DDBA 8151 Week 4 Cause Map Example

Four Candidate Causes, Four Symptoms and the Evidence on Every Arrow: A Cause Map Joining Records and Interviews on Escalated Contractor Credit Decisions at a Building Supply Company

Student Name

Walden University

DDBA 8151: Organizational Leadership

Instructor Name

Month Day, Year

Four Candidate Causes, Four Symptoms and the Evidence on Every Arrow: A Cause Map Joining Records and Interviews on Escalated Contractor Credit Decisions at a Building Supply Company

What the Map Joins

Three weeks of work have produced three piles: symptoms observed directly, a records review and ten interviews. This cause map joins them. Symptoms sit on the right, candidate causes on the left, and each arrow from a cause to a symptom carries a label for the evidence behind it: records, interviews, both or none. Links with no evidence are drawn but marked, so a reader can see where the explanation is thin. Yin (2018) recommends pattern matching in case research, comparing the pattern each candidate explanation predicts with the pattern observed, and laying the evidence out as a map makes that comparison visible.

The Map

Table 1

Cause Map: Candidate Causes, Symptoms and Evidence on Each Link

Evidence labels: Records = credit exception log, authority matrix, minutes; Interviews = ten interviews in Week 3; Both = each source supports the link; None = no evidence found.

Cause A: Unclear Authority

If the restructuring left managers unsure whether their $25,000 limit still applied, they would send exceptions up and decisions would slow while the region worked through them. That is what the records show, and every manager interviewed was unsure what limit now applied. Cause A also predicts that only credit decisions would change, since the restructuring touched credit policy alone, and the exception log confirms that inventory and staffing approvals did not shift. Two links to symptoms are supported by both sources.

Cause B: The Public Discussion

If presenting one manager's audit finding in front of peers made approving exceptions feel personally risky, managers would avoid approving them. The timing fits, since local approvals dropped in the very month of that meeting. All four managers named the meeting unprompted. Cause B also predicts a narrow effect on credit decisions, which fits the records.

Cause C: The Regional Office as an Easier Path

Once a regional credit office existed, sending a request there may simply have become easier than deciding locally. The regional credit manager's comment that requests now arrive "with no recommendation attached" supports this. But this cause alone does not explain why the shift was so sudden in April rather than gradual from March, when the office opened. It is better seen as an enabling condition: it gave managers somewhere to send decisions once they wanted to.

Cause D: Loss of Ownership

The presented explanation predicts that managers would withdraw from decisions generally. The records contradict this: staffing, delivery and inventory decisions continued at yard level without change. A general loss of ownership that affects only one type of decision, beginning in one month, is hard to reconcile with the evidence. Platt (1964) argued that progress comes from setting out several hypotheses and devising tests that exclude some of them; the narrowness of the change is the test that weakens cause D.

Causes Working Together

Causes A and B are not rivals; they combine. Unclear authority made it possible to argue that credit decisions now belonged to the region. The public discussion gave managers a strong reason to make that argument. Either alone might have produced some escalation; together they explain both the size and the timing of the shift. Miles et al. (2014) describe causal networks in which several conditions jointly produce an outcome, and the map shows that structure.

Thin Links

Two links have no evidence. Nothing ties the sales representatives' departures to the regional office's existence or to a loss of ownership. The departures may have other causes entirely; the exit summaries cover only some of them. The map leaves those arrows drawn but unsupported rather than removing them, so the diagnosis next week does not lean on them.

What the Map Supports

The map supports a combined explanation, unclear authority plus a visible penalty for error, with the regional office as an enabling condition, and it weakens the presented explanation. It does not yet test whether reissuing authority or changing how audit findings are discussed would reverse the shift; that is the question for the pilot.

References

Miles, M. B., Huberman, A. M., & Saldana, J. (2014). Qualitative data analysis: A methods sourcebook (3rd ed.). SAGE Publications.

Platt, J. R. (1964). Strong inference. Science, 146(3642), 347-353. https://doi.org/10.1126/science.146.3642.347

Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.