U. S. Chamber of Commerce blog posts with tips for generating innovation -- Innovation & Data For Good -- by Tim Maurer

1. Data for Good – Looking for Innovation in All the
Wrong Places
Tim Maurer, March 27, 2014
You could say that innovating using Big Data requires looking for love in all the wrong places—
and when you find that something to love, persevering through thick and thin to make it take
hold for everyone’s mutual benefit.
Alfred Sommer is an eye doctor who, in his relentless review of research datasets, came across
critical information that led him to forge a low-cost, highly efficacious, life-saving innovation in
healthcare. Sommer’s simple medical intervention has likely saved millions of children from
premature death. Of data, he says:
“You have to know your data, you have to smell it, you have to be in it. If you're not living inside
the data you are going to miss the most interesting things, because the most interesting things
are not going to be the questions you originally proposed; the interesting things are going to be
questions you hadn't thought about."
Sommer’s data-driven discovery proved that vitamin A deficiency not only resulted
in juvenile night blindness but also in death. Furthermore, he proved that a two-cent oral
application of vitamin A could address the issue and prevent many deaths.
An affiliate of the U. S. Chamber Of Commerce
KEY INSIGHTS FROM THIS STORY:
Data should be relentlessly probed to answer not just
questions first proposed, but also questions not considered.
Multiple corporations are prisoners of deeply ingrained
assumptions, information filters, and problem-solving
strategies that comprise their original world views, turning the
very solutions that made them great into straitjackets.
Innovators must examine and harness data across and in
support of multiple dimensions of innovation - - spanning
product and service offerings, business models, delivery
channels, customer engagement provisions, technology,
convergences, partnerships, sourcing and financial strategies.

2. Sommer’s discovery and innovation came in 1982, well before technology-enabled “Big Data.”
He used a hand-held calculator to painstakingly pour through multiple levels of medical data to
arrive at a surprising insight with huge implications.
Discovering that death could result from simple vitamin A deficiency was seen as a phenomenal
breakthrough, particularly coming from an eye doctor. Frankly, he was from an unlikely
place within the medical field for his discovery to be readily accepted.
“Nobody was willing to accept that two cents worth of vitamin A was going to reduce childhood
mortality by a third or half, let alone when that information was coming from an
ophthalmologist,” said Sommer. “A lot of people had spent their lives studying the complex
amalgam of elements leading to childhood deaths…It didn't sit well. What was most frustrating
of all was when you present the hard data and people just say they don't believe it.”
Sommer overcame the issue of disbelief and lack of acceptance by burying critics in data; he
established further studies all over the world to prove his finding was accurate. The World
Bank and Copenhagen Consensus have since listed Sommer’s vitamin A
supplementation as one of the most cost-effective health interventions in the world.
This case study illustrates that meaningful innovation often requires looking deeply into things
outside the norm or in places that nobody else has examined. It shows the value that can come
from focusing on what might at first appear to be impossible, or even prone to being
discredited—but then having the fortitude to look anyway, the perseverance to keep delving into
the issue and reaching for the solution. Indeed, successful innovation starts with the relentless
pursuit of insights, using disparate data sources from across a range of gathering venues and
perspectives. It also requires examining data for best practices across people, processes,
technology, business models, funding—and, ideally, in the pursuit of purpose as
well. Sommer’s work showed the world-changing good that can come from data-driven
innovation.
Unlike when Sommer conducted his groundbreaking work, the advanced data analytics of today
make combing through print outs with calculators obsolete. (Phew.) But given our increasingly
complex, fast-paced world in which there’s so much product and service displacement
and still so many unmet needs, the same relentless pursuit of data is recognized as even
more critical to innovation—and to a company’s survival—than ever before.
Data analytics is seen more and more as the one strategy that can help companies
succeed. GE’s 2013 Global Innovation Barometer affirmed that “63% of senior executives

3. involved in innovation report their firm is developing the ability to use the potential of ‘Big Data’
for Innovation.”
Affirming this, CIOs attending the 2014 Wall Street Journal CIO Network Conference also
indicated theirtop focus will be on Business Intelligence and Analytics and on building a data-
driven culture—with data that is easily accessible and consumable.
In his foundational 2007 innovation discourse, “Sensing, Seizing and Transforming,” David
J. Teece at the University of California-Berkeley’s Institute of Management, Innovation and
Organization, noted with concern that multiple corporations “became prisoners of the deeply
ingrained assumptions, information filters, and problem solving strategies that made up their
world views, turning the solutions that once made them great into strategic straitjackets.”
Teece said that identifying and seizing opportunities means businesses must delve into the rich
data coming from local and distant markets and through myriad technologies. He wrote:
“This activity not only involves investment in research activity and the probing and re-probing of
customer needs and technological possibilities; it also involves understanding latent demand,
the structural evolution of industries and markets, and likely supplier and competitor
responses…The systematic nature of many innovations compounds the need for external
search.”
Teece and other experts concur that innovation success entails scanning customer
demographic, usage and purchase data; unearthing market perceptions; exploring entire
ecosystems; discerning unmet needs through ethnographic and qualitative or quantitative
research; conducting assessments of alternative ways for customers to meet needs;
considering convergent industry developments, technology developments, regulatory policies;
and much more.
Importantly, successful innovators need to examine and harness data across and in support of
multiple dimensions of innovation—well beyond product innovation itself—that can span
product and service offerings, business models, delivery channel solutions, customer
engagement provisions, strategic partnerships and sourcing, and financial mechanisms.
Examples of this holistic scanning and multi-dimentional innovation approach can be found in
the work Deloitte Consulting, LLC is doing with clients, including biopharma companies.

