Booz Allen Case Interview Examples: Government, Defense, Health and Cyber Cases Solved (2026)

Booz Allen's interview leans on behavioral and technical questions, and a case, where one appears, is a short conversation about a government, defense, health or technology problem. Booz Allen publishes no case format, and candidates report a case in only some final rounds, so the useful preparation is practice on the kind of problem its clients have. This page gives you seven worked practice cases in that territory, with the math done step by step.

Booz Allen practice cases at a glance

How a Booz Allen case works: when one appears, candidates report a candidate-led conversation of about 30 minutes on a public sector problem, in a final round where the other interviews are behavioral. Booz Allen does not publish the format, so every fact below is labelled by source.

• Official, process: five steps, with a technical assessment for some roles and interviews tailored to the role (Booz Allen candidate resources). No case is mentioned.
• Official, what to prepare: three stories about your greatest challenge, using technology to improve a process, and choosing a tool.
• Reported, final round: three back-to-back 30 minute interviews, two behavioral and the third possibly a case, with some candidates getting no case at all (Hacking the Case Interview, updated March 19, 2026; CaseBasix).
• Reported, technical roles: a technical screen on frameworks such as NIST and the Risk Management Framework, or on SQL and Python, for cyber, analytics and engineering roles (Hacking the Case Interview).
• Reported, case topics: federal agency efficiency, defense logistics, health policy and cyber strategy, with some quantitative work such as cost savings and ROI.

Start free now: National Health System is an interviewer-led public sector operations case adapted from the INSEAD casebook: the Sydney Department of Health has found that people over 60 are unhappy with the time and quality of the hospital services they receive. It has 8 questions, 1 with math, 1 exhibit, and fewer than 10 completed runs so far, so no median time yet. An AI interviewer runs it out loud, shows each exhibit when you reach it and scores the debrief. Your first full case is free when you create an account. A free account also gets one full run in every simulator inside the app: one complete run of each of our four McKinsey Solve practice formats (Red Rock, Sea Wolf, SFL Classic and SFL Island), a full Casey-style case, a full CCA-style diagnostic and a complete Bain SOVA-style diagnostic.

Case (style, industry)	Quant difficulty	Qualitative difficulty	The math you run	Median time
National Health System (Independent, health services). 8 (1 with math), 1 exhibit.health servicesQuant difficulty easyQualitative difficulty mediumFewer than 10 runsTry free	easy	medium	Older share, visits, specialists needed	Fewer than 10 runsFewer than 10 runs	Try free
Voter Turnout in Philadelphia (McKinsey, public sector). 8 (2 with math), 2 exhibits.public sectorQuant difficulty easyQualitative difficulty hardFewer than 10 runsTry free	easy	hard	Registration and turnout percent change, exhibit read	Fewer than 10 runsFewer than 10 runs	Try free
Dark Sky (McKinsey, aerospace and defense). 8 (3 with math), 3 exhibits.aerospace and defenseQuant difficulty hardQualitative difficulty mediumFewer than 10 runsTry free	hard	medium	Unit growth, revenue, cannibalization	Fewer than 10 runsFewer than 10 runs	Try free
S.A. Shipping (Independent, package delivery). 8 (3 with math), 2 exhibits.package deliveryQuant difficulty mediumQualitative difficulty mediumFewer than 10 runsTry free	medium	medium	Packages per driver, fleet size, daily cost	Fewer than 10 runsFewer than 10 runs	Try free

National Health System is adapted from the INSEAD casebook, Voter Turnout from the Wharton casebook, Dark Sky from another consulting club casebook and S.A. Shipping from the McCombs casebook; none is Booz Allen's own material, and the library has no case in its style, so these are matched by case type: a government program, a defense maker and a logistics operation. More are in the case library, 92 cases in all. Every debrief scores seven categories: structure (25% of the score), quantitative analysis (20%), business judgment (15%), and problem understanding, exhibit reading, communication and synthesis (10% each), with feedback on every question. Median times come from completed runs between June 25 and September 22, 2026, and count runs, not people.

What does a Booz Allen case interview look like?

