Category: Research Methods

Since many of my students aspire to work in consulting after they graduate, the purpose of this post is to round up some examples in the consulting space as related to research methods. This post will be updated from time to time.

• McKinsey article, “Not enough comps for valuation? Try statistical modeling”: https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/not-enough-comps-for-valuation-try-statistical-modeling
• McKinsey article, “Knowing when to stop: finding an appropriate sample in design research”: https://www.mckinsey.com/business-functions/mckinsey-design/how-we-help-clients/design-blog/knowing-when-to-stop-finding-an-appropriate-sample-in-design-research
• Forbes article, “How McKinsey Develops New Breakthrough Insight”: https://www.forbes.com/sites/christianstadler/2021/05/13/how-mckinsey-develops-new-breakthrough-insights/?sh=67befe286e66
• MedPage article, “McKinsey Reveals Methods; Critics Not Appeased”: https://www.medpagetoday.com/washington-watch/reform/27190
• US Senate Committee on Finance, “Baucus Calls on McKinsey to Release Methodology Behind Survey Results: Finance Chairman Formally Requests Information on Methods, Conclusions After Silence from Consulting Company”: https://www.finance.senate.gov/chairmans-news/baucus-calls-on-mckinsey-to-release-methodology-behind-survey-results
• BCG, “Ascent to the Cloud: How Six Key APAC Economies Can Lift-off”: https://www.bcg.com/publications/2019/economic-impact-public-cloud-apac/default (especially see Appendix at: https://www.bcg.com/publications/2019/economic-impact-public-cloud-apac/appendix-detailed-methodology
• ZS Associates, “How behavioral science can solve healthcare hurdles as large as vaccine hesitancy”: https://www.zs.com/content/dam/pdfs/ABI-research-executive-summary-wp.pdf
• McKinsey, “An experiment to inform universal basic income”: https://www.mckinsey.com/industries/public-and-social-sector/our-insights/an-experiment-to-inform-universal-basic-income

In the past, I have used power calculators like GPower for straightforward research designs, but I have never really found a good, practical resource on executing the mechanics of power simulations, especially when research designs and analytical frameworks are more complex. This great article provides a framework (with R code) to execute power simulations and may be useful to students in Research Seminar (AEM 6991). https://cameronraymond.me/blog/power-simulations-in-r/ . There is also a GitHub posting at https://github.com/cameron-raymond/power-simulation-tutorial.

Here are a few resources that students may find useful for research seminar projects that involve data scraping. This list of resources may be updated from time to time:

• Practical Introduction to Data Scraping Using Python – https://realpython.com/python-web-scraping-practical-introduction/
• Python, Data Scraping, and Beautiful Soup Crash Course – https://www.youtube.com/watch?v=XVv6mJpFOb0
• Facebook Data Scraping and Sentiment Analysis Using Python – https://www.danielherediamejias.com/facebook-scraping-and-sentiment-analysis-with-python/
• Twitter Data Scraping and Python – https://www.natasshaselvaraj.com/how-to-scrape-twitter/