1. A Series Of Articles On “Innovation And Data For Good,” By Tim Maurer
Data for Good – Looking for Innovation in All the Wrong Places
Data for Good - Enabling Innovation Like Never Before
Data for Good – Towards Purpose-Driven Innovation
An affiliate of the U. S. Chamber Of Commerce
KEY INSIGHTS FROM THIS STORY:
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.
Data should be relentlessly probed to answer not just questions
first proposed, but also questions not considered.
KEY INSIGHTS FROM THIS STORY:
The rate of innovation’s success is usually below 10%, but by pursuing
multiple types, dimensions and stages of innovation, success rates can be
boosted many fold (and need to be).
Collaboration and crowd sourcing software and rules engines can help
affect Enterprise-wide innovation processes -- and funding, too. Platforms
can pull insights from varied participants to help assess, prioritize, help fund
and realize innovation opportunities.
Sources of insights are growing and must be harnessed: data repositories; IT
interoperability; protocols for data transfer; chats; published research;
regulatory and patent filings; transactional data exchanges;
unstructured/semi-structured data; social media; open but de-identified
records; Internet of Things sensing and controlling devices; and salesforce
automation can all offer critical insights.
Both longitudinal look backs and forward-visioning through rapid
prototyping systems can facilitate more successful innovation evaluations.
Pursuing new business models will be key to success.
5888
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.
· .

2. Wonder, Junk and Innovation
Data for Good – Innovating with Passion and Dogged Determination
Wiki Revolution in Innovation and Big 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
enabled 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.
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.
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.”
- Container Management tackles 3 aspects of innovation: 1.)
Accelerating Change; 2.) Increasing Complexity of Issues; 3.) Ubiquitous
Connectivity.
- Container Management 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.

3. Can Creativity Be Planned?
Serendipity and the 'Aha' Moment – Unexpected Insights in the Innovation
Process
KEY FINDINGS FROM THIS STORY:
There’s 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 provided a future-state model.
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 .
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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 sagacity and assets, who can make things happen.
Also, get the organization to extend outside their existing network for insights.
Seek serendipity—insights of previous unknown, delightful data – using
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 he/she’ll be
able to appreciate a serendipitous connection when he/she stumbles 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 insights requires key attributes to convert insights to yield:
• 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.

4. 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.
KEY INSIGHTS FROM THIS STORY:
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.
Data should be relentlessly probed to answer not just
questions first proposed, but also questions not considered.
An affiliate of the U. S. Chamber Of Commerce

5. 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 involved in innovation report
their firm is developing the ability to use the potential of ‘Big Data’ for Innovation.”

6. 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.
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.

7. 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.

8. Data for Good - Enabling Innovation Like Never
Before
By Tim Maurer
We live in an ever-growing ocean of data. Our networked world is a data-producing machine,
and increasingly businesses and governments are recognizing the great potential for
groundbreaking innovation stemming this much-championed “Big Data.”
Yet, innovations do not on their own bubble out of all this information. How exactly does data
drive innovation and what are the tools that enable us to harness that data?
As noted in the previous Data for Good installment, the opportunities afforded through data
are unlocked by deep analysis, looking for revelations in unlikely places. This innovation
challenge is daunting, but the resources available for insightful data gathering and innovation
optimization have never been greater.
Data-driven innovation is facilitated through:
A massive increase of digital data
This includes IT interoperability and open protocols for data capture and exchanges across
multiple sources and parties. There are also troves of research published on the Internet and
databases containing patent filings.
An affiliate of the U. S. Chamber Of Commerce
KEY INSIGHTS FROM THIS STORY:
The rate of innovation’s success is usually below 10%, but by
pursuing multiple types, dimensions and stages of innovation,
success rates can be boosted many fold (and need to be).
Collaboration and crowd sourcing software and rules engines can
help affect Enterprise-wide innovation processes -- and funding,
too. Platforms can pull insights from varied participants to help
assess, prioritize, help fund and realize innovation opportunities.
Sources of insights are growing and must be harnessed: data
repositories; IT interoperability; protocols for data transfer; chats;
published research; regulatory and patent filings; transactional data
exchanges; unstructured/semi-structured data; social media; open
but de-identified records; Internet of Things sensing and controlling
devices; and salesforce automation can all offer critical insights.
Both longitudinal look backs and forward-visioning through rapid
prototyping systems can facilitate more successful innovation
evaluations. Pursuing new business models will be key to success.
5888

9. Organizations can also look to Web services for transactional monitoring of data, such as
exchange rates, weather, and financial systems, and they can also look to unstructured and
semi-structured data, including social media data, open but de-identified medical records, and
more.
There is the “Internet of Things,” with sensing and controlling devices feeding mountains of
new data, and organizations can even look to their own Sales Force Automation Systems that
can be ready sources of front-line insights.
New technologies for revealing insights
Cloud services are enabling more and more organizations to analyze and glean insights from
myriad data sources at a fraction of the historic costs of building high-speed processing
systems. Businesses can use rules engines, which are able to formulate event triggers to
rapidly isolate opportunities or affirm or refute hypotheses.
The science and technology of business intelligence and analytics is also accelerating, as is the
capacity to leverage longitudinal assessments of approaches to innovation and IP in respective
sectors and spaces.
Methods for fast-tracking the innovation process
Technologies (like 3D printing, