Twelve glowing voice booths in a dark silver hall, each holding an abstract luminous silhouette

Participant voices · P1–P12

In their own words

Verbatim quotations from the dissertation, including informal phrasing — the study deliberately did not smooth participants’ language into formal prose.

AI-generated conceptual illustration · Not research evidence or a real study site

Imaginary professionals seated in a blue-silver interview studio with a recording console
Listening to workplace perspectives while keeping participant identities anonymous.AI-generated illustration · Not research evidence or a real study site

Table 4.1 · Who spoke

Twelve participants, seven organizational contexts

Supply chain and logistics, banking IT, higher education, software engineering, logistics technology, government human services, and frontline manufacturing. Y = clearly evidenced, P = partial or adjacent, — = not evidenced.

All faces are AI-generated, imaginary human icons—not participant photographs. They do not represent participants’ actual appearance, age, gender, or ethnicity. Research identities remain P1–P12.

Fictional human portrait for P1; not the actual participant

P1

Design/UX lead, logistics-tech software vendor

Fictional human portrait for P2; not the actual participant

P2

VP/Head of Operations, supply-chain distribution

Fictional human portrait for P3; not the actual participant

P3

Founder, logistics-data tech startup; former operations/consulting

Fictional human portrait for P4; not the actual participant

P4

IT professional, banking sector

Fictional human portrait for P5; not the actual participant

P5

Higher education administrator / adjunct faculty

Fictional human portrait for P6; not the actual participant

P6

Backend software engineer, observability platform

Fictional human portrait for P7; not the actual participant

P7

QA / software test analyst, state government

Fictional human portrait for P8; not the actual participant

P8

Frontline production employee, manufacturing/assembly

Fictional human portrait for P9; not the actual participant

P9

Frontline production/warehouse employee, wind energy manufacturing

Fictional human portrait for P10; not the actual participant

P10

Logistics manager, wind energy manufacturing (multi-facility)

Fictional human portrait for P11; not the actual participant

P11

Buyer/procurement specialist, supply chain (purchasing)

Fictional human portrait for P12; not the actual participant

P12

Frontline production/operations employee, wind energy manufacturing (mobile reporting)

IDRole / fieldFrontlineManagerSupply chainIT / dataDashboard / BIERPAI
Fictional human portrait for P1; not the actual participantP1
Design/UX lead, logistics-tech software vendor——PPYYY
Fictional human portrait for P2; not the actual participantP2
VP/Head of Operations, supply-chain distribution—YY—YYY
Fictional human portrait for P3; not the actual participantP3
Founder, logistics-data tech startup; former operations/consulting—YPPYYY
Fictional human portrait for P4; not the actual participantP4
IT professional, banking sectorY——YYY—
Fictional human portrait for P5; not the actual participantP5
Higher education administrator / adjunct faculty————P—Y
Fictional human portrait for P6; not the actual participantP6
Backend software engineer, observability platformY——YY—Y
Fictional human portrait for P7; not the actual participantP7
QA / software test analyst, state governmentY——PP—Y
Fictional human portrait for P8; not the actual participantP8
Frontline production employee, manufacturing/assemblyNo direct access to any data system — information received exclusively through verbal briefings.Y—PPY——
Fictional human portrait for P9; not the actual participantP9
Frontline production/warehouse employee, wind energy manufacturingY—PPYYY
Fictional human portrait for P10; not the actual participantP10
Logistics manager, wind energy manufacturing (multi-facility)—YYPYYY
Fictional human portrait for P11; not the actual participantP11
Buyer/procurement specialist, supply chain (purchasing)Built a personal “cheat sheet” of validated data outside the ERP after recurring data-quality problems.——YYYY—
Fictional human portrait for P12; not the actual participantP12
Frontline production/operations employee, wind energy manufacturing (mobile reporting)Y—PPYPY
Translucent glass quotation fragments suspended in a dark hall, their light forming a rising wave
An imagined workplace conversation; the quotations below come from the dissertation.AI-generated illustration · Not research evidence or a real study site

