Industry Playbooks
Research workflows for MBA students cover the distinct research types that MBA education requires — case study preparation, consulting and banking recruiting, case competition analysis, and strategy paper research — each requiring different sources, different depth, and different output formats.
MBA research is practically oriented in ways that undergraduate research rarely is. When an MBA student researches an industry, they're usually doing so to develop the conversational depth that recruiting requires, to prepare a recommendation for a case competition, to evaluate a company for a finance course project, or to inform a class discussion where weak research is visible in real time.
This practically-grounded research creates a distinctive challenge: the quality of MBA research is not primarily judged by academic rigor (methodological precision, comprehensive literature review, theoretical contribution) but by practical applicability — can you walk into an interview and discuss this industry with genuine depth? Can you build a DCF model that reflects your understanding of the company's business model? Can you make a defensible recommendation in a case competition with 72 hours of preparation time?
Research workflows for MBA students are workflows tuned for practical applicability: finding the most relevant, most current, most credible sources quickly; extracting the analytically relevant content efficiently; and organizing the findings to support the specific output you need — a recruiting conversation, a case competition memo, a strategy class contribution.
This article covers four research contexts that MBA students regularly face, each requiring a different workflow: case study preparation research, industry and company research for recruiting, case competition research, and financial modeling and company analysis research.
Most MBA case studies are designed to be self-contained — the case provides the information you need to do the analysis. But MBA professors frequently assign "bring your outside research to class" cases, expect students to contextualize cases with current information, or design cases that require you to know something about the industry that the case doesn't provide.
Workflow for case study background research:
Step 1 — Identify what the case doesn't provide but the analysis requires. Read the case first. Identify the information gaps: Does the competitive analysis require knowing the market shares of competitors the case mentions but doesn't quantify? Does the financial analysis require knowing industry-average margins to benchmark against? Does the strategic decision require knowing regulatory developments after the case's date?
Step 2 — Identify the minimum additional research needed. Case preparation research should be targeted and efficient — you have many cases to prepare, not just one. List the specific pieces of information that would most improve your analysis, not an exhaustive research agenda.
Step 3 — Best sources for case supplementary research:
| Information Need | Best Source |
|---|---|
| Industry structure and market size | IBISWorld (available through most business school libraries), Statista |
| Company financials and market cap | Yahoo Finance, company investor relations website, Capital IQ (school access) |
| Recent company news and strategy | Company earnings calls, press releases, news database (Factiva if available) |
| Competitive intelligence | Company 10-K filings (risk factors section discusses competitors), Crunchbase for startups |
| Industry trends and disruption | McKinsey Global Institute reports, Bain & Company insights, BCG publications (free online) |
| Management consulting frameworks applied to this industry | Harvard Business Review case studies (if related), consulting firm publications |
Step 4 — Synthesize into the case preparation note. Additional research findings should enhance your case preparation note — not replace the case analysis, but provide the context that makes your analysis more sophisticated and your recommendations more defensible.
MBA recruiting research has two layers: industry depth (understanding the competitive dynamics, key players, major trends, and strategic challenges of the industry you're targeting) and firm-specific knowledge (understanding the specific firm's strategy, culture, practice areas, and recent work).
Industry depth research workflow:
Layer 1 — Industry structure (30-60 minutes): Start with IBISWorld or a comparable industry database for market size, competitive structure, major players, and growth drivers. This gives you the vocabulary and baseline metrics for the industry. Supplement with a Google search for recent news on the industry — what's been happening in the last 6-12 months that a practitioner would assume you know about.
Layer 2 — Industry thought leadership (60-90 minutes): The major consulting firms publish high-quality, free industry analyses: McKinsey Global Institute reports, Bain industry briefs, Deloitte insights, EY sector analyses. These publications reflect what sophisticated advisors think about industry dynamics and often use the exact language that practitioners use in recruiting conversations. Reading two or three relevant reports builds the vocabulary and analytical framework for intelligent conversations about the industry.
Layer 3 — Earnings calls and investor communications (30-45 minutes): The management teams of major public companies in the industry discuss industry dynamics, competitive threats, and strategic choices on quarterly earnings calls and at investor days. These calls are publicly available through company investor relations pages and are incredibly informative — you hear how executives actually talk about their business, what they're worried about, what they're investing in. Earnings call transcripts are available through Seeking Alpha (limited free access), The Motley Fool, and sometimes directly from the company's IR page.
