Generative AI for process improvement : advanced guide (accredited).

Format:

Video

Contributor:

Smart Growth Network, instructor, publisher.

Language:

English

Subjects (All):

Generative artificial intelligence.

Production engineering.

Physical Description:

1 online resource (1 video file (4 hr., 32 min.)) : sound, color.

Edition:

[First edition].

Place of Publication:

[Washington, D.C.] : Smart Growth Network, 2026.

Summary:

Generative AI for Process Improvement - Advanced Guide (Accredited) The chart that gets built is almost never the chart that answers the question. It is the chart the software made easy. Look at the analysis packs circulating inside most organizations and you will find the same three visuals repeated endlessly: a bar chart, a line chart, and a pie chart nobody can read. Not because those are the right tools, but because they were the default options in the menu. So a team compares two processes using average cycle time and never sees that one of them is bimodal. A leadership group signs off on an improvement target based on a trend line that conceals a widening spread. A category is declared the priority because its bar is tallest, when a proper concentration analysis would have pointed somewhere else entirely. For a long time this was a defensible compromise. Producing a violin plot or a properly ordered concentration chart meant statistical software, a specialist, or a week of waiting. The economics favored the easy chart, and the easy chart usually got the decision approximately right. That constraint is gone. Conversational AI tools now generate any visualization you can describe in a sentence, from a raw data file, in under a minute. Which means the production cost of a sophisticated chart has collapsed to almost nothing, and the entire remaining skill has moved somewhere else: knowing which visual actually answers the question in front of you, and being able to read what it says without fooling yourself.

Notes:

OCLC-licensed vendor bibliographic record.

OCLC:

1613930082

Publisher Number:

13110GPT2B