4. Deloitte provides innovation landscape research and analytics that incorporates a
broad examination of emerging business models and processes, converging technologies and
trends, and collaboration with an array of entities.
Deloitte’s proprietary discipline for arriving at innovation breakthroughs,“10 Types of
Innovation,” has been proven to lift innovation success many fold. One such holistic innovation
is their work with Pfizer and Keas, developing online healthcare plans that guide patients to
adopt healthier lifestyles. This innovation incorporated perspectives across the entire “system of
care” and social institutions, such as friends and families, churches, social clubs, and
workplaces.
This dedicated, expansive search through massive amounts of data can produce
and efficaciously deliver something distinctly valuable that affords a sustainable advantage. But
technology and data scanning alone won’t do it. There’s much more in the data to be
discovered than meets the eye.
Going beyond what’s readily apparent and digging deeper and sifting for gold nuggets is the
key. Fortunately, today’s businesses have more resources available for insightful data gathering
and innovation optimization than ever before, a topic described in depth in the next installment
of the Data for Good series.

5. Data for Good – Towards Purpose-Driven
Innovation
By Tim Maurer (Author’s note: this blog was written before the Business & Sustainable Development
Commission report indicated the UN SDGs, empowering the bottom of the economic pyramid, could
yield as much as $36 trillion+ in growth, and 380 million jobs/purchasing power.)
The road to innovation is littered with obstacles, and continuing on the path takes more
than just a good idea; it demands perseverance and passion. Yet, from what does this
drive stem?
Looking to examples where data-based insights led to breakthrough innovations (such as
Dr. Jim Olson’s “Tumor Paint” for brain surgery or Dr. Alfred Sommer’s low-cost Vitamin A
therapy), what surfaces is the concept that pursuing “purposeful” innovation can motivate
people in persevering. Indeed, often hidden in the successful pursuit of innovation within
“game-changing” organizations is the concept of “purpose.”
Game-changing organizations are “purpose-driven, performance-oriented and principles-
led,” according to a recent Harvard Business Review (HBR) article, “Building A Game-
Changing Talent Strategy.” Authors Douglas Ready, Linda Hill and Robert Thomas write
that “recent research makes clear the importance of creating companies that are guided
by a collective sense of purpose.”
The HBR article highlights the Chinese energy company Envision, which has doubled
revenues every year since its founding in 2007. The founders, Lei Zhang and Jerry Luo,
created the company with the vision to “help solve the challenges of a sustainable future
for mankind.”
KEY INSIGHTS FROM THIS STORY:
Innovating with purpose could help organizations become
“game changers.”
The fastest growing new markets and opportunities could be
found among the billions of people living on less than $2 per
day—at the “bottom of the [economic} pyramid.”
Three key approaches can help deliver profits while transforming
the lives of millions of people globally: 1) bundling products;
2) offering enabling services; 3) cultivating customer peer groups
Perhaps we should invest innovation resources on innovating
innovation towards solving the world’s most troubling issues.
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6. They reportedly foster open innovation and cross-cultural collaboration, and they measure
key developmental “accelerators” of “wisdom, will and love.” Luo said: “Envision is here to
help people achieve their ambitions and to help improve the world.”
In his 2013 book, Innovation Engine, the late innovation consultant Jatin Desai
documented the importance of “intrapreneurs.” These “mission” or “purpose”-focused
individuals are key to a corporation’s overall innovation success. Desai cited excerpts from
Gifford Pinchot III’s seminal book, Intrapreneuring: Why You Don't Have to Leave the
Corporation to Become an Entrepreneur, writing that intrapreneurs establish new
products, processes or services by combining the talents of technologists and marketers.
He wrote:
“Intrapreneurs are motivated to solve ambitious challenges. The best Intrapreneurs are
not in it for themselves. They are with you (corporations) because they can see a faster
path for bringing their dreams to life…Intraprenuers are not just seeing things
differently but finding new insights that only an idea hunter can discover.”
Desai also documented that intrapreneurs are experts in managing the “pivoting” that is
key to surviving in this era of rapid innovation and competitive displacements. For Desai,
pivoting means making “a courageous and significant shift from the current course of
action, a shift most people would never make.”
Given these and other insights presented in this series, it seems innovating with purpose
could help enable more organizations to become “game changers,” motivate even more
intrapreneurs, and ultimately yield even more successful innovations. Perhaps we should
invest some of our data-gathering and innovation resources on innovating innovation itself
towards a more purpose-driven end. Perhaps resources should be spent in not just
analyzing how to better innovate but also in assessing on what to spend our innovation
energies and resources. Perhaps we need to deploy our exhaustive data analysis in
identifying and solving some of the world’s most troubling issues to afford those crucial
intrapreneurs the large challenges they seek to solve.

7. Opportunity at the Bottom of the Pyramid
There’s another well-articulated data point that asserts the potential value in innovating
around purpose and finding and supporting people who want to innovate based on
purpose.
The late economist C.K. Prahalad proposed and substantiated that there’s a vast market
opportunity (perhaps $5 trillion). Prahalad and Stuart Hart fostered the concept of The
Fortune at the Bottom of the Pyramid in the business journal Strategy+Business. Prahalad
later wrote a book with the same title, articulating new business models and strategies
targeted at providing goods and services to the poorest people in the world.
Prahalad proclaimed that the fastest growing new markets and entrepreneurial
opportunities would be found among the billions of people living on less than $1 or $2 per
day—those as the “bottom of the [economic pyramid.” Affirming this, Bill Gates noted the
proposition "offers an intriguing blueprint for how to fight poverty with profitability."
Prahalad advocated that, rather than Multinational Corporations (MNCs) continuing to
operate in their traditional business models, markets, and channels, if MNCs were to align
with Non-Government Organizations (NGOs) and the Bottom of Pyramid (BOP)
community, MNCs could profit from a lucrative opportunity. And he used significant data
to back up that claim when others doubted the proposition.
Since Prahalad’s ground-breaking encouragement to focus on the BOP, however, there’s
been some discouraging experience suggesting that profitably servicing the BOP market is
indeed very difficult and, in fact, without proper discipline, may well be too difficult.
But Erik Simanis, managing director of Market Creation Strategies at the Center for
Sustainable Enterprise at Cornell University’s Johnson School of Management, is one
innovation leader who has successfully refuted claims that BOP cannot be managed
profitably. Based on his insights in the BOP arena, the merits of focusing on BOP may well
be worth examining once again in the name of both purpose and profit.
In a 2012 Harvard Business Review article, Simanis shows that purposeful, profitable
business can be done based on his experience leading business opportunities in Africa,
India, and other emerging economies. Simanis has demonstrated how to build a margin-
boosting platform to solve the cost problems in bringing critical products and services to
very poor markets.

8. After articulating many of the challenges and frustrations (and even dismal results) MNCs
have experienced in BOP markets, Simanis illustrates that companies can be successful if
they can increase gross margins well-above company averages by lowering variable costs,
by increasing pricing per unit, and by raising the value of a single transaction.
He also outlines three key strategic approaches (e.g., bundling products, offering enabling
services and cultivating customer peer groups) to enable profit while transforming the
lives of millions of people globally. His overall views may be worth incorporating into an
innovation strategy.
Given the recognized role of purpose in motivating innovation, organizations may do well
to focus on solving significant BOP or other purposeful challenges as at least one element
in a portfolio of product innovation—a portfolio that can and should range from low risk,
iterative product functionality-based innovation to higher-risk, truly disruptive and
purposeful innovation. Such a pursuit of purposeful, high-impact innovations can be as a
leader and orchestrator in a BOP or purposeful process or it can be as a supporting
participant in a collaborative BOP or other purposeful initiative.
Fortunately, several innovation consultants are already aware of the value in purposeful
and BOP-oriented opportunities and have even engaged in enabling purposeful initiatives.
Many people have the passion to see these types of opportunities to fruition, and we now
have the Big Data strategies and resources necessary to approach this systematically for
everyone to benefit.
Bottom line – with all our access to data, with our collaboration tools, and with
longitudinal data on successful innovation approaches and impact, we now have the
opportunity to innovate like never before, wherever we choose to innovate. We have the
potential to make a greater impact domestically and globally in quality of life, in economic
development, in purpose, in profit, and more. Given a global economy fraught with
financial stress and significant areas of weakness, if we could work together with purpose,
passion and perseverance to use data for good, we could perhaps see fortunes rise for
everyone.

9. Wonder, Junk and Innovation
By Tim Maurer
Thomas A. Edison once opined, “To invent, you need a good imagination and a pile of junk.”
Indeed, there’s value in wading through junk – or through venues historically viewed as all
the “wrong places” – to realize breakthrough insights and innovations.
But when it comes to innovation in genomics, a “switch” in orientation toward a quote from
Socrates might better represent the opportunities: "Wisdom begins in wonder."
Significant innovations are emerging out of global, big-data enabled DNA research
collaboration. In 2012, the National Human Genome Research Institute announced the
results of the Encyclopedia of DNA Elements (ENCODE), a five-year international study of
the regulation and organization of the human genome.
The goal was to build an exhaustive list of functional elements in the human genome, and to
delineate the regulatory elements that control cells and circumstances in which a gene is
active. The analysis was daunting, involving 442 consortium members, 32 research institutes
and 1650 individual experiences. The researchers generated 15 trillion bytes of raw data.
KEY INSIGHTS FROM THIS STORY:
Project ENCODE (Encyclopedia of DNA Elements) involved a new people, process and
technology framework for massive, collaborative research and efficacious
dissemination of findings for rapid breakthrough innovations. When the National
Human Genome Research Institute announced results of ENCODE -- a 5-year study of
regulation and organization of the human genome, conducted by 442 global
consortium members, 32 research institutes and 1650 individual experiences which
generated 15 trillion bytes of raw data – it both set in motion future innovations and
defined new ways of working toward breakthrough innovations.
Before the ENCODE study, the vast stretches of DNA between our approximately
20,000 protein-coding genes (more than 98% of the genetic sequence inside of our
cells) was written off as junk DNA elements. It was “Big Data” that helped reveal that
the components between the genes were not junk at all. Now, future opportunities
are wide open to discovery, and resulting innovations are coming fast.
ENCODE innovated R&D itself, redefining how people work on massive research and
applications. All data generated are rapidly released into public databases, radically
changing the research publishing model. Rather than publishing papers, ENCODE
enables free access to collaborative “threads” via its vast analytics portal – all so
enabling, they change what's possible for the scientific community.
With scientists worldwide pitching in on ENCODE, there was no guarantee every
scientist would get credit. Scientists knew contributions could get lost in the
collaboration to yield outcomes, yet, they provided data for public (vs. personal) good.

