problem, or code quality problem first? 5. How do I get the staff I need? By the end of this session you will understand the basics of modeling and simulation, understand the types of problems simulation solves, how to communicate likelihood of outcomes with executive leadership, and be positioned to start applying these fundamentals on your own teams and projects.
http://submit2012.agilealliance.org/files/session_pdfs/Modeling, Simulation & Data Mining - Agile 2012 (Magennis & Maccherone).pdf
