Case Interview Practice Log Template
Case practice log: six-criterion weighted rubric, case log, feedback notes, computed averages, moving average and SLOPE trend, weekly review
Cómo usar: Use it from your first practice case to choose what to practise next. Agree the rubric anchors with partners, log each case within 15 minutes and review the trend weekly. The main pitfall is counting cases instead of fixing the weakest criterion.
Vista previa
Case Practice Log: [Your name, recruiting season]
A log for consulting case practice: one row per case, a six-criterion scoring rubric, partner feedback, and computed progress (weighted score, moving average and trend) with Excel formulas. It is for MBA students preparing for case interviews who want to practise deliberately rather than count cases. Source basis: research on deliberate practice (Ericsson, Krampe and Tesch-Römer 1993) and on effective learning techniques (Dunlosky et al. 2013), written in our own words. Replace every [bracketed] value and every row marked Example. This is a preparation aid; no firm uses or endorses this rubric.
Document control
| Field | Value |
|---|---|
| Document ID | [CPL-2026] |
| Candidate | [Your name] |
| Season and target firms | [Season, Firm 1, Firm 2] |
| First interview date (T) | YYYY-MM-DD |
| Target weighted score before T | [4.0 average over the last three cases] |
| Reviewed by | [Case coach or second-year mentor] |
| Last updated | YYYY-MM-DD |
1. Why log deliberately
Ericsson, Krampe and Tesch-Römer (1993) found that expert performance grows with deliberate practice: tasks chosen to stretch a specific weakness, immediate feedback and repetition, rather than with the sheer amount of routine experience or play. Dunlosky et al. (2013) rate practice testing and distributed (spaced) practice as the most useful learning techniques across many studies. A case log puts both into a routine: every case is a test, the rubric gives specific feedback, and the review spaces the work on each weakness over several weeks.
The common failure is the opposite: doing many cases with friendly partners, feeling busy, and repeating the same mistakes. The log makes that visible.
2. Scoring rubric
Score each criterion from 1 to 5. Weights reflect how much each skill usually decides a case; adjust them for the formats your target firms use (for example, raise "Data" for interviewer-led cases with several exhibits).
| Criterion | Weight | 1 (weak) | 3 (acceptable) | 5 (strong) |
|---|---|---|---|---|
| Def: problem definition | 10% | Starts without restating the objective | Restates objective and asks basic questions | Pins down objective, measure, time frame and constraints |
| Str: structure | 20% | Generic list, overlaps | MECE but standard | Tailored, MECE, prioritised, client-ready |
| Hyp: hypothesis and prioritisation | 15% | No hypothesis | States one but does not update | States, tests and revises a hypothesis openly |
| Math: quantitative work | 20% | Errors, silent arithmetic | Correct with prompting | Set up aloud, correct, units and sanity check |
| Data: charts and exhibits | 15% | Misreads units or axes | Reads correctly, finds a fact | Finds the insight and links it to the hypothesis |
| Syn: synthesis and communication | 20% | Recaps the analysis | Gives an answer with some support | Answer first, numbers, risks, next steps, in 60 seconds |
The weighted score is where is the score on criterion and the weights sum to 1.
Spreadsheet layout used by every formula in this log. Column A holds the case number (1, 2, 3 and so on), column
B the case ID, columns C to H the scores Def, Str, Hyp, Math, Data and Syn, and column I the weighted score. The
weights sit in C3:H3 and the cases start in row 5. The weighted score for the first case is
=SUMPRODUCT(C5:H5,$C$3:$H$3), copied down.
