Six interlocking gears of light above a steel table, a human hand and a robotic hand turning one together

Discussion · Contribution · Future work

From information to shared meaning

The six themes tell a conditional story: information becomes useful through access, explanation, dialogue, audience fit, and honest disclosure—not technology alone.

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

Supplementary interpretation · not a tested model

This discussion connects the reported findings with scholarship. It adds no participants, measurements, or field observations. The dissertation’s goal is addressed through a contextual understanding of perceptions; causal effectiveness and sustained engagement remain questions for further study.

Six streams of cyan light braiding into one luminous rope held in silver rings
Connecting interpretations without claiming a tested causal pathway.AI-generated illustration · Not research evidence or a real study site

Six themes · One interpretive account

Conditions for meaningful operational data

These are interacting conditions, not a chronological sequence or a validated causal pathway. Technology supports every condition; inaccurate data or excluded voices can undermine any of them.

  1. THEME 01 · REACH

    Can the employee receive and question the information?

    Channels, permissions, and a return path make information available for shared interpretation.

    P8 describes no direct system access; P12 describes reporting a problem at its point of occurrence.

    Availability alone does not establish understanding.

  2. THEME 02 · EXPLAIN

    What changed, and why does it matter?

    Context connects an operational figure to a consequence and a possible response.

    P10 describes starting point, change, impact, and response; P4 describes reporting largely without storytelling.

    A convincing story may still rest on incorrect figures.

  3. THEME 03 · QUESTION

    Whose interpretation is missing?

    Discussion can bring frontline knowledge and competing explanations into a decision.

    P3 describes debate that surfaces unexpected insights; P11 maintains parallel records when shared information is unreliable.

    Attendance at a meeting does not demonstrate safe disagreement.

  4. THEME 04 · CLARIFY

    Does this representation fit this reader?

    Visual form and accompanying explanation should serve the task, not the sophistication of the software.

    P8 rejects graphs while P9 describes useful dashboards; the contrast must remain visible.

    The contrast does not isolate access, literacy, or design as a causal explanation.

  5. THEME 05 · JUDGE

    Is this relevant, accurate, and honest?

    Employees need both a reason to attend to the message and grounds for judging its credibility.

    P5 connects attention to work relevance; P4 describes deliberate omissions; P8 emphasizes honesty and accountability.

    Trust, attention, and sustained employee engagement are distinct outcomes.

  6. THEME 06 · ENABLE

    Can the technology support accountable action?

    Systems and AI can assist communication while humans retain responsibility for source verification and operational decisions.

    P9 and P10 require checking original data before relying on AI explanations.

    Technology is a cross-cutting condition, not a final causal step or an evaluated intervention.

Original findings and quotations

Conceptual precision

Related concepts are not the same outcome

Data storytelling

Context, change, consequence, and response organized around operational figures.

Not merely an attractive chart or persuasive presentation.

Understanding

A reader’s interpretation of what happened and what it means for a task.

Self-reported clarity is not an independently scored comprehension result.

Trust

Confidence in an account, its source, or the people communicating it.

Trust in data, leadership, and an AI explanation should not be treated as interchangeable.

Employee engagement

The dissertation captures accounts of relevance, attention, participation, and usefulness at work.

Those accounts do not establish a validated engagement score or sustained change over time.

Contribution to the study’s goal

What the research adds

RQ1 · A conditional account of engagement

Read together, Themes 1, 2, 3, and 5 suggest that participants perceive storytelling as useful when information reaches their role, explains consequences, and permits response. The contribution is a contextual account of perceived engagement—not an estimate of how much engagement increases.

THEMES 01 · 02 · 03 · 05

RQ2 · Fit and transparency, rather than visual novelty

Themes 2, 3, 4, and 5 suggest that interpretation depends on explanation, audience fit, discussion, and disclosure of limitations. P8 and P9 challenge a universal claim that dashboards help frontline employees. The contrast identifies questions for further study, not a proven cause of the difference.

THEMES 02 · 03 · 04 · 05

Theoretical meaning · Sensemaking in everyday work

Weick’s lens helps interpret how employees connect ambiguous figures with operational experience and social discussion. P10’s narrative structure, P3’s debate, and P12’s response loop illustrate possible meaning-making practices. Applying this lens is an interpretation; it does not independently test Sensemaking Theory.

THEMES 01 · 02 · 03

Alternative explanations

Five translucent paths of light branching from one glowing point in a dark hall
Workplace context may shape how information is received.AI-generated illustration · Not research evidence or a real study site

What else could explain these accounts?

Leadership and organizational culture

An explanatory leader might also create trust and participation independently of storytelling. P4’s contrasting experience makes leadership a competing explanation, not background noise.

Access, task fit, and prior experience

P8 and P9 differ in reported access and experience. Their accounts cannot determine whether design, training, task relevance, or another contextual factor explains their different reactions.

Data quality and visible follow-through

Accurate inputs or prompt responses may explain perceived usefulness even without a narrative. P11’s parallel records and P12’s response loop make these alternatives important.

Recruitment and retrospective self-report

Professional-network recruitment and recalled experiences may favor particular perspectives. Cross-sector breadth is informative but limits the specificity of supply-chain conclusions.

Proposed practices · Not tested outcomes

Implications for operations and leadership

01 · Structured Data Communication Creates Shared Understanding

Provide the same operational context through accessible channels and record unanswered questions.

Review question: Look for roles that still cannot receive information or report an issue.

02 · Data Storytelling Facilitates Meaning-Making

Use a starting point → change → impact → response structure beside the original figures.

