1. Meeting the Opportunity of “Big Data”: Lessons from Science Learning for Life Series October 1, 2014
Benjamin F. Jones
Gordon and Llura Gund Family Professor of Entrepreneurship
Kellogg School of Management, Northwestern University

2. Big Data Big Data is an opportunity and a challenge.
Opportunity: New answers.
Challenge: New answers to what exactly?
How do we make sense of all this data?
What are the right questions?

3. …or Put Another Way (Peter Drucker) (Pablo Picasso)
“You can’t manage what you don’t measure.”
(Peter Drucker)
“Computers are useless.
They can only give you answers.”
(Pablo Picasso)

4. This Talk
Connect the “big data” challenge to a longer- standing “burden of knowledge” challenge in science and technology
Learn how innovators solve these challenges
Learn how new data sets (yes, big data) have informed the nature of scientific creativity

5. Knowledge and Creativity
“If I have seen further it is by standing on ye sholders of Giants.”
-- Isaac Newton

6. Knowledge in the 17th Century
Harvard University is named after John Harvard,
largely because he gave the new university his (then remarkable) 320 volume library in 1639

7. Knowledge Today
Annual journal Articles Published (thousands)
Publication Year
1960
1970
1980
1990
2000
2010 50
100
200
400
800
Scientists have been facing the problem of “too much information” for a long time…
Annual journal publications worldwide (source: Jones 2011)

8. The Specialization Dimension
“…knowledge has become vastly more profound in every department of science. But the assimilative power of the human intellect is and remains strictly limited. Hence it was inevitable that the activity of the individual investigator should be confined to a smaller and smaller section…”
-- Albert Einstein (1932)

9. How Do People Respond? A Simple Theory (Innovators)
If knowledge accumulates, then training decisions may naturally shift
(1) Extend training
Life-Cycle Changes
(2) Choose narrower expertise
Organizational Changes
Two dimensions of response

10. The Aging of Innovators
“Ordinary Innovation”
Age at first patent is going up
(Jones 2009)
Application Year
Age
1985
1987
1991
1993
1997
1999
30.50
30.8
31.1
31.4
31.7
1989
1995
Trend in age at “first” innovation
“Great Innovation”
Major scientific/technical achievements increasingly rare in early life-cycle
(Jones 2010)
Age
Innovation Potential 10 20 40 50 70 80 .2 .4 .6 30 60 .8
1900 Estimate
2000 Estimate

11. The Team Dimension
“…men begin to know their strength when instead of great numbers doing all the same things, one shall take charge of one thing and another of another”
-- Francis Bacon (1620)

12. The Ubiquitous Rise in Teamwork
Year
Mean-Team Size
1955
1960 .1
1.5 2
2.5 3 4
3.5
4.5
1965
1970
1975
1980
1985
1990
1995
2000
2005
Science & Engineering Papers
Patents
Social Science Papers
Data: Web of Science, 19 million articles (Wuchty et al. 2007)

13. Example The Rise in Team Size
First airplane
Wright brothers
787
30 Different Ph.D. disciplines just to design engines

14. The Team Impact Advantage Today
Mean Citations Received
Probability > 100 citations
Team
Solo
Team/Solo
Science and Engineering
11.95
4.55
2.63
1.21%
0.28%
4.25
Social Sciences
8.74
3.31
2.64
0.59%
0.13%
4.57
Patents
6.66
5.64
1.18
0.025%
0.015%
1.65
Teams have a large and increasing advantage in producing the highest impact ideas
(Source: Jones 2011)

15. This Talk
Connect the “big data” challenge to a longer- standing “burden of knowledge” challenge in science and technology
Learn how innovators solve these challenges
Learn how new data sets (yes, big data) have informed the nature of scientific creativity

16. Creativity as New Combinations
Mendel
Combining peas (literally) to understand genetics
Edison
Light bulb = candle (old) + electricity (new)
Mullis
DNA replication = DNA (new) + enzyme (new)
Mendel’s laws: experimented ; importance of work not recognized until 20th century.
Edison: Called light bulb an “electric candle”. (1879)
Kary Mullis: while driving down the Pacific Coast highway, in 1983.

17. Yet meaningful novelty is hard
The “burden of knowledge” (above) suggests that scientists and inventors become increasingly narrow in their reach
And innovations are often, in part, intentionally conventional
What is the right balance between novelty and conventionality and in what circumstances do scientists achieve it?

18. Using Big Data to Inform Creativity
We study all fields of science, from
Data: The Web of Science, with ~ 20 million scientific articles
Method:
Examine combinations of prior work in each individual paper.
Assess whether these combinations are novel or conventional.
Then ask what types of combinations predict the highest impact science.

19. Probability of a “Home Run” Paper (Paper in top 5% Percentile of all papers)
~ 2x
~ 6x
Application Year

20. Teams and Tail Novelty What about teams as a solution to narrowness?
Teams prove substantially more likely to make novel combinations of prior work.
Teams’ capacity to reach (and comprehend) knowledge across boundaries can help explain why teams are increasingly the source of the highest impact new ideas.
Application Year

21. Final Thoughts
We were drowning in information before there was big data…
Studies of knowledge-intensive areas (science) can help show how to meet this challenge
“Big data” used here to inform the problem of “big data”!
How do we still make sense of things, ask good questions?
Specialization.
How do we bring sufficient expertise to bear?
Teamwork.
Application Year

22. Thank You