Booz Allen does not publish a case format, and candidates report at most one case of about 30 minutes in a final round that is mostly behavioral. The firm's candidate resources page says interviews are tailored to the role and typically combine technical screens with individual or panel interviews, and its three prep prompts ask for stories, not cases. Everything about a case itself comes from candidate reports, so treat it as likely, not certain.

Now run one out loud the way a Booz Allen interviewer would expect, with a technology capacity problem:

What differs by track, as far as published sources show:

• Consulting and strategy roles: these are the roles where candidates report the final round of three interviews with one possible case. CaseBasix describes the interviewers as often client-facing government consultants, and PrepLounge says Booz Allen prioritizes behavioral and fit assessments over traditional case studies. Hacking the Case Interview contrasts this with MBB firms by saying Booz Allen gives 0 to 1 cases to their 4 to 6, which is that site's estimate, not Booz Allen's.
• Technology, cyber, analytics and engineering roles: Booz Allen says some roles include a skills-based assessment and that interviews often include technical screens. The reported topics are technical (compliance frameworks, SQL, Python, cloud platforms), with no case described. A business-style case is possible but unconfirmed.
• Government, defense and cleared roles: Booz Allen publishes no separate interview for these. What changes is the posting, which asks you to hold or be able to obtain a clearance, and the federal investigation that follows an offer. The Booz Allen interview guide covers the posting wording and the rules.
• Early career roles: Booz Allen's careers page points students to internships and early careers but gives no interview detail on the page we read.

The honest summary is that cases are the smaller part of this interview. Spend most of your time on the three official story prompts and your behavioral answers, using the STAR method guide and the behavioral interview guide for consulting, and use the cases below as a second layer if your invitation or recruiter confirms one.

Does Booz Allen publish practice cases?

No: the Booz Allen careers pages we read contain no practice case, so every example here is original. The candidate resources page describes the process and three prep prompts, the application FAQs cover camera and identity rules, and neither page describes a case. Booz Allen does publish what it works on, and that is the best vocabulary for a government case:

• Health. Booz Allen says it has partnered with federal health organizations, including the Department of Veterans Affairs and the Military Health System, for more than half a century, and lists work on cloud, DevSecOps, retiring legacy systems without disrupting operations and change management to drive adoption. Its VA Health Connect story describes a Clinical Contact Center handling about 45 million calls a year, a CRM that pulled data from more than 10 systems into one interface, and staff going from as many as 45 applications to one. Case 2 uses that kind of contact center problem with made-up numbers.
• Defense. Booz Allen describes predictive maintenance tools that forecast part demand from operational tempo. Case 3 is a spare parts problem in that spirit.
• Cyber and technology. Its careers page lists cybersecurity, engineering, digital solutions and technology solutions as focus areas. Cases 4, 5 and 6 are vulnerability, legacy system and data center problems.

Read two or three of these pages before an interview for vocabulary, and do not treat them as prompts. If you want the general frameworks first, the government and public sector case interview guide covers them.

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• Learn how to caseGuided learning · 35 min
• The Case Interview MethodLesson · 8 min
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Which case types does Booz Allen ask, and which worked case covers each?

Each case below sits in a market Booz Allen lists on its careers page, so you can start with the one that matches the role you applied to. The careers page names Defense, Intelligence, Space, Civil (including Health, Homeland Security and Law Enforcement, Transportation, and Energy, Resources and Utilities), International and Commercial work (checked November 12, 2026).

All numbers in Cases 2 to 7 are assumptions made up for practice. Case 1 uses the reference inputs stored with the library case. State your own assumptions out loud in an interview, exactly as the cases do.

The loop to run on every case

Read only the prompt, write your structure and your questions, then open the solution. The cases use the same five parts so you can compare each to your own:

1. Prompt: the client, the decision and the constraint.
2. Clarifying questions: what you would ask, and what the interviewer would plausibly say.
3. Structure: two to four branches you can test, not a template.
4. The math: every step substituted, with units.
5. Recommendation: a decision, one number, one risk and a next step.

With a federal client, add one question to every case: what is the constraint on money and time that the mission sets, for example a budget that cannot grow or a deadline set by law? The technology case interview guide, healthcare case interview guide and operations case interview guide teach the frameworks. This page is for reps.

