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@StarweaverGroup Are you available for a business discussion regarding your Udemy course promotion? I don't know if you might be available for a brief call on this. Looking forward to your response Thanks
Thank you for your explanations, easy to understand. However, I would recommend re-recording the audio so there are no glitches and re-uploading the video.
Hey, Cody, Thanks for your feedback. I'm trying to find where there is the interference you mention. Are you able to find that for us? We don't see that and (maybe) it is your connection or a RU-vid issue (not shifting responsibility but curious since we never saw that before). Looking for your further input. Many thanks in advance. BTW, we are running agile programs on our platform, and if you'd like to experience those just check them out, and we can get you some free/low cost, etc. (go.starweaver.com/search?q=agile&t=on-demand,certifications,test-prep,journeys,live-labs) ~Paul Siegel
How do you know your velocity before you even start? Answer: You don't. Average velocity should just be calculated after a few sprints. Also: the product backlog is likely to change. What is the point of sizing all the items in the backlog upfront? Why not only size/refine the ones you know you're going to be doing in the next 1 or 2 sprints?
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Ahh. So is that the reason physicians push drugs so heavily? Since 1 out 250 drugs make it to market, they need to cover all the money lost from the drugs that didn't make it beyond discovery?
Physicians aren't the ones "pushing drugs" and have no obligation to the success of up-and-coming drugs. Pharmaceutical representatives will seek out physicians and present data on a new drug and present a case as to why the physician should be prescribing it over other drugs. If the data is convincing and it costs less or is easier for patients to take, then physicians are likely to suggest to their patients to take it.
We have a vast library of these contents taught on our platform but professionals and instructors from top universities! Visit us on go.starweaver.com/
We have a vast library of these contents taught on our platform but professionals and instructors from top universities! Visit us on go.starweaver.com/
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hi! The approach assumes that we have the total amount of Story Points determined beforehand, what if we have a Product Roadmap that is iterating and adapting based on results/feedback? And also implies that we know before starting, velocity ranges for each team, is that right?
Hi @esteban - I was thinking the same thing. We know that the adaptive approach of Agile requires us to 'harness change for the customer's competitive advantage' and for teams using the popular Scrum framework they will inspect progress / reality in the Sprint Review and adapt the future work (the 'Product Backlog') accordingly. Teams also learn as they go, so continuous refinement might also suggest continuous estimation: what we estimated would be '13' 2-3 sprints ago we might now - now that we've learned more - re-estimate to '8' or, worst, '20' or some other estimation other than the original. The backlog is 'continuously evolving' as the world of work also 'continuously evolves'. So I hear what you're saying and I'm also curious how to capture this Complexity, Uncertainty and the natural Volatility in the world of work (Service Outage anyone? Root Cause Analysis, working on critical defects? - it can all cause Volatility and Uncertainty). Perhaps as more and more datapoints are sampled then we might have more meaningful predictions, but this also assumes 'dynamically stable systems' such as the so-called 'long term stable teams' - but how often do we encounter that in reality: teams are in a state of flux (people resign, get head-hunted, move to different teams or areas in the company) and therefore we have a brand new team that goes through the typical 'Form > Storm > Norm > Perform' cycle - this feeds into the Complexity. All to say, I'm remaining agnostic to these mathematical techniques. I personally don't use them, instead choosing to use leading indicators (both coarse and fine) in my data-driven predictions of delivery. "It's better to be roughly right than precisely wrong" after all...
Use historical data of high level estimates, e.g. t-shirt sizes which were then subsequently broken down and estimated into stories to infer what future comparable high level estimates might be in scope. Same approach as described in the video for velocity but instead for scope. Tbh I would call all this probalistic forecasting.
@@darrex999 Hi Darren! totally agree with your comments, in the end, the main challenge is the fact that management/investors that sponsor/monitor the project or product and its results, they always seek certainty, it is a long journey to learn together to cope with all the variables you mention (and I see everyday as well). In the past I had a rough time explaining that fact that 13 story points for an item would be re-estimated in 8 or 20 at the moment it becomes part of a Sprint Backlog.
