In the "Ask Why" step, is there a specific method (or suite of methods) you use for discovering and validating the causal connections? I've done many RCAs in the nuclear power industry and I'm curious how our methods/toolsets differ. Thanks!
Thanks for sharing a quality video as always! Btw, as I made a quick research on this subject, I found out that the standard definition of RCA from ISO includes 4 steps rather than 7. So I guess you explained the concept, combining the two related concepts (RCA and Corrective Actions) to make the video more self-contained and pragmatic. It was a good watch! Are there some materials on this subject you'd recommend? Thanks again for the good video and feel free to correct me if I'm misunderstanding something.
Thanks so much for the feedback. I included the corrective actions into the RCA because, frankly, an RCA without a plan to avoid it in the future is just a paperwork exercise. Figuring out what happened is only useful if you can use that data to prevent it from happening again.
I need this as a new QA supervisor. Can you show us samples? 1. Determine the NO survey returns is agent driven or Process driven. 2. the impact of call drivers to the resolution rate. that's where I got stuck.
Good video. What type of data structures do you use to represent RCA. In particular, one has logs of various forms. What is the mechanism for them to be put in a logical relationship? This seems to resemble Fault Tree Analysis in my aerospace days. Right now I am leaning to a graphical db for this type of analysis. What is your opinion?
In the "Ask Why" step, is there a specific method (or suite of methods) you use for discovering and validating the causal connections? I've done many RCAs in the nuclear power industry and I'm curious how our methods/toolsets differ. Thanks!
Thanks for sharing a quality video as always!
Btw, as I made a quick research on this subject, I found out that the standard definition of RCA from ISO includes 4 steps rather than 7. So I guess you explained the concept, combining the two related concepts (RCA and Corrective Actions) to make the video more self-contained and pragmatic.
It was a good watch! Are there some materials on this subject you'd recommend?
Thanks again for the good video and feel free to correct me if I'm misunderstanding something.
Thanks so much for the feedback. I included the corrective actions into the RCA because, frankly, an RCA without a plan to avoid it in the future is just a paperwork exercise. Figuring out what happened is only useful if you can use that data to prevent it from happening again.
Hands up who was thinking the entire video that facebook outage was the inspiration to this video.
He looks like AI
It's nauseating to see him write 😢
I need this as a new QA supervisor.
Can you show us samples?
1. Determine the NO survey returns is agent driven or Process driven.
2. the impact of call drivers to the resolution rate.
that's where I got stuck.
Why my man looks like a NPC from gta 4
Is he writing backward...?
It's surprising but nice to be thanked for clicking on a video.
Right? Set such a pleasant tone.
Good content.
Did the explanator just write outside in?
I think they mirrored it in post because his speed of writing would be a little fast for writing backwards
Good call
I was literally searching about this yesterday! Got as far as the 5 Whys until I got bored.
Hi Levy! What would you have liked to learn from this video? 🙂
Good video. What type of data structures do you use to represent RCA. In particular, one has logs of various forms. What is the mechanism for them to be put in a logical relationship? This seems to resemble Fault Tree Analysis in my aerospace days. Right now I am leaning to a graphical db for this type of analysis. What is your opinion?
Helpful. Thanks 😁
great tutorial, but i cant help to notice those squeaky marker sound is distracting
wow, this was very helpful. great advice
Can i use this to fix my procrastination?
Cool
Thanks this will help me in class. Much appreciated 🙏
A more effective method is to talk to the stakeholders.