Chapter Four · Findings
The thematic framework
Six themes, thirty codes, and participants’ own words — as reported in Chapter Four.
AI-generated conceptual illustration · Not research evidence or a real study site
Collaborative Sensemaking Enhances Understanding
Understanding was described as produced between people rather than by an individual reading a report alone. All twelve participants described the Decisions and Leadership codes; nine described Knowledge Sharing; eight provided direct evidence for Training.
Research question
RQ1 and RQ2 (supporting)
Strength of evidence
Strong (Training: Emerging)
Codes
Key findings
- Group, synchronous review was repeatedly credited with surfacing insight individual review would not — P3: “people start to go, oh, wow, I didn’t realize this… And then the debate sparks, right?”
- P10: “the ERP system provides the data, but the decision still requires human interpretation.”
- P11 described distrust pushing decisions away from collaboration: “I had to maintain my own separate thing… there’s no set one rule how everybody is following.”
- P12’s report-and-response loop sustained system use: “when they see that the warehouse responds and the material arrives, they understand that reporting the information actually helps the operation.”
- P4 offered the dataset’s most severe cautionary account: an executive announced a forecast of a 25% growth slowdown that triggered layoffs and was later shown to be incorrect — “some executives, they don’t have the full stories.”
Added scholarly interpretation
Why this theme matters
Interpretation is social work. People can surface missing context and competing explanations together; leadership shapes whether a disagreement becomes learning or remains hidden.
Proposed design implication · not tested
Include a question-and-challenge moment in data reviews, capture alternative explanations, and make ownership of the next decision explicit.
Boundary of the claim
A meeting is not evidence of collaboration or psychological safety. P4’s reported incorrect forecast and P11’s parallel records suggest risks of authority and unreliable upstream information.
In their words
“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?”— P3
“Some systems are easier to understand after somebody actually walks you through them.”— P9
“The ERP system provides the data, but the decision still requires human interpretation.”— P10
“When they see that the warehouse responds and the material arrives, they understand that reporting the information actually helps the operation.”— P12
“If employees report shortages and nothing happens, eventually they may stop using the process.”
“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.”— P11
“Some executives, they don't have the full stories. They just see someone prepared that number and they started announcing it.”— P4
Answers to the research questions
How do frontline employees and managers perceive the role of data storytelling in enhancing employee engagement within supply chain and operational environments?
Participants perceived data storytelling — the addition of context, cause, and consequence to raw operational figures — as associated with increased engagement, while raw or unexplained data was associated with confusion and, in one severe case, costly organizational error. The perception was strongly but not universally shared: P4 described an organizational culture in which storytelling was largely absent.
Drawn from themes 02, 05, 01, 03
How does narrative visualization influence employees’ trust, understanding, and interpretation of operational data?
Narrative visualization’s influence depended on the fit between visual form and data structure, the presence of accompanying explanation, and audience-specific tailoring. Transparency about data limitations was the most consistent trust-building practice; its absence — particularly deliberate omission — was the most serious threat to trust. P8’s categorical rejection of visual formats, set against P9’s affirmatively positive account, showed that fit, not frontline status, is what the evidence differentiates.
Drawn from themes 04, 02, 03, 05
Strength of evidence reflects the consistency, richness, and specificity of participant evidence across the twelve interviews, not participant count alone. Findings are participant perceptions, not statistically generalizable or causal claims.