Verbatim evidence

“The data became much more meaningful when leadership explained the story behind the numbers.”
Fictional human portrait for P5; not the actual participantP5Theme 02
“We somehow assume the person who reads it understands what those numbers mean.”
Fictional human portrait for P4; not the actual participantP4Theme 02
“I realized that data doesn't always tell the entire story by itself.”
Fictional human portrait for P9; not the actual participantP9Theme 02
“You have the starting point, you have what changed, you have the impact, and then you have the response.”
Fictional human portrait for P10; not the actual participantP10Theme 02
“If I simply put a spreadsheet on the screen, people may look at it, but they may not understand what they're supposed to take away from it.”
Fictional human portrait for P10; not the actual participantP10Theme 02
“If I just report, 'Part missing,' that's not very useful. But if the system shows that it's needed for a specific operation or that the shortage is preventing us from moving forward, people understand the urgency better.”
Fictional human portrait for P12; not the actual participantP12Theme 02
“If you show us that a certain supplier delay is going to stop a production activity tomorrow, people pay attention because now the data has meaning.”
Fictional human portrait for P9; not the actual participantP9Theme 02
“It turns data from something people simply review into something they can actually use to improve their work.”
Fictional human portrait for P5; not the actual participantP5Theme 02
“The data gets overwhelmingly boring at times because you're just doing the same thing over and over and over again.”
Fictional human portrait for P11; not the actual participantP11Theme 02
“People start to go, oh, wow, I didn't realize this… And then the debate sparks, right? Then you start and they go, why did that happen?”
Fictional human portrait for P3; not the actual participantP3Theme 03
“Some systems are easier to understand after somebody actually walks you through them.”
Fictional human portrait for P9; not the actual participantP9Theme 03
“The ERP system provides the data, but the decision still requires human interpretation.”
Fictional human portrait for P10; not the actual participantP10Theme 03
“When they see that the warehouse responds and the material arrives, they understand that reporting the information actually helps the operation.”
Fictional human portrait for P12; not the actual participantP12Theme 03
“If employees report shortages and nothing happens, eventually they may stop using the process.”
Fictional human portrait for P12; not the actual participantP12Theme 03
“Even when they're there, they're not a proper training that's involved and then everybody has their own way of looking at those data.”
Fictional human portrait for P11; not the actual participantP11Theme 03
“Some executives, they don't have the full stories. They just see someone prepared that number and they started announcing it.”
Fictional human portrait for P4; not the actual participantP4Theme 03
“Visuals reduce connective load because they allow you to recognize the patterns much faster than reading tables full of numbers.”
Fictional human portrait for P5; not the actual participantP5Theme 04
“If I see a dashboard showing overdue deliveries, for example, I can understand the situation much faster than if somebody gives me a spreadsheet with hundreds of rows.”
Fictional human portrait for P9; not the actual participantP9Theme 04
“I think a good dashboard should answer three questions: What happened? Why does it matter? And what do I need to do?”
Fictional human portrait for P9; not the actual participantP9Theme 04
“The same information, the same metric, the same dashboard, the same report is and will always be interpreted in different ways by different level of people.”
Fictional human portrait for P7; not the actual participantP7Theme 04
“When you start putting stuff on a map, right? It sounds so simple, but… you show them something they did not know.”
Fictional human portrait for P3; not the actual participantP3Theme 04
“A number by itself doesn't always catch my attention. But if something is highlighted or there is an indicator showing that action is needed, I notice it much faster.”
Fictional human portrait for P12; not the actual participantP12Theme 04
“The dashboard tells us what is happening, but the people on the floor provide the context.”
Fictional human portrait for P12; not the actual participantP12Theme 04
“It confuses you. A lot of people don't know how to read bars or graphs.”
Fictional human portrait for P8; not the actual participantP8Theme 04
“Employees trust the information more when there is a connection between what the system says and what we actually experience.”
