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
Effective Data Communication Builds Trust and Employee Engagement
The clearest bridge between communication practice and employee engagement. The Engagement code converged strongly around relevance as the primary engagement trigger; the Transparency code was the single most frequently cited trust-builder in the dataset.
Research question
RQ1 and RQ2
Strength of evidence
Strong
Codes
Key findings
- P5: “employees engage more often when data is directly connected to their work and when leaders explain why the information matters.”
- P2’s first-person articulation of relevance: “I want something that makes an impact on me or to me, to my group, to my team.”
- P9: “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.”
- P10 on audience fit: “If I show somebody 15 different KPIs and don’t explain which ones matter, I’ve probably created more confusion than understanding.”
- P3’s transparency technique — name and exclude known-imperfect data rather than conceal it: “the story doesn’t change if you take out 2% of the data, right? The story stays the same.”
- The most serious documented trust breach: P4 described a colleague who “deliberately omitted certain information” from shared data.
Divergence, preserved — not smoothed
P8 centered trust on accountability and honesty rather than relevance: “trust is earned. It’s not given,” citing deadline communication — “they’ll tell you, oh, the deadline is two months from now, but the deadline is really six months from now… they spin you.”
Added scholarly interpretation
Why this theme matters
Engagement and trust are connected but distinct. Relevance helps people see why data concerns their work; honest disclosure helps them judge whether the account deserves confidence.
Proposed design implication · not tested
Name uncertainties, missing records, and exclusions beside the conclusion. Explain which metrics matter for each role and avoid using narrative to conceal inconvenient evidence.
Boundary of the claim
These are participant perceptions, not engagement-scale scores or a causal estimate. Transparency should not be equated with selective persuasion; job engagement and organization engagement should also be distinguished.
In their words
“Employees trust the information more when there is a connection between what the system says and what we actually experience.”— P12
“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.”— P3
“The story doesn't change if you take out 2% of the data, right? The story stays the same.”
“Employees engage more often when data is directly connected to their work and when leaders explain why the information matters.”— P5
“Transparency, context… context and consistency are what build trust for me.”
“If there's a conflicting information going around, that just defeats the purpose of the data coming out of the system.”— P11
“Trust is earned. It's not given.”— P8
“They'll tell you, oh, the deadline is two months from now, but the deadline is really six months from now… they spin you.”
“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.”— P2
“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.”— P9
“If I show somebody 15 different KPIs and don't explain which ones matter, I've probably created more confusion than understanding.”— P10
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.