10. The results specifically refuted the prevalent scientific belief of the time asserting that all
but a small percentage of our DNA is “junk.” For years before the ENCODE study, the vast
stretches of DNA between our approximately 20,000 protein-coding genes (more than 98%
of the genetic sequence inside of our cells) was written off as junk DNA.
It was “Big Data” that helped reveal the components between the genes were not junk at
all. Importantly, had this widely-held belief not been refuted by Project ENCODE and
consigned to the history books, the world would be missing out on some significant medical
and other contributions. Now, future opportunities are wide open to discovery, and
resulting innovations are coming fast.
Project ENCODE involved deploying a new people, process and technology framework for
massive, collaborative research and for affecting the efficacious dissemination of findings to
rapidly yield breakthrough innovations.
One key ENCODE finding has truly been a watershed development: those elements of DNA
that are referred to as genes are but a very small piece of what makes our cells and our
bodies work. In contrast, what had been hidden and became so valuable after all the
analysis was the extensive presence of critical “switches” within DNA. The resulting
biomedical approaches and technologies owing to this discovery promise vast societal
impact.
The breakthrough was described in a cancerfocus.net forum denoting the practical
applications derived from ENCODE. From an applied science perspective, most of the
changes to cells that affect cancer don't occur in our genes but occur within the 40 million
different “switches” that control the genes, switching them on and off in complicated and
nuanced ways.
Researchers have also linked gene switches to an array of human diseases, such as multiple
sclerosis, lupus, rheumatoid arthritis, Crohn’s disease, and celiac disease.
New innovation-enabling approaches include catalyzing basic science studies to identify the
genetic basis of complex diseases, such as diabetes, cardiovascular disease, and neurological
disorders. This will in turn result in advancing other innovations, such as enhanced
biopharmaceutical and agricultural production.

11. Indeed, recent genome modifications have been used in applications as diverse as:
correcting mutations that cause genetic disease and inhibiting HIV infection of human cells;
engineering cell lines to produce biopharmaceuticals; and even generating pesticide-
resistant crops.
A Collaborative Approach to Mega-Data
Beyond breakthrough findings, ENCODE also innovated the process for R&D itself. ENCODE
redefined how people worked together on massive research and applications. Pardis Sabeti,
an assistant professor at Harvard University, said, "You need the large projects that really
galvanize effort [and] get people working with each other across groups to create these
resources that would not be possible in any one lab alone."
A fundamental aspect of ENCODE, for example, was that all data generated has been and
will continue to be rapidly released into public databases. This has radically changed the
research publishing model. Rather than just publishing papers, ENCODE enables access to
collaborative “threads” (like the Nature ENCODE Explorer) and wiki management. ENCODE
outputs include a vast analytics portal, 741 Wiki collaborative-content pages, threads and
more. Today, ENCODE results can be freely accessed by anyone on the Internet via
ENCODE’s portal, or at the University of California, Santa Cruz Genome Browser, the
National Center for Biotechnology Information, and the European Bioinformatics Institute.
A recent genomeweb.com article looked at the success of the Human Genome Project
overall, including ENCODE’s mega-scale approach. It reviewed a debate in the research
community about balancing funding for consortium programs with individual grants. The
article noted, “The real advantage of these large-scale programs lies in the databases and
other infrastructure they generate. Done properly, these resources are so enabling that they
can change what's possible for the rest of the scientific community.”

12. Beyond simply fostering large-scale efforts that can yield vast impacts, ENCODE also
suggests that purpose and passion might even trump prestige, power and profit in
understanding what truly drives breakthrough innovation.
With groups of scientists worldwide pitching in on ENCODE, there was no guarantee that
every scientist would get credit for his or her work. People recognized that even truly great
contributions could get lost in the collaborative work producing an outcome. Yet, they
persevered, using data for public (rather than personal) good.
Matthew Meyerson, an associate professor at Dana-Farber Cancer Institute and member of
The Cancer Genome Atlas, said, "To do this, I think you just have to say, 'I'm going to go
ahead and do this because it interests me, and I think the results are going to be important
and I'm not going to worry too much about its impact on my career.'"
While the yield from ENCODE is enormous and growing, perhaps the most valuable
outcome is the realization that there is a new way of innovating through harnessing really
big data that sets the benchmark and lays the foundation for rapid global impact.
Given the impacts that we’re already beginning to experience from Project ENCODE, we
should establish a new model of innovation management to which we aspire.
As with ENCODE, the use of Big Data, generated by substantial collaborations, can create
significant impacts. Through this approach, we can drive purposeful and passionate
innovation planning, funding and operations.

