1. Research Foundations Great 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
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. 8. Limitations and Issues.
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
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
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. Began by identifying innovation as having different aspects
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