Research FoundationsGreat By Choice

Group 6

Justin Schamp, Stuart Gaston, Michael Grizzle, Tate Roueche, Ryan Moeller, Rachel Camunez

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

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.

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

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

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

Methodology

◦ 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

10X- Company Selection

◦ 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

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

10X 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)

Comparison – Company Selections

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

20 Mile March 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

Innovation Analysis

From the 290 innovation events analyzed researchers came out with these findings

1. Most companies had a high amount of innovations

2. There is an “ Innovation Threshold” in each industry

3. 10X companies were Not more innovative then their comparison companies

4. 10X companies pursued more incremental innovations

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

Bullets then Cannonballs Analysis

Findings1. 10X companies fired more bullets then

their comparison companies2. 10X companies did not fire more

cannonballs3. 10X companies had a higher portion of

calibrated cannonballs4. Calibrated cannonballs produced more

positive outcomes 5. 10X companies were overall more

successful with their cannonballs

Looked at the financial statements from each company to determine their cash reserves and debts

1. 10X companies had a more conservative balance-sheet during the observation period

2. 10X companies were more conservative during their first five years as public companies

3. During the first year as a public company, 10X companies were more conservative

Cash And Balance-sheet Rick Analysis

Researchers analyzed 114 decision events Three Categories of Risk

Death Line Risk – could kill or severely damage the companyAsymmetric Risk – the potential downside is greater than the upsideUncontrollable Risk – the company is exposed to forces and events it cannot control

Risk- Category Analysis

Findings

1. 10X companies made fewer death line risk decisions

2. 10X companies made fewer asymmetric risks

3. 10X companies made fewer uncontrollable risk decisions

4. 10X companies overall made less risk decisions

5. 10X companies were more successful in a risk categories

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)

Speed Analysis

1. early recognition of an unequal moment was associated with a good outcome with strong evidence

2. The benefit of fast decision making depended on the pace of events

3. Deliberate decision making was associated with good outcomes

4. The benefit of fast execution depended on the pace of events

5. The 10X companies adhered to findings 1-4 more than the comparison companies

Findings

Findings1. The 10X companies clearly understood the

SMaC recipes2. The comparison companies fairly understood

the SMaC recipes3. The 10X companies rarely changed their SmaC

recipes4. The comparison companies changed their SMaC

recipe elements more than the 10X companies5. On average, both sides took a long time to

change their elemnts

SMaC – Recipe 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

Luck Analysis

“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

Graduations of Luck

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)

Genentech in 1977

1. Both the 10X companies and the comparison companies experienced good luck during the observation period

2. The 10X companies didn’t experience substantially more good luck

3. The 10X companies didn’t experience more high-importance and pure good luck events

4. The 10X companies didn’t experience substantially more good luck events during their early years

5. The comparison companies didn’t experience substantially more bad luck events than the 10X companies

6. The comparison companies didn’t experience substantially more bad luck events during their early years

Findings

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

Hockey Hall of Fame Analysis