Layer 4 — Practitioner conversation notes: What you've learned from alumni coffee chats, career treks, and informational interviews should be integrated into your industry intelligence file. Practitioners provide the ground-level context that published research can't — which subverticals are most interesting, what the culture differences are between firms, what skills matter most for success in this industry.
Firm-specific research workflow:
For each target firm, research should cover:
Case competitions — whether internal MBA competitions or national competitions like Danaher Business Case Competition, HBS Business Case Competition, or industry-specific competitions — present a unique research challenge: you typically have 24-72 hours to research an unfamiliar company or industry and produce a professional-quality strategic recommendation.
The 72-hour case competition research workflow:
Hour 0-4 — Case brief analysis and research agenda: Read the case carefully and define exactly what you need to know. Don't start researching until you have a clear list of questions the research needs to answer. Typical questions: What is the strategic problem the company faces? What is the relevant market structure? What have competitors done in similar situations? What data would validate or refute the key hypotheses about the solution?
Hours 4-12 — Targeted source collection: Divide research tasks across team members by type: one person on the company (10-K, earnings calls, recent news), one on the industry (IBISWorld, consulting firm publications), one on comparable cases or precedents (other companies that faced similar decisions, academic or HBR case studies on analogous situations).
Each researcher creates a brief summary of their findings — not a comprehensive literature review, but the three to five most analytically relevant findings. The goal is to have a shared synthesis by Hour 12 so the team can begin framework application.
Hours 12-24 — Framework application and hypothesis testing: Apply the relevant strategic framework (Porter's Five Forces for industry entry decisions; BCG matrix for portfolio questions; SWOT for situation assessment followed by strategy selection). Test your working hypotheses against the research findings — which hypotheses does the research support? Which does it undercut? This is where research connects to analysis.
Hours 24-48 — Synthesis and recommendation development: The recommendation should be specific, actionable, and financially grounded. MBA case competition recommendations that can't answer "by how much would this move the financial metrics?" are weaker than those that at least attempt quantification.
Hours 48-72 — Presentation preparation: The research finding that doesn't make it into the presentation isn't useful. Every slide should be directly supported by research evidence. Cut what isn't analytically load-bearing.
For finance courses (corporate finance, investment management, M&A), private equity recruiting, and financial modeling assignments, the research workflow is more quantitative and securities-focused.
Company financial analysis research workflow:
Step 1 — Understand the business model (not just the financials): Before analyzing the numbers, understand how the company makes money: revenue model, customer acquisition, key operational drivers, competitive dynamics. The 10-K (annual report to the SEC) is the primary source — the Business Description and Risk Factors sections explain the business model; the Management Discussion and Analysis section explains the year's financial performance in management's own words.
Step 2 — Collect historical financials: For DCF modeling and comparable company analysis (comps), you need 3-5 years of historical income statement, balance sheet, and cash flow statement data. Sources:
Step 3 — Develop operating model assumptions: The most important assumptions in a DCF are the revenue growth rate, operating margin, and WACC. Supporting these assumptions requires:
Step 4 — Comparable company analysis: Comps analysis requires identifying a peer set — companies in the same industry with similar business models, scale, and growth profiles. Finding the peer set requires understanding the industry well enough to know who the true comparables are, not just who shares an SIC code.
Step 5 — Sensitivity analysis: Any financial model without sensitivity analysis is incomplete. The base case DCF is a point estimate; the sensitivity table shows what the value is across a range of revenue growth and margin assumptions. This is both analytically important and presentation-important — it demonstrates that you understand what drives value rather than just executing the model mechanics.
| Context | Tool | Notes |
|---|---|---|
| Case study background | IBISWorld, company IR pages | Targeted to case gaps; not comprehensive research |
| Industry depth | McKinsey/Bain/BCG publications, IBISWorld | Free consulting firm publications are high-quality |
| Firm-specific research | Company website, LinkedIn, alumni network | Practitioners are the best source of firm culture |
| Company financials | SEC EDGAR (free), Capital IQ (school) | 10-K is the primary source; databases for efficiency |
| Case competition | Targeted multi-source, time-constrained | Divide by type; synthesize by Hour 12 |
| News and market intelligence | Google Alerts, Bloomberg, FT | Set alerts for target companies and industries |
| Web resource capture | WebSnips | Consulting publications, IR presentations, industry reports |
| Citation management | Zotero | For strategy papers; generates citations |
| Financial modeling | Excel | DCF, comps, LBO — build from first principles |
WebSnips for MBA research: The high-quality, publicly available research that feeds MBA industry knowledge lives on the web: McKinsey Global Institute reports, Bain Brief publications, BCG thought leadership, company investor day presentations, industry conference proceedings, and regulatory agency market analyses. These are the sources that consulting firm analysts read to build their own industry knowledge. WebSnips captures them with date and source URL — critical because a McKinsey report on digital banking from 2022 has different relevance to today's competitive landscape than one from 2025. Organized by industry (FinTech, Healthcare Services, Consumer), firm (Target Firm A recruiting research, Target Firm B), and project (Case Competition: Retail Strategy), WebSnips clips build the organized, dated intelligence library that makes MBA research systematic rather than ad hoc. When you're in a 72-hour case competition, having the industry's relevant consulting publications already captured and organized saves you the 2-3 hours you'd otherwise spend re-finding them.