13. Data for Good – Innovating with Passion and
Dogged Determination
By Tim Maurer
All the excitement over the age of “Big Data” sometimes seems to champion numbers
and raw information as the source of world-changing innovations. The thing is, data on
its own does nothing. It is the people who take an insight gleaned through data and run
with it through all the frustrating hurdles of the innovation process that turn a sound
insight into a viable, groundbreaking application.
Innovation success requires hiring and nurturing skilled people who can access and
mine data for gems; who can collaborate with others for mutual benefit; and who can
muster the spark of energy, the passion, and the fortitude to drive the process from
data to insights and invention to a systemic innovation or business model shift that
takes hold in affecting a true, breakthrough change. This despite—and often
persevering through—the inertia that will likely need to be overcome. Bleeding-edge
stuff.
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KEY INSIGHTS FROM THIS STORY:
Multiple people collaborating in directed data pursuit
and analysis is helpful to discovery
Pursuing an idea to funding takes more than data and
substantiation – it takes perseverance
To covert ideas to inventions and innovations that take
hold requires working with networks -- people with
organizational or financial equity. Collaboration software
can help, too.
“Mutual helping” should be encouraged -- lending
perspective, experience, and execution to improve the
quality and execution of ideas, and matching help
seekers with helpers. It also means encouraging
reciprocity, including through recognition of helpers.
In collaboration, intellectual property (IP), trust building
and talent poaching, must be addressed.

14. We can all be inspired by exemplary innovators who not only illustrate the art of mining
data for innovation, but also model how to push the envelope in making an impact
through research-based innovation.
One exciting biomedical innovator to watch, Dr. Jim Olson, speaks on the importance of
finding the spark of brilliance—like that brilliance in the center of a violet—and of
having the passion that’s represented in a violet’s purple petals.
Olson is a surgeon specializing in children’s brain cancer treatment. He created Tumor
Paint from scorpion venom to better differentiate healthy brain cells from tumorous
cells. This helps surgeons avoid the typical collateral damage that often comes from
removing healthy cells during brain surgery due to lack of distinction between the
healthy and cancerous cells.
When asked what gave him the idea to work with scorpion venom, Olson cited the
data-related research work that a talented neurosurgery resident contributed. Patrick
Gabikin had come into Olson’s lab to perform research. Olson guided Patrick Gabikin to
dig into Big Data, to review all the scientific literature and computer databases, adding
that other scientists had examined differences between brain tumors and normal
brains for years and had published their information—but typically only in the form of
lists.
After six weeks of digging and presenting various findings to Olson, Olson saw the basis
for a solution that seemed promising. Gabikin had found articles where researchers
were studying chlorotoxin, which is created by scorpions.
This ultimately became the targeting agent in Olson’s Tumor Paint. Olson would soon
attach a fluorescent molecule to it, grow a human brain tumor in a mouse, and inject
the tumor paint molecule in the blood stream to determine if the tumor would glow.
An hour and a half after injecting the paint, the tumor was indeed glowing, and Olson
was literally jumping for joy.
Still, to grant-funding bodies and others in the field, Olson’s innovation initially seemed
far too outlandish and improbable to fund or support. So, after his moment of
brilliance, Olson had to muster the passion and perseverance to not only prove his
theory, but also pursue and secure self-funding sources to make his seemingly
inconceivable discovery a viable part of surgery. Passion and perseverance was the key.
Fortunately, through innovativeness and persevering in fundraising, Olson succeeded in
raising the capital.

15. In part to encourage and engage others, Olson has named his latest and perhaps most
exciting initiative, Project Violet, after a patient who had suffered from incurable brain
cancer and who, after she died, had arranged for her brain to be donated for science.
Project Violet will use crowd funding to secure the help of the community to develop
new class anti-cancer compounds derived from scaffolds of nature—chemical
templates from organisms such as violets, scorpions and sunflowers.
Olson’s ultimate goal is to develop treatments that are highly targeted to kill cancer
while sparing patients from the toxic side effects of chemotherapy, including nausea
and hair loss. His team is now pursuing the development of a fundamentally new class
of anti-cancer compounds: molecules called “optides” that specifically attack cancerous
cells while leaving healthy cells untouched and offer the potential to improve on
current chemotherapies.
Collaborating for Innovation
As Olson and others like him are uncovering data-based breakthroughs, we can see that
innovation is not a solitary endeavor. Working together, we have the potential to
achieve much more than we could on our own. In short, we need to up our collective
game in the area of collaboration.
In managing innovation through impeding inertia and barriers, it can be beneficial to
team people who can identify a spark of brilliance together with established players
across enterprises and industry ecosystems who have the equity, budgets and
networks needed to affect institutional change. Identifying and marshalling multiple
parties with the propensity to collaborate—as well as harvesting collaboration
processes and technologies—is becoming more and more essential for success.
In Olson’s case, the key to taking innovative insights to fruition went well beyond data
collection and analytics and involved collaboration and continual, concerted
perseverance. Olson formed a team and is reaching across disciplines, and the team is
not just working on developing improvements in brain tumor surgeries or finding a cure
for a particular disease. And fostering even greater collaboration, they’re also creating
a platform that can be used by thousands of scientists to address many diseases like
Alzheimer’s disease, autism, and diseases that affect developing nations.