Review question: Ask readers to explain the implication in their own words, including uncertainty.

03 · Collaborative Sensemaking Enhances Understanding

Invite an alternative explanation before assigning action; record who will respond.

Review question: Check whether objections receive consideration rather than only counting meeting attendance.

04 · Narrative Visualization Enhances Interpretation

Compare visual and narrated alternatives with the actual intended audience.

Review question: Observe whether the reader identifies the issue and an appropriate next action.

05 · Effective Data Communication Builds Trust and Employee Engagement

Disclose missing records, exclusions, uncertainty, and role-specific relevance.

Review question: Check whether trust rests on accuracy and transparency rather than persuasion.

06 · Technology Enables Data Storytelling and Data Communication

Label AI-generated text, retain its source figures, and require human review before operational use.

Review question: Record unsupported statements, corrections, and access barriers.

A holographic dashboard held inside a precision test rig of silver measuring arms
Considering access and audience fit across environments in a future evaluation.AI-generated illustration · Not research evidence or a real study site

GENIOS · Proposed future study · no outcomes collected

A defensible next study

Does a contextualized operational narrative improve task understanding compared with the same figures alone, and under what conditions?

Begin with a committee-approved pilot using de-identified or synthetic operational cases. Compare a figures-only version with a contextualized narrative using the same source facts. Counterbalance presentation order and use matched cases to reduce recall effects. Include frontline and manager perspectives, accessible non-chart versions, and records of prior task familiarity.

Open the GENIOS demo

Illustrative demo, not a validated research instrument or evidence of improved engagement.

Task understanding
Score factual interpretation and proposed action against an expert-reviewed rubric; record incorrect inferences as well as correct answers.
Trust calibration
Include an explicitly incomplete case and ask readers to identify limitations and verification needs. Confidence alone is not successful trust calibration.
Engagement over time
If sustained engagement is studied, choose a validated measure with committee guidance, check permission and scoring requirements, and collect repeated observations. Do not substitute clicks or immediate satisfaction for engagement.
Equity and accessibility
Review differences by role, access, task familiarity, and accessibility needs without treating illustrative portraits as demographic data.
AI fidelity
If GENIOS generates explanations, audit every factual claim against its inputs and record unsupported claims and human corrections. Evaluate generation separately from presentation.

Ethics and interpretation safeguards

Confirm ethics approval and consent before recruitment; avoid collecting confidential employer records; protect identities and voluntary participation. Predefine outcomes and analysis, justify sample size for the chosen design, and report null, adverse, and divergent results. A small pilot informs feasibility—not universal effectiveness.

A translucent manuscript under construction inside silver scaffolding
Source checking and transparent manuscript review.AI-generated illustration · Not research evidence or a real study site

Manuscript review · Verification still required

What a complete dissertation still needs

These are review requirements, not claims that work is missing or already completed. This website does not modify the uploaded dissertation, verify every research record, or substitute for committee approval.

Specific flags found in the supplied manuscript

These observations refer to the supplied version, not later revisions. The underlying archived documents and demographic records have not been independently verified here.

Documentary source verification

The Retrieval and Preservation note and Table 4.4 discussion retain a SOURCE VERIFICATION REQUIRED note: the archived-document comparison was AI-assisted, and an independent manual read-through remains to be completed.

Verify each coded excerpt against the actual archived D1–D3 documents and carry any corrections into the tables and discussion.

Demographic information

The participant description and text preceding Table 4.1 retain INFORMATION NEEDED placeholders for demographic questionnaire data; the text also says the questionnaire was administered.

Reconcile those statements using actual records. Complete the summary only where data exist, or explicitly report unavailable information; fictional portraits cannot fill the gap.

Shop-floor sample description

Later sections describe P8, P9, and P12 as the three shop-floor participants, while some earlier wording still refers to two. This subgroup is distinct from the broader frontline role category.

Update stale manuscript references consistently, retain the contrary P8 account, and do not use the subgroup count as proof of saturation.

Methodological context: Malterud et al. on information power and Braun & Clarke on analytic coherence support review questions, not automatic validation of the study.

01Question–evidence alignment

Map each RQ to codes, themes, quotations, contrary cases, and the conclusions it supports. Keep Theme 6 supplementary and distinguish AI awareness from direct use.

02Analytic coherence

Explain what deductive and inductive work meant within a framework where no new codes were added. Do not retrospectively claim a different form of thematic analysis or add unperformed reliability procedures.

03Sample sufficiency and scope

Justify the twelve interviews using study aim, specificity, dialogue quality, theory, and analysis; reconcile the supply-chain focus with the cross-sector sample. Do not claim saturation solely from sample size.

04Document provenance

Check the exact editions, retrieval dates, archive records, coding excerpts, and page references for NCDOT documents. Distinguish public organizational context from corroboration of participants’ own workplaces.

05Ethics and reflexivity

Check the actual approval, consent, anonymization, retention, recruitment, and researcher-position records. Describe the influence of professional experience and relationships without inventing safeguards.

06Source and quotation audit

Verify every quotation against its transcript and every citation against the original publication. Reconcile in-text citations with the dissertation bibliography and check APA and university requirements.

07Discussion and conclusion

Separate reported perceptions, literature-supported interpretation, proposed practices, and future evaluation. Address rival explanations, transferability, limitations, and the contribution to both RQs.

08Committee submission

Confirm the current manuscript date, appendices, tables, formatting, and committee feedback in the actual dissertation document. These website additions do not certify document completeness or acceptance.