3. Case log
| Case ID | Date | Partner | Case type and industry | Format | Def | Str | Hyp | Math | Data | Syn | Weighted | One focus for next case |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CPL-001 (Example) | 2026-08-25 | Amara O. | Profitability, retail | Candidate-led | 3 | 2 | 2 | 3 | 2 | 2 | 2.30 | Tailor the structure to the question |
| CPL-002 (Example) | 2026-08-27 | Jonas W. | Market entry, robotics | Interviewer-led | 3 | 3 | 2 | 2 | 3 | 2 | 2.45 | State a hypothesis after the structure |
| CPL-003 (Example) | 2026-08-30 | Priya S. | Operations, hospital | Candidate-led | 4 | 3 | 3 | 3 | 3 | 2 | 2.90 | Synthesis: answer first |
| CPL-004 (Example) | 2026-09-02 | Amara O. | Pricing, consumer goods | Interviewer-led | 4 | 3 | 3 | 4 | 3 | 3 | 3.30 | Read exhibit units aloud |
| CPL-005 (Example) | 2026-09-05 | Diego R. | M&A, industrial | Candidate-led | 4 | 4 | 3 | 3 | 3 | 3 | 3.30 | Percent math under time |
| CPL-006 (Example) | 2026-09-08 | Jonas W. | Growth strategy, software | Interviewer-led | 4 | 4 | 3 | 4 | 4 | 3 | 3.65 | Revise hypothesis when data disagree |
| CPL-007 (Example) | 2026-09-11 | Second-year coach | Cost reduction, airline | Candidate-led | 4 | 4 | 4 | 4 | 3 | 4 | 3.85 | Link each exhibit to the hypothesis |
| CPL-008 (Example) | 2026-09-14 | Second-year coach | New product, healthcare | Interviewer-led | 5 | 4 | 4 | 4 | 4 | 4 | 4.10 | Keep pace: finish in 30 minutes |
| [CPL-009] | YYYY-MM-DD | [ ] | [ ] | [ ] | [ ] | [ ] | [ ] | [ ] | [ ] | [ ] | [ ] | [ ] |
Feedback notes (one block per case)
| Case ID | What went well | What to change | Exact moment it went wrong | Drill assigned |
|---|---|---|---|---|
| CPL-003 (Example) | Clear patient-flow structure | Synthesis listed findings in order | Final minute: started with "So first we looked at" | Three 60-second syntheses a day for a week |
| [CPL-009] | [ ] | [ ] | [ ] | [ ] |
4. Progress (computed)
From the eight Example cases above (recomputed from the rubric weights):
| Measure | Value | Excel (layout in section 2, cases in rows 5 to 12) |
|---|---|---|
| Average of the first three cases | 2.55 | =AVERAGE(I5:I7) |
| Average of the last three cases | 3.87 | =AVERAGE(I10:I12) |
| Change | +1.32 | =AVERAGE(I10:I12)-AVERAGE(I5:I7) |
| Trend per case (least-squares slope) | +0.26 | =SLOPE(I5:I12,A5:A12) |
| Three-case moving average, latest | 3.87 | =AVERAGE(I10:I12) |
| Target met (4.0 over the last three cases)? | Not yet | =IF(AVERAGE(I10:I12)>=4,"Met","Not yet") |
Average score by criterion
| Criterion | All eight cases | Last three cases | Excel (all cases) |
|---|---|---|---|
| Def | 3.88 | 4.33 | =AVERAGE(C5:C12) |
| Str | 3.38 | 4.00 | =AVERAGE(D5:D12) |
| Hyp | 3.00 | 3.67 | =AVERAGE(E5:E12) |
| Math | 3.38 | 4.00 | =AVERAGE(F5:F12) |
| Data | 3.13 | 3.67 | =AVERAGE(G5:G12) |
| Syn | 2.88 | 3.67 | =AVERAGE(H5:H12) |
Reading: synthesis has improved but remains the weakest criterion over all cases, tied with hypothesis and data in the last three. With a 20% weight it is the best next focus. The weekly review would assign synthesis drills and an exhibit-heavy interviewer-led case.
Three-case moving averages for cases 3 to 8: 2.55, 2.88, 3.17, 3.42, 3.60, 3.87 (=AVERAGE(I5:I7) copied down).
5. Weekly review routine
- Update the progress table and the chart.
- Identify the weakest criterion over the last three cases, weighted by importance.
- Choose two drills for it and one case type that exercises it.
- Plan the partners: mix classmates, second-years and coaches so scores are calibrated.
- Space your practice: alternate case types (interleaving) rather than doing five profitability cases in a row.
6. Self-test
- Compute the weighted score for scores Def 4, Str 3, Hyp 4, Math 5, Data 3, Syn 4 with the weights in section 2.
- What Excel function returns the trend per case, and what are its arguments?
- Why choose one focus per case rather than working on everything?
- Your scores are high with friends and low with coaches. What does that suggest?
- Name two learning techniques Dunlosky et al. (2013) rated highly that this log uses.
Sources and further reading
- Ericsson, K. A., Krampe, R. T., and Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100(3), 363-406.
- Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., and Willingham, D. T. (2013). Improving students' learning with effective learning techniques. Psychological Science in the Public Interest, 14(1), 4-58.
- Related templates: mba/mba-case-interview-prep, mba/mba-market-sizing-drills.
Answer key
- 3.85:
=SUMPRODUCT({4,3,4,5,3,4},{0.1,0.2,0.15,0.2,0.15,0.2}). =SLOPE(known_y's, known_x's): the weighted scores as y and the case numbers as x.- Deliberate practice needs a specific goal and feedback on it; spreading attention across six criteria dilutes both.
- Scoring is not calibrated across partners; friends may score generously. Weight the trend with coach scores and agree the rubric anchors with every partner.
- Practice testing (each case is a test) and distributed practice (spaced work on each weakness), the two techniques Dunlosky et al. rated high utility. Interleaving case types, rated moderate utility, is a third the log uses.
Revision history
| Version | Date | Author | Change |
|---|---|---|---|
| 0.1 | YYYY-MM-DD | [Name] | First version from template |
| [0.2] | YYYY-MM-DD | [Name] | [Weights adjusted for interviewer-led formats] |
Standard and licence note
Based on research on deliberate practice and effective learning techniques. The rubric, example log and numbers are original and fictional; no firm uses or endorses this rubric, and this template is not affiliated with any firm or school. Template licence: MIT.
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