An MBA student, Jordan Park, is recruiting for management consulting with a focus on technology strategy. She has a first-round interview in two weeks with a major consulting firm.
Layer 1 — Industry structure (Thursday evening, 45 minutes): Jordan starts with IBISWorld's Management Consulting industry report: market size ($350B+ globally), growth drivers (digital transformation, cost optimization, AI adoption), major players and market concentration. She notes the trend toward "implementation" versus "recommendation" work and the blurring of consulting and systems integration.
Layer 2 — Consulting firm thought leadership (Friday, 60 minutes): Jordan reads two McKinsey Technology reports from the past 18 months (captured via WebSnips with dates): "The State of AI: From Hype to Reality" and "Digital Transformation: Closing the Value Gap." These give her the vocabulary and analytical frameworks that this firm's practitioners use. She notes specific phrases and frameworks from each report in her industry intelligence file.
Layer 3 — Company-specific research (Friday evening, 45 minutes): Jordan visits the firm's website: she reads their most recent annual review (for public/large partnerships), three recent case studies from the technology practice group, and a leadership profile of the practice head. She notes the specific types of technology strategy engagements they highlight — AI implementation, cloud transformation, enterprise software — and connects these to the consulting publications she read.
Layer 4 — Alumni conversations (over the past two months): Jordan has had coffee chats with three alumni at this firm. She reviews her contact notes: one told her that AI implementation work is the fastest-growing practice; another mentioned that the firm is expanding its data analytics capability and hiring people with quantitative backgrounds; the third gave her the name of the recruiting coordinator who runs the MBA process.
Interview preparation: The night before the interview, Jordan synthesizes: she can speak about industry dynamics (from IBISWorld), about the firm's intellectual approach (from their publications, using their language), about the specific practice areas she's interested in (from the case studies), and she has three alumni relationship points to reference authentically. She's not memorizing facts — she's reviewing an organized system of knowledge she's built over two months.
Mistake 1: Research without a clearly defined research question. Starting research without knowing specifically what you're trying to find produces comprehensive but analytically unfocused output. Define what question the research needs to answer before opening a database.
Mistake 2: Relying on Wikipedia and basic news for industry knowledge. Wikipedia provides public-domain basics; news provides events. Neither provides the analytical depth — market structure, competitive dynamics, value chain economics, strategic trends — that MBA-level industry knowledge requires. Consulting firm publications and IBISWorld reports go significantly deeper.
Mistake 3: One-dimensional financial analysis. A DCF model that doesn't connect the revenue growth assumption to actual industry dynamics and company positioning is mechanically correct but analytically weak. Financial analysis and industry research should inform each other: the operating model assumptions should be grounded in industry research.
Mistake 4: Not saving research for future reference. Research done for one recruiting context often has direct applicability to a case competition, a finance course project, or a class discussion in a related course. MBA students who don't save and organize their research re-do the same work multiple times. A research library that grows throughout the MBA program is a significant time investment return.
Mistake 5: Waiting until the recruiting season to start industry research. Firms conduct coffee chats, career treks, and informational interviews throughout the year. The industry knowledge that makes these conversations genuinely mutual (rather than a one-directional information extraction) is built over months, not days. Start industry research early in the MBA program, not when recruiting deadlines approach.
Research workflows for MBA students are among the most practically consequential skills developed during the MBA — because the quality of your research directly determines the quality of your recruiting conversations, your case competition recommendations, your financial model assumptions, and your class contributions. The MBA students who develop systematic, efficient research workflows early — knowing which sources to go to for which questions, how to extract analytically relevant content quickly, and how to organize findings for future retrieval — gain a genuine professional advantage that persists well beyond graduation. The sources and databases change over a career; the research workflow habits formed during the MBA don't.
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