Chapter 38 — Dissertation II: findings

Lesson map

Lesson 38 published. Map, example, EX112.

flowchart TD
  N0["Learning outcomes"]
  N1["38.1 Results"]
  N2["38.2 Long delays"]
  N3["38.3 Rival explanations"]
  N4["38.4 Cautious conclusions"]
  N0 --> N1 --> N2 --> N3 --> N4
  N4 --> EX["Worked example"]
  EX --> Q["Exercise EX112"]

Logical drawing

flowchart LR
  N0["Learning outcomes"]
  N1["38.1 Results"]
  N2["38.2 Long delays"]
  N3["38.3 Rival explanations"]
  N4["38.4 Cautious conclusions"]
  N0 --> N1 --> N2 --> N3 --> N4 --> Q["EX112"]

[Learning outcomes]
    |
    v
[38.1 Results]
    |
    v
[38.2 Long delays]
    |
    v
[38.3 Rival explanations]
    |
    v
[38.4 Cautious conclusions]
    |
    v
[Worked example] --> [Exercise EX112]

Learning outcomes

You will (1) analyse data according to plan; (2) check rival explanations; (3) report findings with appropriate caution.

38.1 Results

Aisha receives anonymised synthetic records for leavers in the year before and after the automated process. Before, the median time to disable was five days, and a quarter of accounts were disabled within one day. After, the median was zero days, with most accounts disabled on the last working day. A few accounts in the after period still took longer, which she examines individually. She presents the results in a table showing medians, the share disabled within one day and the number of leavers in each year, alongside a simple chart of removal times.

38.2 Long delays

Aisha investigates the after-period delays. Most involve temporary staff whose end dates were not entered in the human resources system, so the automated process did not trigger. This is a gap in the process, not a failure of automation. She recommends that temporary contracts always include an end date in the system. Dr. Carrow praises her for examining exceptions rather than reporting only the median. She counts the temporary staff cases and lists them by month, which shows they were spread across the year rather than concentrated in one busy period.

38.3 Rival explanations

Aisha checks rivals. Leaver numbers were similar in both years. A new IT staff member joined during the after period, which could have improved manual removals too. She examines the removal logs and finds that almost all after-period removals were performed automatically, not manually, which makes the staffing explanation less likely. She reports this check and its limits openly. She also checks whether the type of leavers changed between years, for example more temporary staff in one year, and finds the mix broadly similar. She reports each check in a short table so examiners can see what was examined and what was found.

38.4 Cautious conclusions

Aisha concludes that, at Ashfield, introducing the automated leaver process was followed by much faster account removal, with remaining delays concentrated among temporary staff. She does not claim the result applies to all organisations. She notes that one organisation over two years is a small evidence base. Dr. Carrow notes that cautious, well-supported conclusions are worth more than bold claims. She writes the conclusion in a single paragraph and checks that every sentence is supported by a result or a check reported earlier. She removes one sentence that suggested the process would work equally well in larger organisations.

Worked example

Aisha finds median removal fell from five days to zero, traces remaining delays to missing temporary-staff end dates, checks rival explanations using logs and concludes cautiously.

Synthetic case. Results are synthetic.

Errors and limits

Reporting only the median hides exceptions that reveal process gaps.

Exercises

• EX112 — Median before. What was the median removal time before?
  Show marking criteria

  Rubric: 3 = five days;; 2 = partly correct;; 1 = wrong;; 0 = none.
• EX113 — Delay cause. What caused most after-period delays?
  Show marking criteria

  Rubric: 3 = missing end dates for temporary staff;; 2 = partly correct;; 1 = vague;; 0 = none.
• EX114 — Staffing rival. How is the staffing rival weakened?
  Show marking criteria

  Rubric: 3 = removals were performed automatically;; 2 = partly correct;; 1 = vague;; 0 = none.