Case 1: A public health service and older patients

Prompt. The Sydney Department of Health has found that people over 60 are unhappy with the time and quality of the hospital services they receive, and asks what it should investigate and change. This is the library case National Health System, adapted from the INSEAD casebook. The numbers below are its own reference inputs, which its exhibit labels as illustrative.

Clarifying questions. Which services cause the unhappiness? In the case, older patients are generally content with community medical centres, and the problem sits in hospital services reached by a GP referral and an online booking. Ask for the objective (better hospital services for older patients), a waiting-time baseline and a budget. The case supplies neither, and saying so is a good move: it tells the interviewer your first recommendation will be about what to measure.

Structure. Link what older patients need to the care process and to feasibility:

• Needs: what time and quality mean for someone over 60, such as the wait for a slot, the wait on the day, a correct diagnosis and follow-up.
• Process: booking and transport, waiting and treatment, follow-up, each with hypotheses.
• Feasibility: funding, hospital management, staff and union support.

The math. How many specialists does the department need? The reference inputs are 16 million people with ages spread evenly from 0 to 80, four visits a year for each person over 60, 30 minutes a visit, 8 hours a day, 5 days a week, 50 weeks a year, and 1,000 specialists today.

1. People over 60: ages 60 to 80 are 20 of 80 years, so 20 / 80 = 25%, and 25% x 16M = 4M people.
2. Visits: 4M x 4 = 16M visits a year.
3. One specialist: 8 x 5 x 50 = 2,000 hours a year, and at 30 minutes a visit that is 2 visits an hour, so 4,000 visits a year.
4. Specialists needed: 16M / 4,000 = 4,000. Beyond the 1,000 in place, that is 3,000 more.

The usual slip is reading 30 minutes as one visit an hour and doubling the capacity to 8,000, which halves the answer. Check units before you divide.

Recommendation. Make medical histories available across the hospital system first, since that fixes a cause the case confirms without hiring, and phase staffing toward the 3,000 gap. The estimate assumes every specialist hour goes to these visits and every specialist can be redeployed, so validate utilization, recruitment and funding first. To run the case out loud, use the link in the table above.

Independent

Run the National Health System case

Public sectorMedium

Practice this case free

Case 2: A federal health contact center

Original practice case, not a Booz Allen case.

Prompt. A federal health agency runs clinical contact centers that take 3.6 million calls a year. Leadership is considering a $9 million customer relationship management (CRM) system to cut call volume and handling time. Should the agency buy it? All numbers are practice assumptions.

Clarifying questions. What does the CRM change: repeat calls, handling time, or both? What counts as a repeat call? How many agents do we have, and what does one cost? What payback does the agency require? You get: 25% of calls are repeats of an unresolved issue, the average call takes 9 minutes, an agent handles 1,500 productive hours a year, an agent costs $75,000 a year fully loaded, the CRM costs $9 million up front and $1.5 million a year to run, and the agency wants payback within 3 years. The vendor says the CRM cuts repeat calls to 10% of volume and handling time to 8.5 minutes.

Structure.

• Demand: calls, split into first calls and repeats.
• Workload: calls times minutes, converted to agent hours.
• Benefit: fewer repeat calls and shorter calls, converted to agents and dollars.
• Cost and test: up-front and running cost, payback, and how sensitive it is to the vendor's claim.

The math.

1. Today's workload: 3.6M calls x 9 minutes = 32.4M minutes, which is 540,000 hours. At 1,500 hours an agent that is 360 agents.
2. First calls: 75% of 3.6M = 2.7M unique issues. The other 0.9M are repeats.
3. With the CRM, repeats are 10% of volume, so 2.7M is 90% of calls: 2.7M / 0.9 = 3.0M calls, which is 0.6M fewer.
4. New workload: 3.0M x 8.5 minutes = 25.5M minutes, which is 425,000 hours, or 283 agents.
5. Agents released: 360 - 283 = about 77, worth 77 x $75,000 = about $5.75M a year.
6. Net of running cost: 5.75 - 1.5 = $4.25M a year, so payback is 9 / 4.25 = 2.1 years, inside the 3-year hurdle.
7. Stress the vendor's claim: if repeats only fall to 18% of volume, calls are 2.7M / 0.82 = 3.29M, and at 8.5 minutes that is 311 agents. Savings are 49 agents x $75,000 = $3.7M, net $2.2M, and payback is 9 / 2.2 = 4.1 years, which fails the hurdle.

