A finished MGT-420 Topic 7 structural root cause diagnosis example, tracing a persistent behavioral problem to the measure and rules that produce it and testing the diagnosis against variation in the data. Searches like "mgt 420 topic 7 assignment example", "mgt420 topic 7 sample" and "mgt-420 topic 7 example" land here.
What a finished MGT-420 Topic 7 structural root cause diagnosis looks like
The finished diagnosis starts from a pattern and refuses the easy explanation. Technicians at a composite help desk close tickets that customers promptly reopen, and supervisors describe the team as sloppy. The example lists candidate causes across the organization's systems and gathers evidence for each. The decisive finding is that performance is judged on tickets closed per hour and a reopened ticket counts as new work, so the scorecard pays twice for a rushed fix, an instance of the pattern Kerr described as rewarding one behavior while hoping for another. The example strengthens the diagnosis with variation: reopen rates climb in the last days of each month, when targets bite, and stay low on a team measured differently. Contributing causes are ranked beneath the root.
How an MGT-420 Topic 7 example is structured
Evidence accumulates across six sections until one cause stands out. The first defines the problem in measurable terms, including when it began, where it is concentrated and what it costs. The second records the explanations currently offered, most of which describe the people involved. The third lists candidate structural causes by system, covering measurement, rewards, workload, escalation rules and information flow, with a mechanism stated for each. The fourth tests the candidates against the pattern in the data, asking which cause predicts the timing and the teams where the behavior is strongest and weakest. The fifth separates the root cause from contributing conditions and explains the ranking. The sixth states the diagnosis in one paragraph and names the prediction that would confirm it if the condition were changed.
The problem defined by its pattern
Timing, location and cost are measured first, because a behavior's distribution across months and teams is the evidence that later separates the causes.
Current explanations recorded then tested
What supervisors already say is written down fairly, and most of it turns out to describe the technicians rather than their working conditions.
Candidate causes listed by system
Measurement, rewards, workload, escalation rules and information flow each receive a stated mechanism linking them to the reopened tickets.
Variation used as the deciding evidence
The cause that predicts when and where the behavior peaks, such as month-end spikes under the closure target, earns the root position.
Root separated from contributing conditions
Understaffing and slow escalation are ranked as contributors, since they worsen the pattern without explaining why it follows the scorecard.
Where marks go in MGT-420 Topic 7
The heaviest deduction lands on diagnoses that conclude the staff need retraining or closer supervision, since that treats the behavior as the cause and leaves the scorecard paying for it. A candidate cause offered with no mechanism is untestable, and a list of every system in the organization is no more useful than a list of none. Ignoring variation in the data wastes the strongest evidence a diagnosis can offer, because a structural cause should predict where and when the behavior peaks. Treating every contributing condition as equally important produces a diagnosis with no root. Blaming the measure without showing how it rewards the behavior asserts the finding rather than establishing it. Diagnoses with no confirming prediction offer a reader no way to know whether they are right.
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MGT-420 Topic 7 questions, answered
What makes a cause structural rather than personal?
It sits in the arrangements rather than in the individuals, and it would affect anyone placed in the same position. Performance measures, reward formulas, workload, reporting lines and procedural rules all qualify. The test is whether replacing the people would change the behavior. If a new technician would face the same scorecard and rush the same fixes, the cause is structural.
How can data variation support a diagnosis?
A genuine cause should predict where and when the behavior is strongest. If rushed fixes rise when targets tighten and fall on a team measured differently, the measure is implicated. If the behavior is spread evenly regardless of conditions, the proposed cause is weaker. Using variation turns a plausible story into an argument a reader can check against the numbers.
What is rewarding A while hoping for B?
The pattern Steven Kerr described, in which an organization says it wants one behavior while its reward system pays for another. A help desk that wants lasting fixes but pays for closures is a clear instance. The idea is useful in diagnosis because it directs attention to what the measures actually reward, which is frequently the opposite of what the mission statement says.