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Research Foundations Great By Choice

Research Foundations Great By Choice. Group 6 Justin Schamp, Stuart Gaston, Michael Grizzle, Tate Roueche, Ryan Moeller, Rachel Camunez. Methodology . 1. Identifying the Research Question and Unit of Analysis Why do some companies thrive in uncertainty, even chaos, and others do not ?

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Research Foundations Great By Choice

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  1. Research FoundationsGreat By Choice Group 6 Justin Schamp, Stuart Gaston, Michael Grizzle, Tate Roueche, Ryan Moeller, Rachel Camunez

  2. Methodology • 1. Identifying the Research Question and Unit of Analysis • Why do some companies thrive in uncertainty, even chaos, and others do not? • Must meet all 5 characteristics • The unit of analysis was a company era • This era covered the company’s start-up phase, its transition to a public company, its growth years, and its mature years as a large public enterprise

  3. Methodology • 2. Selecting the Appropriate Research Method: the Matched-Pair Methodology • Maximize the potential for discovering new insights • Based on qualitative data collection • Follows a tradition in organizational behavior, finance, and medical research • Avoid sampling on success by selecting both successful and less successful companies, and studied the contrast.

  4. Methodology • 3. Selecting the Study Population: Companies That Went Public in the U.S. • So companies would feel impact of uncertain and chaotic events around them • Chose those who started in the U.S. between 1971-1990 • 4. Identifying Exceptionally Performing Companies • Chose a performance measure, stock return, that applies equally across industries • Went through screening process and identified 7 10X companies

  5. Methodology • 5. Selecting Comparison Companies • Used 2 principles for selecting a comparison company for each 10X company • 1. When the company became public, comparison should have been similar • 2. Registered an average stock market performance • 6. Collecting Data: Historical Chronology • Went back in time and collected historical documentation for each company

  6. Methodology • 7. Conducting Analysis. • Within Pair Analysis • Cross pair analysis • Concept generation • Financial analysis • Event-history analysis • 8. Limitations and Issues. • Discussion of the strengths and weaknesses found using this research method

  7. 10X- Company Selection • Used 3 principles to identify the study set of exceptionally performing companies • 1. They achieved spectacular results • 2. They were highly uncertain and chaotic industries • 3. They were vulnerable early on

  8. 10X Company Selections • Started with a data set drawn from the University of Chicago Center for Research in Security Prices (CRSP) database and filtered the steps down to: • Cut1: Select companies first appearing in CRSP 1971-95 • Cut 2: Keep companies in existence after June 2002 • Cut 3: Meet initial stock performance threshold • Cut 4: Verify were real U.S. companies with IPOs 1971-90 • Cut 5: Eliminate companies with less than

  9. 10X Company Selections • Cut 6: Meet stock-performance threshold from IPO date to 15 years afterward • Cut 7: Eliminate companies with inconsistent stock-performance patterns • Cut 8: Select companies in highly uncertain and chaotic industries • Cut 9: Red Flag test • Cut 10: Young or small at IPO • Cut 11: Outperform industry index

  10. Comparison – Company Selections • Using the historical documents, conducted a systematic search to identify industry peers, scored each, and selected best match • They were scored based on 6 criteria: • 1. Business fit (early years) • 2. Age fit • 3. Size fit • 4. Conservative test • 5. Performance gap • 6. Face validity (in 2002)

  11. 20 Mile March Analysis • They coded for and analyzed the companies’ 20 Mile March behaviors and noted whether they articulated and achieved such behaviors. • Finding 1. The 10X companies practiced the 20 Mile March principle to a much greater extent than the comparison companies. • Finding 2. Companies that practiced the 20 Mile March principle at a given time performed much better in subsequent industry downturns than those that didn’t

  12. Innovation Analysis Began by identifying innovation as having different aspects • Innovation has different dimensions - Product, Operational, Business – model • Innovation has different degrees - Major, Medium, Incremental • Innovation has different reference points • Innovation does not guarantee economic success

