Rob Spencer, CHI Collaborative Innovation in Biomedicine ...scaledinnovation.com/innovation/conferences/2010-06-chi.pdf · Bonafides and Context Rob Spencer, CHI Collaborative Innovation

1 Rob Spencer, CHI Collaborative Innovation in Biomedicine, Philadelphia, June 2010


Steve Street, Doug Phillips

Mark Turrell, Tim Woods

Anne Rogers, Kurt Detloff

Jon Bidwell

Howard Smith

Mike Hatrick, Dave Wootten

Employer

Partner

colleagues sharing data

Many Thanks

Outline

Rob Spencer, CHI Collaborative Innovation in Biomedicine, Philadelphia, June 2010 3

• Why do things differently?

• The Challenge Model

• The Long Tail in Collaborative Innovation

• Risk-Management Tactics

Bonafides and Context

Rob Spencer, CHI Collaborative Innovation in Biomedicine, Philadelphia, June 2010 4 4

•  World’s largest pharmaceutical company

•  $7 billion annual R&D

•  Tightly focused, managed research teams

•  Scientist & manager, 29 years in R&D

•  Past 5 years leading innovation initiative

•  Retired, 2nd career developing collaborative intelligence systems

me

Outline


Why do things differently?

You must master things...


In Science Business, Gary Pisano notes that biopharma survival depends on mastery of the

• complexity

• uncertainty

•  speed of change

of the underlying science.

Gary Pisano (2006) Science Business

...that you don’t know inside your company


Pfizer spent more on research in 2007 than any other company in the world.

JAMA, September 21, 2005—Vol 294, No. 11 1333 http://www.nsf.gov/statistics/seind00/access/c2/c2h.htm

Pfizer medical device firms

foundations & charities

rest of world

other government

biotechnology firms

other pharmaceutical

firms

National Institutes of

Health

USA But that represents only

1.7% of the world’s biomedical R+D spending,

1.4% of the world’s biomedical scientists

Outline


The Challenge Model


The “Idea Farm” is an all-company collaborative innovation and problem-solving system.

We ran 30-50 campaigns every year.

This approach is known to be effective and sustainable.

Scaling up open collaboration inside is a perfect prelude to Open Innovation.

Pfizer experience


? ?

Diverge-Converge

The diverge-converge model is centuries old, proven effective, and scales perfectly with electronic media.

The classic example is the Longitude Act of 1714; see Dava Sobel’s book Longitude


Case Studies by Scale and Type

social problem-solving

meeting and decision support

Continuous Improvement

outside supplier & partner challenges

portfolios & priorities : Speed Dates

portfolios & priorities : large challenges

difficult scientific challenges

interactive communications

Outline


The Long Tail

The Long Tail


There is a Long Tail of large scale collaboration behavior.

Chris Anderson’s book tells the story for retail books and music. His observations, conclusions, and advice apply directly to collaborative innovation.

It matters because the results are non-obvious, universal, and now predictable.

Classic vs Long Tail Statistics


What’s the average height of people?

What’s the average number of ideas from

our employees?

ideas per person

how

ofte

n it

occu

rs

•  It’s nothing like a bell curve.

•  “Average” makes no sense.

•  Some people enter no ideas, some enter hundreds. The range is huge.

inches of height per person

how

ofte

n it

occu

rs

•  It’s a bell curve.

•  “Average” is a useful description.

•  The range of values is only a factor of 2.

Log-log graphs reveal the tail


linear graph

Log-log plots show the tail clearly.

A straight line on a log-log graph has the form y = Cx-b , a power law.

I graph these like Zipf, with the axes are flipped vs the Pareto convention. Slopes here = b = 1/(α-1)

log-log

Pfizer Idea Farm 2006-2009 20,000 entries from 4000 authors in >200 campaigns

Long Tails are everywhere


•  book and music sales

• word usage

•  internet hits

•  salaries

•  avalanches

• wildfires

M. E. J. Newman (2006) Power laws, Pareto distributions and Zipf’s law, http://arxiv.org/abs/cond-mat/0412004v3

Many Companies, One Phenomenon


Each dataset is a single campaign at a different company.

Lines all have α=3.0


These are huge datasets over 3-4 years and thousands of people each.

These very different businesses show identical behavior patterns.

Cargill and Pfizer

Voluntary External Contributions


An external open-transom system has exactly the same pattern of contributions.