16. According to the GE Global Innovation Barometer, 87% of senior executives think their
company would innovate better through partnering than by working on their own, and
67% have “developed a new product, improved a product or created a new business
model through collaboration with another company.”
Fostering collaborations within companies and across disparate units and departments
is also critical. Noted innovation expert, IDEO, was highlighted recently in the Harvard
Business Review for its documentation of “mutual helping” as an essential dynamic
within a truly successful innovation culture.
Beyond workload sharing, “mutual helping” is the process of lending perspective,
experience, and execution to improve the quality and execution of ideas. It’s the
matching of help seekers with the helpers themselves.
Mutual helping also means encouraging reciprocity, including through the recognition
of the helpers. It also entails working to eliminate the perception that seeking help is a
sign of weakness. According to IDEO, successful mutual helping entails fostering a
collaborative innovation environment comprised of three measurable indicators:
competence; trust; and accessibility.
Unfortunately, today, when it comes to collaboration, there appears to be significant
room for improvement. In assessing their collaborative capabilities, a majority of WSJ
CIO Network Conference participants (51%) would only give their organizations a “C” or
“D” grade for collaboration. There are also concerns over intellectual property (IP), as
well as trust and talent poaching, that need to be addressed.
In any innovative endeavor, motivating passion is essential for success, though the
sources from which this relentless determination can arise are often unique to the
innovator. As discussed in the next installment in this series, maintaining a focus on
“purpose” throughout the innovation process is what can drive breakthrough
discoveries.
For Olson, his deceased patient, Violet, has become a catalyst for purpose and
innovation. May we all find our Violets, seizing the moment when inspiration blossoms
from the fertile soil of disparate data, and applying the passion and perseverance
needed to see a discovery through to fruition. This is precisely what is meant by data
for good.

17. A Wiki Revolution in Innovation and Big Data
By Tim Maurer
When Wikipedia began in 2001, it capitalized on the Internet Age’s collaborative
potential. Wikipedia’s open-source approach to sharing and spreading data (encyclopedic
content) has proven so successful, the prefix “wiki” has become a prevalent term in all
things online. This is valuable not just for sharing information; it can be a catalyst for
innovation.
Innovation consultant Rod Collins, of Optimity Advisors, has articulated a key facet of a
new type of approach to fostering innovation and collaboration, what he calls “Wiki
Management” (which is also the title of his 2013 book). Within Wiki Management is a
new philosophy and practice that can drive incredible connectivity and collaborative work
across multiple disciplines. Collins has defined how this can help organizations affect and
harvest collaboration and data.
“The wiki world is a hyper-connected global network where people can work directly and
effectively with each other without having to go through a central organization,” said
Collins. This includes “the ability to process the abundance of human intelligence
distributed throughout their organizations.”
Collins argues for a replacement of command and control management with new
“container-based” facilitation models for driving innovation in a hyper-connected world.
Among other things, Collins articulates how Wiki Management exploits the “container”
that fosters collaboration to improve work processes, output and impact.
An affiliate of the U. S. Chamber Of Commerce
KEY INSIGHTS FROM THIS STORY:
- “Wiki or Container Management” is a term for driving
connectivity and collaboration across multiple disciplines. It can
help organizations harvest the abundance of human intelligence
distributed throughout their organizations and networks.”
- W. M. tackles 3 aspects of innovation: 1.) Accelerating Change;
2.) Increasing Complexity of Issues; 3.) Ubiquitous Connectivity.
- W. M. exploits a “container” system that fosters collaboration to
improve work processes, output and impact.
· Leverage collective intelligence, integrating diverse points of view
· Achieving shared and actionable understanding of key drivers
· Determining what’s key to delighting customers, and managing to this
· Developing and managing measurements to hold people accountable
· Transitioning leaders from the role of “boss” to that of facilitator.

18. In this case, container refers to the development of technology spaces for content. As
Collins describes it:
“Before the mid-1990s, writing the content of computer programs involved far more
work than necessary because software specialists didn't have a practical way to
share their methods. In early 1995, Ward Cunningham came up with an innovative
solution for how programmers could share their common staples when he launched
the WikiWikiWeb site. In creating the “wiki,” as it came to be known among its early
aficionados, Cunningham constructed a container in which programmers could
effectively self-organize their work. Open source leaders and Agile managers don't
manage content—they manage the container. The container is the virtual or the
physical space in which people work together.”
Overall, Wiki Management tackles three fundamental aspects of innovation: 1.)
Accelerating Change; 2.) Increasing Complexity of Issues; and 3.) Ubiquitous
Connectivity. Wiki Management describes how the power of networks is dramatically
reshaping both the work we do and the way we work. It establishes keys to harnessing
this, including (but not limited to):
· Leveraging collective intelligence and effectively integrating diverse points of view
· Achieving a shared and actionable understanding of the key drivers of success,
including the iterative measures and outcomes that drive the future
· Determining what’s important to delighting customers, and manage to this
· Developing and managing actionable measurements to hold people accountable,
including to their peers
· Transitioning leaders from the role of “boss” to that of facilitator.
As an example, Collins contrasts the development of the original online encyclopedia,
Nupedia, with the open-source Wikipedia. He frames the staying power, currency and
ubiquitous value of Wikipedia to make the case for why open source is more valuable.
Nupedia started back in 2000, but the concept to create an online publication was
impeded by its conventional seven-step, academician-oriented, hierarchical editorial
review process that only produced 25 reference articles after the initial development
year.
So the founders abandoned the process, replaced it with the Wiki container process,
and dubbed it Wikipedia, which enabled both contributions and edits at a far greater
and sustainable rate from a mass of contributors.