  13. From the 290 innovation events analyzed researchers came out with these findings • Most companies had a high amount of innovations • There is an “ Innovation Threshold” in each industry • 10X companies were Not more innovative then their comparison companies • 10X companies pursued more incremental innovations

  14. Bullets then Cannonballs Analysis Researchers analyzed 62 cannonball events from the 10X companies and their comparison’s Bullets – A low cost, low risk, and low distraction empirical test, that helps companies learn what works Cannonballs – Products associated with large costs and risk, either calibrated or un-calibrated

  15. Findings • 10X companies fired more bullets then their comparison companies • 10X companies did not fire more cannonballs • 10X companies had a higher portion of calibrated cannonballs • Calibrated cannonballs produced more positive outcomes • 10X companies were overall more successful with their cannonballs

  16. Cash And Balance-sheet Rick Analysis Looked at the financial statements from each company to determine their cash reserves and debts • 10X companies had a more conservative balance-sheet during the observation period • 10X companies were more conservative during their first five years as public companies • During the first year as a public company, 10X companies were more conservative

  17. Risk- Category Analysis • Researchers analyzed 114 decision events • Three Categories of Risk Death Line Risk – could kill or severely damage the company Asymmetric Risk – the potential downside is greater than the upside Uncontrollable Risk – the company is exposed to forces and events it cannot control

  18. Findings • 10X companies made fewer death line risk decisions • 10X companies made fewer asymmetric risks • 10X companies made fewer uncontrollable risk decisions • 10X companies overall made less risk decisions • 10X companies were more successful in a risk categories

  19. Speed Analysis • Analyzed 115 time-sensitive moments • Unequal moments = events where there are signs that conditions have changed & the risk profile is changing with time • Classification of unequal moments • Pace of Events (slow-moving/fast-moving) • Nature of Moment (threat/opportunity) • Clarity of Response (clear/unclear) • Outcome (good/poor)

  20. Findings • early recognition of an unequal moment was associated with a good outcome with strong evidence • The benefit of fast decision making depended on the pace of events • Deliberate decision making was associated with good outcomes • The benefit of fast execution depended on the pace of events • The 10X companies adhered to findings 1-4 more than the comparison companies

  21. SMaC – Recipe Analysis • Findings • The 10X companies clearly understood the SMaC recipes • The comparison companies fairly understood the SMaC recipes • The 10X companies rarely changed their SmaC recipes • The comparison companies changed their SMaC recipe elements more than the 10X companies • On average, both sides took a long time to change their elemnts

  22. Luck Analysis • Luck event = (1) some significant aspect of the events occurs largely or entirely independently of the key actors of the enterprise; (2) the event has a potentially major consequence (good or bad) for the enterprise; (3) the event has some element of unpredictability

  23. Graduations of Luck • “Pure Luck” = the occurrence of the event is completely independent of the actions of the key actors of the enterprise • “Partial Luck” = the occurrence of the event is largely but not completely independent of the actions of the key actors

  24. Genentech in 1977 • 1 year of gene – splicing • Likely due to skill, and not luck • Lucky that no other individual, group/company had achieved this before • Coded as “partial luck” (combo of skill, luck, and timing)

  25. Findings • Both the 10X companies and the comparison companies experienced good luck during the observation period • The 10X companies didn’t experience substantially more good luck • The 10X companies didn’t experience more high-importance and pure good luck events • The 10X companies didn’t experience substantially more good luck events during their early years • The comparison companies didn’t experience substantially more bad luck events than the 10X companies • The comparison companies didn’t experience substantially more bad luck events during their early years

  26. Hockey Hall of Fame Analysis • Compared the distribution of birth months in the general Canadian population with those of people in the hockey hall of fame • Findings • No disproportionate # of hockey hall of fame inductees born in Canada between Jan-March

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