Challenge
The names, characters, dialects, and phrases are imaginary.
Yesterday, I was one among the spectators, to an event performed at the local stadium. The event may appear to have a certain resemblance to a competition for the first-time visitor. But it was strictly not a competition. Professionals from different disciplines demonstrated their talents.
Every year, pupils from the School of Drona, enthrall the audience with their stellar performance. This year is no exception. An archer, Arjun, fascinated us, by striking the target, by looking at the reflection of it in a pool of water.
Drona, a staunch believer in the personalized coaching school of systems, has helped many individuals to realize their potential.
I decided to interview him the next day to understand how Drona helps these professionals, in transforming themselves into extraordinary performers.
I visited him the next day, to unravel the secret.
Lying on a futon, Drona was relishing in the memories of the previous day.
Drona said, “It is obvious that every great performer practices well, but practice alone is not adequate to become an elite performer.”
He continued narrating about Arjun and his coaching strategy.
Arjun approached him around 6 months before and requested to coach him towards improving his accuracy in striking the target.
Drona guided Arjun to discover the wildly important objective. Arjun is now focusing on realizing an “objective” of 5 misses* in 100 aims in 6 months down the line. (SMART isn’t it?)
Drona helped Arjun to discover 3 “onward” tasks, to be performed for the next three weeks. Let us call the tasks as T1, T2, and T3.
Both of them “observe” the results every week.
Please suggest any possible data-driven techniques that Drona may leverage and ways to align towards the potential of achieving the objective.
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.