Data from several years of Pfizer’s open contribution system, courtesy of Doug Phillips

Long Tails in Public Forums


M. E. J. Newman, Power laws, Pareto distributions and Zipf’s law, 2004

D. Wilkinson, Strong regularities in online peer production, in Proceedings of the 2008 ACM Conference on E-Commerce, Chicago, IL, July 2008

Long tails (power laws) are the norm for large scale voluntary contributions.

Wikipedia and Digg

The Value of a Contribution


The value* of an entry from a top contributor is the same as that from a rare contributor.

The huge number of singleton authors puts their value far ahead of the top contributors.

* Value was measured for multiple large internal challenges, assigned by rankings of the sponsoring business unit.

Lesson #1


Voluntary external behavior is different from structured internal behavior.

Internal systems are typically push, external are pull: this is a huge mindset change for motivation and management.

John Seely Brown & John Hagel III, Push Pull -- The Next Frontier of Innovation

Lesson #2


Most of your contributions and value come from the occasional contributors.

from authors of 1 idea

of 2 ideas

of 3

Internal contribution statistics are gaussian, external are power law.

Do not bias your system by quantity; you may exclude your best contributors.

Use a structured, scalable approach to evaluating the input.

Dirty Secrets of 5 Star Voting


•  it’s biased

•  it’s compressed

•  followers drive to extremes

•  don’t make it too easy

How public opinion forms, Fang Wu and Bernardo A. Huberman, Social Computing Lab, HP Labs, Palo Alto, CA 94304, http://www.hpl.hp.com/research/scl/papers/howopinions/wine.pdf

Is the crowd’s wisdom biased? A quantitative assessment of three online communities, Vassilis Kostakos, at http://arxiv.org/pdf/0909.0237

“...when people observe previous opinions ... they tend to follow the trend. As a result ... extreme views get reinforced and become increasingly more extreme.

“... where expressing a view is costly, like when writing a book review...people will tend to ... offset the current view by presenting a differing one.”

“This analysis has shown that the wisdom of the crowd is indeed biased.”

Analysis of Amazon: 380,000 reviews of 21,000 books by 134,000 people

Amazon average is 4.4 out of 5

Lesson #3

Rob Spencer, CHI Collaborative Innovation in Biomedicine, Philadelphia, June 2010 25 sources: Twitter: Heil and Piskorski, Harvard Business School October 2009; Digg, Wikipedia: Wilkinson, Hewlett-Packard labs; other, this work

What percent of people put in 80% of the content? 80%

Twitter tweets 5%

Digg votes

9%

comments, star votes

21- 28%

Wikipedia edits

46%

corporate ideas

58- 68%

info

rmat

ion

cont

ent

The simpler the task, the less representative the results. Be very suspicious of mass ratings.

Outline


Risk Management Tactics in Open

Innovation

Ask Valuable but Low-Risk Questions


•  Which of our policies and procedures makes your CRO task onerous?

•  What are the bottlenecks in regulatory document preparation?

•  Can you make this molecule for under $200/kilo?

•  We have a new drug for diabetes in Phase III. What could you do with it in other disease areas?

Ask for help in finding problems, not solutions.

Start with optimization, not new opportunities.

Offer an opportunity you wouldn’t exploit anyway.

examples

Ask Different Questions


inside supply chain & partners Open Innovation

Approach Open Innovation in Stages


A staged approach prepares for, and minimizes, IP risk when going outside

project team

whole company

partners, suppliers rest of world

know

ledg

e

time

risk

Good Reading


•  John Seely Brown & John Hagel III, Push Pull -- The Next Frontier of Innovation, McKinsey Quarterly 2005 no 3, 82-91.

•  John Hagel & John Seely Brown, From Push to Pull - Emerging Models for Mobilizing Resources, working paper, Oct 2005.

•  Gary Pisano, Science Business, 2006, HBR Press

•  Gary Hamel, The Future of Management, 2007

•  Thomas Friedman, The World is Flat, 2006

•  Managing Uncertainty, Harvard Business Review

•  Strategy Under Uncertainty, HBR OnPoint reprint

•  Peter Senge, The Fifth Discipline

Contact information

Robin W. Spencer [email protected] 860-326-8077


Questions ?

Documents

Rob Spencer, CHI Collaborative Innovation in Biomedicine ...scaledinnovation.com/innovation/conferences/2010-06-chi.pdf · Bonafides and Context Rob Spencer, CHI Collaborative Innovation