Drunk Agile

Potentially the most important concept in Agile that no one talks about is the difference between ex ante and ex post. Much of Agile assumes ex ante knowledge that you just don't have. #Nisha, Prateek, and Dan discuss on this week's episode of Drunk Agile.

Agile expert Nisha, product management specialist Dan, and software development guru Prateek explore using Monte Carlo simulation to forecast completion times for products when backlog size is unknown. They discuss utilizing the simulation for project estimation with uncertain work item counts, managing uncertainty in backlog items, and forecasting future work in Agile projects through historical data analysis and simulations.

Most #agile frameworks love to talk about "done" and most forecasting is centered around done. But how do we forecast when something will begin? (spoiler alert: or do we?) Join Nisha, Dan, and Prateek to find out in this week's episode of Drunk Agile.

Dan, Prateek and Nisha discuss how to answer the question of "When will it be done" for an item that is still in the backlog. Can Monte Carlo help?

Jose Casal joins Nisha, Dan and Prateek for this week's edition of Drunk Agile where we talk about OKRs. Well, Jose and Prateek talk and Dan just channels his inner Demming.

Nisha, Dan and Prateek answer an audience question about when is it appropriate to use Cycle Time Scatterplot vs Monte Carlo for predictions.

Dan, Nisha and Prateek host Chad and Jeff as they talk about the shipping problems of the world and of course... aging.

Johanna Rothman comes back to visit Nisha, Dan and Prateek to talk about more aspects of aging. More whisky, more insights, more bigger aging.

Karl Scotland, an expert in agile methodologies, joins the hosts to unravel the concept of predictability in agile development. They dive into the challenges of measuring productivity, advocating for meaningful metrics beyond lead time. A light-hearted whiskey tasting leads to serious discussions on minimizing variability in project delivery. Scotland emphasizes the importance of aligning customer expectations with actual capabilities, while redefining productivity to focus on value and satisfaction rather than sheer output.

In a lively discussion, the hosts toast to their favorite bourbons while diving into the concepts of leading and lagging indicators in agile frameworks. They challenge the importance of their distinction, emphasizing that timely action matters more than mere categorization. The conversation also includes insights from Monte Carlo simulations on Work In Progress, questioning common assumptions about cycle time. Ultimately, they highlight the importance of actionable insights and fostering a culture of learning to drive real improvements.