19. “The meteoric growth of Wikipedia is well documented, and most of us have never
heard of Nupedia. While the experts continue to debate the quality of the online
encyclopedia, all of us are amazed that the world's largest and most widely used
reference work continues to be built by a self-organized collaboration of the masses,”
notes Collins.
Through this example, Collins affirms the need for opening eyes to new disruptive
business models (versus simply improving performance on an old model) and
particularly illustrates the value of the container.

20. Can Creativity Be Planned?
By Tim Maurer
In an earlier post, I wrote about Project ENCODE, the massive, global research into the
human genome, including the functionality of hidden regulatory switches within our
DNA. This was one of the greatest examples of “Data For Good,” and it involved
significant collaboration, tremendous computing power, and new ways of gathering
and presenting findings. ENCODE redefined how people work together on massive
research and applications. A fundamental aspect of the project, for example, was that
all data is rapidly released into public databases, which can foster connections and new
insights.
In Wiki Management, Rod Collins, of Optimity Advisors cites another, similar global
research project comprised of open source technology, mass collaboration, multiple-
centers, and the best scientists from across 11 nations. It was the 2003 effort to rapidly
identify and help address the SARS (Severe Acute Respiratory System) virus.
This process ultimately averted a global pandemic, and it’s similar to the collaboration
and container management processes pursued in ENCODE. Indeed, the SARS effort
involved continually passing data back and forth—including working through informed
and informative daily calls—to learn, aggregate, and disperse collective knowledge.
KEY FINDINGS FROM THIS STORY
There’ great irony that Post It notes are so common in innovation and
planning sessions, because the product was not planned. It was born
of a use found by a choir director for an adhesive that was otherwise
considered a mistake and wasn’t expected to generate any revenue.
True innovation comes from multiple parties being exposed to data and
methodically open to serendipitously connecting dots.
The global research project to avert a global pandemic from the SARS
(Severe Acute Respiratory System) virus. It comprised open source
technology, mass collaboration, multiple-centers, and the best
scientists from 11 nations. The SARS effort involved continually passing
data back and forth—including working through informative daily
calls—to learn, aggregate, and disperse collective knowledge .
8888888888

21. According to Collins, innovation requires discovering what we don’t know that we don’t
know. Numerous examples from history show that sometimes the greatest
breakthroughs happen by accident (e.g., penicillin, Post-It notes).
Collins says this is another key aspect of container-enabled innovation, what he calls
“serendipity over planning.”
While serendipitous discoveries may be accidental, that does not mean serendipity is
random. Rather, it is the product of connections or insights paired with one’s ability to
recognize the discovery.
“Creativity cannot be planned, it can only be facilitated,” Collins argues. “Centralized
planning of command and control is designed to eliminate surprises and therefore
blunts serendipity…Organizations need good surprises for sustained business
success.”
The value in fostering serendipity would seem to be key to looking for innovation in all
the wrong places.

22. Serendipity and the 'Aha' Moment – Unexpected
Insights in the Innovation Process
By Tim Maurer
Disruptive innovation and displacement is happening so fast that many innovation and
product development leaders are looking to accelerate and systematize the hard-to-fulfill
ideation and discovery phase of the innovation process—the innovation funnel. To that
end, for more than 20 years, organizations, researchers and computer scientists have
been examining the recurring role that serendipity has played in successful innovations.
These innovation drivers have sought to not only assess the role of serendipity, but to
also determine if serendipity can indeed be systemically enabled through big data,
analytics and visualization. Indeed, it can be.
Simply defined, serendipity is “an aptitude for making desirable discoveries by accident.”
Key findings on serendipity in innovation are detailed in a paper, “Discovery Is Never by
Chance: Designing for (Un)Serendipity,” by experts at the University of Southampton, UK
KEY INSIGHTS FROM THIS STORY:
Key for organizations, innovation managers and teams will be finding and
tapping “super-encounterers” who repeatedly encounter and harvest
unexpected information. Pair super-encounters with core, established,
networked leaders, with assets, who can make things happen.
Seek serendipity—insights of previous unknown, delightful data – use systems.
Discovery recommender technology can spawn serendipitous insights. Spurring
innovation via serendipity includes purposefully and systematically enhancing a
discoverer‘s domain knowledge to enhance likelihood they’ll be able to
appreciate a serendipitous connection when they stumble across it.
Partially relevant/iterative data nuggets are key to generating new directions in
discovery-seeking and harvesting processes. Publish data/discoveries for
serendipity-hunting agents to find; dispatch insights to domain experts who’ll
translate them. Combing big data for serendipitous insights and prepping
recipients to harvest the insights requires key attributes to convert insights to
yields:
• Supplement data gathering with collective wisdom to ascribe merit and
potential to a serendipitous discovery (include data gathering “containers”
and collaboration processes to share and work across systems
• Build capacity to leverage serendipitous insights into tests and production.