Fictional human portrait for P12; not the actual participantP12Theme 05
“I'm always very skeptical, right, when I see people presenting data, because I know what it takes to get a data set in good shape.”
Fictional human portrait for P3; not the actual participantP3Theme 05
“The story doesn't change if you take out 2% of the data, right? The story stays the same.”
Fictional human portrait for P3; not the actual participantP3Theme 05
“Employees engage more often when data is directly connected to their work and when leaders explain why the information matters.”
Fictional human portrait for P5; not the actual participantP5Theme 05
“Transparency, context… context and consistency are what build trust for me.”
Fictional human portrait for P5; not the actual participantP5Theme 05
“If there's a conflicting information going around, that just defeats the purpose of the data coming out of the system.”
Fictional human portrait for P11; not the actual participantP11Theme 05
“Trust is earned. It's not given.”
Fictional human portrait for P8; not the actual participantP8Theme 05
“They'll tell you, oh, the deadline is two months from now, but the deadline is really six months from now… they spin you.”
Fictional human portrait for P8; not the actual participantP8Theme 05
“I want something that makes an impact on me or to me, to my group, to my team. Tell me something that will help me, obviously.”
Fictional human portrait for P2; not the actual participantP2Theme 05
“If I'm working in the warehouse and someone shows me a dashboard with 20 different metrics that don't relate to my work, I'm probably not going to remember much of it.”
Fictional human portrait for P9; not the actual participantP9Theme 05
“If I show somebody 15 different KPIs and don't explain which ones matter, I've probably created more confusion than understanding.”
Fictional human portrait for P10; not the actual participantP10Theme 05
“That's top level management controlling the information that's filtered down.”
Fictional human portrait for P2; not the actual participantP2Theme 01
“It varies greatly depending on the level of the management, right?... the only data they see is really tactical information.”
Fictional human portrait for P3; not the actual participantP3Theme 01
“Once I submit the missing-part information, it becomes visible to the people who are responsible for material support… the information is coming directly from the person who is experiencing the problem.”
Fictional human portrait for P12; not the actual participantP12Theme 01
“If that information is incorrect, then the demand signals or the information you're getting out of the ERP is also incorrect.”
Fictional human portrait for P11; not the actual participantP11Theme 01
“We don't get data. We don't get data like no computer. So when I get my information, I get my information from my boss.”
Fictional human portrait for P8; not the actual participantP8Theme 01
“Once you use it a few times, it becomes part of your normal work process.”
Fictional human portrait for P12; not the actual participantP12Theme 06
“Sometimes I can look directly in the system, but sometimes I depend on someone explaining what the numbers actually mean.”
Fictional human portrait for P9; not the actual participantP9Theme 06
“If you do the prompts right and give them the instruction to AI, hey, give me detailed storytelling. It tells you exactly like, hey, your sales are high in this region, you can… expand more on this on this channel.”
Fictional human portrait for P3; not the actual participantP3Theme 06
“The interesting thing is what the context you need to give it, right? And the domain knowledge that you need to give it… it tells you a lot of the obvious.”
Fictional human portrait for P3; not the actual participantP3Theme 06
“I wouldn't automatically trust an AI-generated explanation without checking the original data.”
Fictional human portrait for P9; not the actual participantP9Theme 06
“I think AI can be useful for finding patterns or helping communicate information, but I would still want the original data validated before making an operational decision.”
Fictional human portrait for P10; not the actual participantP10Theme 06
“I could see AI being useful in the future for identifying patterns — for example, if the same part keeps being reported as missing or if certain shortages happen repeatedly.”
Fictional human portrait for P12; not the actual participantP12Theme 06
“SAP and Oracle are this gold standard. They're just the gold standard within the industry.”
Fictional human portrait for P2; not the actual participantP2Theme 06
“ERP works only when the information entered in the system is accurate.”
Fictional human portrait for P11; not the actual participantP11Theme 06