Recommendation. Buy it, but in phases, starting at the two largest centers, because at the vendor's numbers it pays back in about 2 years and the agency can still stop if repeat calls stay near 18%. The weakest assumption is the 10% repeat rate, so measure repeat calls at the first two sites for a quarter before committing the rest of the $9 million. The model also leaves out the value to patients of a resolved first call, which is the real mission reason to do it.

Case 3: Spare parts stockouts at new equipment sites

Original practice case, not a Booz Allen case.

Prompt. A defense logistics command supplies spare parts to 12 installations. Six installations received new equipment three years ago, and stockouts there are well above the other six. The commander asks where the stockouts come from and what to fix first. All numbers are practice assumptions.

Clarifying questions. How many parts requests does each site make a year? What is a stockout: a part not on the shelf when requested? What does a stockout cost? Is the problem the same at all six new sites? You get: 20,000 requests per site per year, a stockout means the part is not available at the site when requested, one stockout costs about $1,800 (expedited shipping plus idle equipment days), and the pattern is the same at all six new sites. Stockout rates are 4% at the six older sites and 14% at the six new ones. A team reviewed the excess stockouts at the new sites by cause and produced the exhibit below.

Structure. Size the problem, then split it by cause and test each lever:

• Size: stockouts today, and the excess over the older sites.
• Causes: catalog, forecast, distribution, supplier.
• Levers: for the biggest causes, what fix removes how much, at what cost.

The math.

1. Requests: 12 x 20,000 = 240,000 a year.
2. Stockouts: older sites 6 x 20,000 x 4% = 4,800. New sites 6 x 20,000 x 14% = 16,800. Total 21,600, which is 9.0% of requests.
3. Excess at the new sites: 16,800 - 4,800 = 12,000, which is 56% of all stockouts.
4. Cost of the excess: 12,000 x $1,800 = $21.6M a year.
5. Split by the exhibit: catalog 55% x 12,000 = 6,600; forecast 30% = 3,600; distribution 10% = 1,200; supplier 5% = 600.
6. Catalog fix: adding the missing parts removes 90% of 6,600 = 5,940 stockouts, worth 5,940 x $1,800 = $10.7M a year, for a one-time $2.4M.
7. Forecast fix: a new demand model halves 3,600, so 1,800 stockouts, worth $3.2M a year, for $1.5M a year to run.
8. Together: 7,740 fewer stockouts, so the overall rate falls from 9.0% to (21,600 - 7,740) / 240,000 = 5.8%. The catalog fix alone takes it to 6.5%.

Recommendation. Fix the catalog first: it removes about half of the 12,000 excess stockouts for $2.4M once, and it pays for itself in under three months. Add the forecast model second. The risk is the exhibit itself: the shares come from a review of a limited number of stockouts, so confirm the 55% on a larger sample before you cancel anything else. Also say what the dollars leave out, which is the readiness cost of a vehicle that cannot move, not only the $1,800.

Case 4: A cyber vulnerability backlog

Original practice case, not a Booz Allen case.

Prompt. A federal agency's security team has 40,000 open vulnerabilities across its systems and a deadline from its inspector general to show progress in six months. How should the team decide what to fix first? All numbers are practice assumptions.

Clarifying questions. How many are critical or high severity? How many are on systems reachable from the internet? How many does the team fix a month, and how many new ones arrive? What happens if a low-severity item is never fixed? You get: 5% are critical (2,000), 20% high (8,000), 45% medium and 30% low. Twelve engineers each close 125 fixes a month, so the team closes 1,500 a month, and 1,200 new findings arrive a month. About 15% of critical and high findings sit on internet-facing systems, and the asset inventory is believed to be complete.

The math.