23. and Microsoft Research. The paper describes how computer scientists have been
generating “serendipity-inducing systems.”
IT experts have focused on developing “discovery recommender” technology to
recommend something interesting and previously unknown—or at least something
unknown within the domain involved. These systems can enhance serendipity as a
foreground activity in innovation and can foster behavior change in looking for,
internalizing, and applying insights. The authors suggest it is the particular type of
unknown and unexpected data that creates value in a Big Data-type recommender
system. In particular, tapping other domain “knowns” can be very valuable.
Importantly, it has also been shown that partially relevant or iterative nuggets of data or
results may play a key role in informing and generating new directions in the discovery-
seeking and harvesting processes. The authors of the paper cite the importance of
publishing discoveries so many serendipity-hunting agents can find them. They also cite
the importance of structurally dispatching this insight to appropriate domain experts
who may be able to make something of it. They stress that knowledge about the
encountered information or resource—as well as knowledge about the task the person is
engaged in—are both critical dimensions within serendipity and recommender-system
outputs.
Combining the value of big data for serendipitous insights and preparing recipients to
harvest those insights, the authors unearthed several key attributes for potential
systemic replication, including:
• Structured data gathering and analytics to unearth what would be viewed as
serendipity—particularly insights from previous “unknown” and “delightful” data.
• Supplementing that data gathering with elements to tap and increase collective
wisdom to ascribe merit and potential to a serendipitous discovery (which could
include the use of data gathering processes and “containers” as well as collaboration
processes to share and work information across organizations, ecosystems, unrelated
disciplines and industries)
• Building capacity to internalize serendipitous discovery into innovative insight and
action, including through networks that can marshal resources to extend innovative
insights and ideas into tests and eventually full production.
Enter the Super-Encounterers

24. Another key finding that presents implications for organizations, innovation managers
and teams is the existence of so-called “super-encounterers.” These are people who
regularly and repeatedly encounter—and harvest—unexpected information, even
counting on it as an important “expected” element in information acquisition.
Finding, retaining, nurturing, equipping, and leveraging super-encounterers who can
receive, discern, and share information is the key to establishing a culture that can
produce serendipity-enabled discoveries and innovations.
One of today’s most recognized, successful and enabling super-encounterers is the big
data innovation leader, Stephen Wolfram. His innovativeness using big data and analytics
was behind the renowned computer language Mathematica. Wolfram also publishes one
of the most leveraged computational knowledge engines, Wolfram|Alpha, which supports
Apple’s Siri, Microsoft’s Bing, Facebook’s personal analytics, the CIA World Factbook and
the independent search engine DuckDuckGo.
Written with over 15 million lines of Mathematica code, Wolfram|Alpha has helped
people make powerful, unanticipated connections across multiple databases and
operations.
“The number one thing I probably contribute is making connections to other
things,” Wolfram said. “As a CEO, I get different people in different parts of our company
to learn about what’s happening in other parts of the company. It’s somewhat successful,
but ultimately I’m usually the one who has to tell people to make this or that connection.”
Yet, fostering serendipity (or at least the potential for it) is possible throughout an
organization, not just with these super-encounterers.
It boils down to expanding knowledge and connections to create fertile ground for
serendipitous insights. In a 2011, Forbes contributor Deborah Mills Scofield wrote that
the randomness that emanates from our networks is a key element in disruptive
innovation. According to Scofield, “What you know depends a lot on who you know. … If
you stay within those confines, your network remains fairly constant and self-selected. …
It’s when you venture outside of that circle that your network, and knowledge, starts to
expand – you ‘know’ more people so you ‘learn’ more which leads to knowing more
people and on and on.”
The importance of chance encounters in the workplace can be frustrated by a world
where telecommuting is increasingly in vogue. Not so at Yahoo!, which banned

25. telecommuting in 2013. Of this challenge, Greg Lindsay wrote in The New York
Times about the importance of forcing collaborations among colleagues and filling
corporate “structural holes.” Lindsay noted: “As Yahoo and Google see it, serendipity is
largely a byproduct of social networks.
Close-knit teams do well at tackling the challenges in front of them, but lack the
connections to spot complementary ideas elsewhere in the company…but are hallway
collisions really the best way to stoke innovation?”
The Beauty of Sagacity
Innovations that have been enabled via serendipity have required an equally important
aspect—“sagacity” (the breakthrough connection of those findings to relevant
perspectives—or wisdom—to generate the truly “aha” discovery).
Indeed, equally important to appreciating serendipity is finding those parties who have
the sagacity to accept the insights referred by the serendipity-hunting systems and
developed by the super-encounterers—especially if those encounterers are not the final
say regarding an idea’s worth.
A 2012 paper from scholars at Sam Houston State University, “Leadership Sagacity and
Its Relationship with Individual Creative Performance and Innovation,” affirms the
importance of sagacity in leadership when guiding an idea through full innovation
implementation. The authors assert that it is essential for leaders with authority for
allocation of resources to have a high level of sagacity, including a high level of
discernment, wisdom, and judgment necessary to decide which ideas should be
championed toward innovation.
As an example of the importance of sagacity in innovation leadership, consider Ernest
Duchesne, who first documented Penicillin in 1897. Duchesne’s findings, however, were
rejected by the Institut Pasteur, reportedly because of his youth. It would take another 30
years before Alexander Fleming would accidentally create Penicillium mold, the first step
down the road to today’s antibiotics.
There other examples of potentially serendipitous discoveries missed for lack of sagacity,
essentially because people were incapable of drawing or accepting the necessary
connections.

26. Thus, a complementary challenge to spurring innovation through serendipity must
involve purposefully and systematically enhancing the discoverer‘s domain knowledge to
enhance the likelihood that they will be able to appreciate a serendipitous connection
when they stumble across it.