19.1 Why Exhibit Interpretation Is So Important
Consultants regularly work with charts, tables, financial data, survey results, and operating metrics. Case exhibits simulate that part of the job.
An interviewer may use an exhibit to test several skills at once:
- Attention to detail: Can you read the information correctly?
- Analytical ability: Can you identify patterns and relationships?
- Quantitative ability: Can you calculate useful metrics?
- Prioritization: Can you focus on the most important data?
- Synthesis: Can you explain what the exhibit means for the client?
Core principle: Reading the chart is only the first step. The real value comes from interpreting it.
19.2 Orienting Yourself Before Analyzing
When you receive an exhibit, do not immediately start discussing individual numbers. First understand what you are looking at.
Take a short pause and determine:
- What is being measured?
- What period does the data cover?
- What categories are being compared?
- What units are being used?
Good habit: Spend a few seconds orienting yourself before searching for insights. This reduces the risk of misreading the exhibit.
19.3 Reading Titles, Axes, Units, and Footnotes
Many exhibit mistakes come from ignoring basic labels.
Read the title, axis labels, units, legend, and footnotes before interpreting the chart. A figure labeled “$ millions” is very different from one labeled “$ billions,” and a chart showing market share is different from one showing absolute sales.
Footnotes may define exclusions, time periods, averages, or data limitations.
Rule: Never begin calculating until you are certain what the numbers represent.
19.4 Understanding What the Exhibit Is Designed to Answer
An exhibit usually appears for a reason. Connect it to the current question in the case.
If you are investigating why profits declined and the interviewer gives you a chart of revenue by product, the exhibit may help determine whether certain products are driving the problem.
Useful question: “What question should this exhibit help me answer?”
This prevents you from discussing interesting but irrelevant details.
19.5 Identifying the Headline
The headline is the single most important message from the exhibit.
For example, instead of saying, “Product A grew 5%, Product B fell 10%, and Product C fell 30%,” you might say:
Headline: “The overall decline appears to be driven primarily by Product C, which fell much more sharply than the rest of the portfolio.”
A strong headline summarizes the pattern rather than reading the exhibit aloud.
19.6 Comparing Categories
Many exhibits require comparisons across products, customers, regions, competitors, or time periods.
Look for:
- Largest versus smallest: Which categories dominate?
- Best versus worst: Where is performance strongest or weakest?
- Relative differences: How much larger or smaller is one category than another?
- Mix: Which categories account for most of the total?
Focus: Compare categories in ways that help explain the business problem.
19.7 Identifying Trends
Trend charts show how something changes over time. Look for direction, speed, and changes in the pattern.
Ask:
- Is the metric increasing, decreasing, or stable?
- Is the change accelerating or slowing?
- Did anything shift suddenly?
- Do multiple series move together or differently?
Example: A gradual revenue decline may suggest a structural problem, while a sudden drop might point toward a specific event.
19.8 Identifying Outliers
Outliers are data points that differ significantly from the rest. They can reveal important problems or opportunities.
If most regions have stable sales but one region is down 40%, investigate what is different about that region.
Important: An outlier is not automatically the answer. It is a signal that deserves explanation.
19.9 Calculating Changes and Ratios
Sometimes the insight is not directly shown and requires a calculation.
Common calculations include:
- Absolute change: New value − old value.
- Percentage change: Change ÷ old value.
- Share: Category ÷ total.
- Ratio: One quantity compared with another.
Perform calculations only when they help answer the question. Do not calculate every possible metric simply because the data is available.
19.10 Connecting Data to Your Hypothesis
Use exhibits to test your current view of the case.
If your hypothesis is that falling profit is caused by declining volume, a chart showing stable volume would weaken that hypothesis and redirect your attention toward price, mix, or costs.
Good behavior: Explicitly state whether the exhibit supports, weakens, or changes your current hypothesis.
19.11 Distinguishing Observations from Insights
An observation describes what the data shows. An insight explains why it matters.
Observation: “Customer retention declined from 90% to 80%.”
Insight: “The decline in retention appears large enough to explain much of the revenue shortfall, so customer churn should become a priority for further analysis.”
Interviewers care much more about the second statement.
19.12 Moving from “What” to “So What”
After every major finding, ask, “So what?”
If one product has the highest growth, what does that mean for the client? Should investment shift toward it? Does it have attractive margins? Is it large enough to matter?
Strong progression: Data → Pattern → Interpretation → Business implication.
This is what turns exhibit reading into consulting-style analysis.
19.13 Connecting Multiple Exhibits
Later in a case, you may need to combine evidence from several exhibits.
One chart may show that sales declined in a certain customer segment, while another shows that the same segment experienced a large price increase. Together, the exhibits may suggest price sensitivity as a possible cause.
Synthesis: Do not treat each exhibit as an isolated exercise. Build a cumulative understanding of the business problem.
19.14 Common Exhibit-Reading Mistakes
Common mistakes include:
- Ignoring units: Misreading millions as billions or percentages as absolute values.
- Reading every number: Describing the exhibit instead of identifying its message.
- Missing the question: Discussing information unrelated to the current objective.
- Overcalculating: Performing unnecessary arithmetic.
- Confusing correlation with causation: Assuming that two trends moving together proves one caused the other.
- Stopping at observation: Identifying a pattern without explaining its implication.
Final principle: Read exhibits with a purpose. Orient yourself, identify the headline, perform only the calculations you need, and connect every important finding back to the client’s objective. The strongest exhibit analysis does not merely explain what the data shows—it explains what the client should learn from it.