1. Capacity: 12 x 125 = 1,500 fixes a month, against 1,200 arriving, so the backlog shrinks by only 300 a month. At that rate 40,000 / 300 = 133 months, over 11 years. Working the list in order cannot meet a six-month deadline.
2. Hire only: eight more engineers at $140,000 is $1.12M a year and lifts capacity to 20 x 125 = 2,500. The net burn is 2,500 - 1,200 = 1,300 a month, so 40,000 / 1,300 = 31 months.
3. Critical and high: 2,000 + 8,000 = 10,000 findings. Internet-facing: 15% x 10,000 = 1,500.
4. Prioritize exposed ones first: 1,500 / 1,500 = 1 month of current capacity clears all exposed critical and high findings.
5. Then the rest of critical and high: 10,000 - 1,500 = 8,500. About 25% of the 1,200 new findings a month are critical or high, which is 300, and 15% of those (45) are exposed and are fixed on arrival. The other 255 join the backlog. Net burn is 1,455 - 255 = 1,200 a month, so 8,500 / 1,200 = about 7 months.
6. So all critical and high findings are cleared in about 8 months with the current team, and the exposed ones in the first month. Medium and low findings, 30,000 of the backlog plus 900 new ones a month, are not worked during that time.

Recommendation. Fix the 1,500 exposed critical and high findings in the first month, report that to the inspector general as the six-month deliverable's first milestone, and plan the remaining 8,500 critical and high findings over the following seven months. Do not hire to attack the whole list: it takes 31 months and does not put exposed systems first. The risk is the inventory. If unknown internet-facing systems exist, the 1,500 is too low, so run an external scan to compare the asset list with what is actually reachable before the first month ends. State plainly that medium and low findings are accepted risk with compensating controls, not ignored.

Case 5: Replace or modernize a legacy benefits system

Original practice case, not a Booz Allen case.

Prompt. A federal agency's benefits system runs on a 30 year old platform that costs $42M a year to operate. The vendor will end standard support in year 4, which adds $9M a year after that. The agency is choosing between a full replacement and a modular upgrade. Which should it pick? All numbers are practice assumptions, in millions of dollars over 10 years and undiscounted.

Clarifying questions. What does each option cost to build and run? How long does each take? How do outcomes change if the build runs over? Are there mission constraints, such as payments that cannot be interrupted? You get: a full replacement costs $120M to build over 3 years and $22M a year to run afterward. A modular upgrade costs $54M over 3 years and brings run cost to $34M a year afterward. During the build the legacy system keeps running at $42M a year. Benefits payments must not stop at any point.

Structure.

• Status quo: run cost, plus the extended support penalty from year 4.
• Option A, full replacement: build, then run.
• Option B, modular upgrade: build, then run.
• Risk: overrun, interruption of payments, interfaces between old and new.

The math.

1. Status quo, 10 years: years 1 to 3 at $42M is 126. Years 4 to 10 at $42M + $9M = $51M is 7 x 51 = 357. Total $483M.
2. Option A: years 1 to 3 cost 40 of build plus 42 of legacy per year, so 3 x 82 = 246. Years 4 to 10 at $22M is 154. Total $400M, which saves $83M.
3. Option B: years 1 to 3 cost 18 of build plus 42 of legacy, so 3 x 60 = 180. Years 4 to 10 at $34M is 238. Total $418M, which saves $65M.
4. Overrun test, build cost up 30%. Option A: build 156, so 156 + 126 + 154 = 436, saving $47M. Option B: build 70.2, so 70.2 + 126 + 238 = 434.2, saving $49M.
5. So A saves $18M more than B on paper, and the lead disappears at a 30% overrun. A larger build also carries more risk to payments, since everything switches at once.

Practice an investment case for a government client

Public SectorHard

Start the investment case

Recommendation. Choose the modular upgrade. It gives up about $18M of saving over ten years, and in return the first modules go live in year 1 or 2, payments never depend on one cutover date, and it matches A at a 30% overrun. The risk to test is the seams between old and new modules: if interface work adds more than about $18M of cost, A wins. Ask the engineering team to price the interfaces for the first module before committing. Undiscounted figures flatter the later years, and A's extra cost comes early while its extra savings come late, so discounting (see the NPV case interview guide) would narrow its lead further. The cost benefit analysis framework page covers the structure.

