Agile Retrospectives: Making Good Teams Great by Diana Larsen, Esther Derby, Ken Schwaber
Agile Retrospectives: Making Good Teams Great Diana Larsen, Esther Derby, Ken Schwaber ebook
Format: pdf
Publisher: Pragmatic Bookshelf
Page: 181
ISBN: 0977616649, 9780977616640
Pragmatic Bookshelf Publishing Agile Retrospectives, Making Good Teams Great (2006).pdf. Gathering data creates a shared pool of data. Esther Derby (co author of Agile Retrospectives: Making Good Teams Great). Establish a list of factors or objectives to analyze; every member rank those objectives from the team's point of view: how good are we at doing this factor/activity/whatever? Agile Software Development: The Cooperative Game, Alistair Cockburn 11. She's co-author of Behind Closed Doors Secrets of Great Management and Agile Retrospectives: Making Good Teams Great. Agile Retrospectives: Making Good Teams Great, Esther Derby 9. Agility Explained Understand 6 Levels of Agile Planning Agile Retrospectives: Making Good Teams Great! Agile Retrospectives - Making Good Teams Great Publisher : Pragmatic Bookshelf | Author :Diana Larsen | ISBN 0977616649 | PDF | 1.15 MB Release Date 26 July 2006 | 170 pages Want to save time on your next project? Agile Retrospectives – Making good teams great. ƛ籍『Agile Retrospectives: Making Good Teams Great』(^_^) http://www.amazon.co.jp/gp/product/0977616649/. Agile Project Management: Creating Innovative Products, Jim Highsmith 10. Pragmatic Bookshelf Publishing Agile Web Development with Rails, A Pragmatic Guide (2005).pdf. The only true wisdom is in knowing you know nothing.- Socrates. Take a free but the best Scrum crash course. Agile Retrospectives: Making Good Teams Great Esther Derby and Diana Larsen gave a presentation at Google Tech Talk about agile retrospectives. Agile Retrospectives: Making Good Teams Great Diana Larsen, Esther Derby, Ken Schwaber. I recommend the following resources to new team members starting to learn Scrum. Agile Retrospectives: Making Good Teams Great book download. When teams start with Start/Stop/Continue, each person is working from his own data.