– A. Competency
– B. Enabler
– C. Practice
– D. Measure of effectiveness
– E. Project outcome
– F. None of the above list
1. Defects reported 30 days beyond product acceptance by the customer
2. Ability to clearly distinguish between risk mitigation actions and contingency actions
3. Performance of the “shadow” Tech Lead when the primary Tech Lead is away due to a personal contingency
4. Organization’s risk appetite
5. Tracking project assumptions on a continual basis as a source of risk
6. Customer responsiveness on project issues
7. Risk repository and templates
8. Appointment of a contract administrator
9. Knowledge of customer’s business domain
10. Number of risks that occurred that were not identified earlier
Suggested solution:
1. Defects reported 30 days beyond product acceptance by the customer (project outcome)
2. Ability to clearly distinguish between risk mitigation actions and contingency actions (risk related competency)
3. Performance of the “shadow” Tech Lead when the primary Tech Lead is away due to a personal contingency (measure of effectiveness)
4. Organization’s risk appetite (enabler/culture)
5. Tracking project assumptions on a continual basis as a source of risk (practice)
6. Customer responsiveness on project issues (none of the above in list)
7. Risk repository and templates (enabler/infra)
8. Appointment of a contract administrator (none of the above in list)
9. Knowledge of customer’s business domain (enabler/domain expertise)
10. Number of risks that occurred that were not identified earlier (measure of effectiveness)
2 Responses
Velocity of each individual iteration will be a different figure. There are many ways velocity gets impacted. Apart from planned absence (planned leave, training etc.) and holidays, there could be unplanned absences caused by illness, personal emergency etc. which impact velocity. User stories that do not get completed in an iteration get moved to next iteration. This brings down the velocity of the iteration where the story was started and bumps up the velocity of the iteration where it got completed. This being the situation, good practice is to take an average of last five or six iterations as the velocity of the team. Team stability is another factor that impacts velocity. Teams that have higher churn will see higher volatility in velocity. Other factors such as change in technology, adoption of new tools, increase in automation, will also impact velocity either positively or negatively! However, if team is stable and has reached “performing stage” steady rise in average velocity will be seen over a period of time till any of the factors mentioned above comes into play and impacts it.
Thanks Milind, fully agree with your comment.
Finally, irrespective of the increasing trend in velocity, there is improvement for sure. This cannot be missed, if observed. One of the intent of my blog is to encourage this observation, by taking a mildly provocative stand.