Case 6: Consolidating federal data centers

Original practice case, not a Booz Allen case.

Prompt. A federal department runs 40 data centers at an average cost of $9M a year each. The CIO wants to consolidate and asks how much it saves and how fast it pays back. Hacking the Case Interview lists the savings from consolidating government data centers as an example of the quantitative part of a Booz Allen case, which is why this case exists. All numbers here are practice assumptions.

Clarifying questions. What is fixed and what is variable in the $9M? Are any sites unmovable? What does it cost to close and migrate one site? Can the remaining sites absorb the work? You get: $5M of each site's cost is fixed (facility and staff) and $4M is variable (servers and power). Eight sites hold classified work and must stay open. Closing and migrating a site costs $12M one time. Moving a site's workload into a receiving site cuts that workload's variable cost by 20% through virtualization. Each receiving site needs $10M of expansion to take the extra load.

Structure.

• Baseline: 40 sites x $9M, split into fixed and variable.
• Constraints: sites that cannot close.
• Savings per closed site: fixed cost saved, plus the variable cost reduction on its moved workload.
• One-time cost: migration, plus expansion of receiving sites, then payback.

The math.

1. Baseline: 40 x $9M = $360M a year, of which fixed 40 x 5 = $200M and variable 40 x 4 = $160M.
2. Closable sites: 40 - 8 classified = 32. Plan A closes 24 of them and keeps 16 open: the 8 classified sites and 8 receiving sites.
3. Fixed savings: 24 x $5M = $120M.
4. Variable savings: the 24 closed sites carry 24 x $4M = $96M of variable cost, and virtualization cuts 20% of it, so $19.2M.
5. Annual savings: 120 + 19.2 = $139.2M, which is 39% of $360M.
6. One-time cost: migration 24 x $12M = $288M, plus expansion of 8 receiving sites at $10M each = $80M, so $368M.
7. Payback: 368 / 139.2 = 2.6 years.
8. Plan B, close 12 and keep 28 open with 4 receiving sites: savings 12 x 5 + 12 x 4 x 20% = 60 + 9.6 = $69.6M, cost 12 x 12 + 4 x 10 = $184M, and payback 184 / 69.6 = 2.6 years.
9. Sensitivity for Plan A: if migration costs $18M a site, one-time cost is 24 x 18 + 80 = $512M and payback is 512 / 139.2 = 3.7 years.

Recommendation. Close the 24 sites in two waves of 12, because both plans pay back in 2.6 years and Plan A simply saves twice as much. Use the first wave to find out what a migration really costs before committing the second. The assumption that deserves the most pressure is the $12M per site: at $18M the payback moves past 3.5 years. Say that the 20% virtualization saving is the softest part, since it is only $19M of the $139M, and that the largest saving, the $120M of fixed cost, depends on actually closing buildings and releasing staff.

Case 7: Vaccination capacity on a flat budget

Original practice case, not a Booz Allen case.

Prompt. A state health agency must vaccinate 65% of its eligible adults within 12 weeks during an outbreak, with a flat $60M budget. How many sites does it need, and can the budget cover them? This is a practice case, the pandemic response prompt on our Booz Allen interview guide worked with numbers. All numbers are practice assumptions.

Clarifying questions. How many people are in the state, and what share is eligible? How many will be vaccinated by pharmacies and clinics without the agency? How fast is one lane, and how long are sites open? What does a site cost per week? You get: 8M people, 75% eligible, and pharmacies and clinics will deliver 40% of the doses. A lane gives 15 doses an hour. A site has 3 lanes, is open 8 hours a day for 6 days a week, and runs at 75% utilization. A site costs $60,000 a week.

The math.

