Sparsh Goel | Profound

Sparsh's Profound AI Rep

Sparsh's stories span commercial due diligence, primary research design, and independent sector analysis.

Sparsh Goel

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Hypothesis-Driven Research Design

Sparsh builds research from the hypothesis down. Before a question is written or a call is scheduled, he has already mapped what he needs to prove and why each data point matters. This pattern showed up at Dalberg, where he grounded every questionnaire segment in secondary research signals before fielding a single question. It showed up again at McKinsey, where he built a structured scenario map before conducting expert interviews on cross-sell opportunity. The mechanism is consistent: break the problem into specific hypotheses, design the research to test each one, and let the evidence determine the conclusion rather than the brief. The result is research that holds up under scrutiny, because the structure was built to surface what is true, not to confirm what the client hoped to find.

Spotted in 3 Stories

Translating Evidence into Decisions

Sparsh turns research findings into structured, actionable conclusions, even when those conclusions contradict the original thesis. He separates what the data supports from what it does not, and communicates that distinction clearly to senior audiences. At McKinsey, he found that the fiduciary tailwind thesis was stalled and communicated that directly to a PE client who had expected a different answer. He held the position under pushback, supported by expert testimony and a clear confidence assessment. At Dalberg, he converted raw survey data into a benchmarked investment opportunity map, layering in qualitative findings to explain the numbers rather than just report them. The pattern is consistent: the conclusion leads, the evidence follows, and the limitations are stated explicitly rather than buried.

Spotted in 3 Stories

Testing Sector Theses Against Constraints

Sparsh does not accept sector narratives at face value. When a thesis looks compelling on the surface, he traces it upstream to find where the structural constraints sit. On the ethanol blending opportunity in India, he moved past the renewable energy framing to examine the water intensity of the feedstock crops, identifying a supply-side constraint that the optimistic forecasts were underweighting. On the fiduciary tailwind thesis in US retirement services, he found that the regulatory landscape had been stalled for years and was not a reliable business lever. The pattern is consistent: read the optimistic case, then find the constraint that the headline does not price in. This is the instinct that makes research useful in an investment context, where the cost of a wrong thesis is real.

Spotted in 2 Stories

Sparsh Goel

Career Stories

Retirement Services Due Diligence: Testing the Cross-sell Thesis

At McKinsey & Company as Analyst

2026

Ethanol Blending in India: Building an Independent Sector View

At McKinsey & Company as Analyst

2026

McKinsey Cross-Sell Workstream: Mapping Retirement-to-Wealth Expansion Scenarios

At McKinsey & Company as Analyst

2026

Dalberg Physical Activity Study: Designing India's Baseline Research

At Dalberg as Summer Intern

2023 - 2023

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