1. Target: 8M x 75% = 6.0M eligible adults, and 65% of them is 3.9M to vaccinate.
2. Agency share: pharmacies and clinics deliver 40%, so the agency delivers 60% x 3.9M = 2.34M doses.
3. One site-week: 3 lanes x 15 per hour = 45 an hour, x 8 hours = 360 a day, x 75% = 270, x 6 days = 1,620 doses a week.
4. Site-weeks needed: 2.34M / 1,620 = 1,444, which over 12 weeks is 120 sites.
5. Budget: 1,444 x $60,000 = $86.7M, against $60M, so the plan is $26.7M over (45% above budget).
6. Lever one, a fourth lane per site: 4 x 15 = 60 an hour, so 60 x 8 x 75% x 6 = 2,160 doses a week. Assume the extra lane lifts a site's cost 15% to $69,000. The $60M buys 60M / 69,000 = 870 site-weeks and 870 x 2,160 = 1.88M doses, which is 80% of 2.34M.
7. Lever two, appointments lift utilization to 85%: 60 x 8 x 85% x 6 = 2,448 doses a week, so 870 site-weeks give about 2.13M doses, 91% of the need.
8. Lever three, a pharmacy partnership raises their share from 40% to 45%: the agency need is 55% x 3.9M = 2.145M, which the 2.13M almost covers, a gap of under 1%.

Recommendation. Run about 73 sites for 12 weeks (870 site-weeks / 12) with four lanes, appointment booking and a pharmacy partnership, which fits in $60M and covers about 99% of the doses needed. Adding lanes and booking does more than adding sites because each lever lifts doses per dollar, from 27 per $1,000 with three lanes to 31 with four lanes and 35 with four lanes at 85% utilization. The risk is the 85% utilization, since no-shows drive it, so overbook slots slightly and track daily utilization from week one. If it stays near 75%, the plan delivers 1.88M doses, so tell the agency in advance what the fallback is, such as extending the campaign by a week.

How do you turn these cases into a prep plan?

Spend most of your time on behavioral stories and the technical screen for your role, and use the cases as a second layer. Booz Allen's published prep prompts are stories, and candidates report that cases are the smaller part of the interview. Cases 1, 2 and 7 test capacity and sizing, Cases 3 and 4 test diagnosis and prioritization, and Cases 5 and 6 test investment and payback.

If your role sits in strategy, read the consulting interview process and the consulting interview prep timeline to see where a Booz Allen process differs from the usual. For the peers that also hire into government work, read the Guidehouse practice cases and the West Monroe practice cases, and use the top IT consulting firms page to compare the technology side. The case interview examples hub collects worked cases from other firms, and the digital transformation case interview guide covers the frameworks behind Case 4. If you want more math reps first, see case interview math practice.

Turn this guide into a Booz Allen Hamilton plan

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1

Learn the format

15 steps

• Learn how to caseGuided learning · 35 min
• The Case Interview MethodLesson · 8 min
• Profitability & Turnaround: AfrihealSkill drill · 5 min
• Profitability & Turnaround: Berty BankSkill drill · 5 min

Sources and further reading (checked November 12, 2026)

• Booz Allen: candidate resources (five-step process, technical assessment for some roles, interviews tailored to the role, three prep prompts, camera and ID rules)
• Booz Allen: application FAQs (camera, identity check; no mention of cases, clearances or citizenship)
• Booz Allen: careers (focus areas and markets: defense, intelligence, space, civil including health, homeland security, transportation and energy, international, commercial cyber)
• Booz Allen: health technology and IT modernization (VA and Military Health System partnership for more than half a century; work areas)
• Booz Allen: upgrading the customer experience at VA Health Connect (about 45 million calls a year, CRM on Salesforce Health Cloud, more than 10 systems into one interface, 45 applications to one; company-reported)
• Booz Allen: AI-enabled supply chain and predictive maintenance (defense predictive maintenance tools; company brochure)
• Hacking the Case Interview: Booz Allen Hamilton consulting interview (updated March 19, 2026; reported two-round process, final round of three interviews with a possible case, technical screen topics; a prep site, not Booz Allen)
• CaseBasix: Booz Allen Hamilton consulting interview (reported final round of three 30 minute interviews, candidate-led public sector cases; a prep site, undated, not Booz Allen)
• PrepLounge: Booz Allen Hamilton consulting interview guide (updated November 18, 2024; behavioral and fit prioritized, cases less common; a prep site, not Booz Allen)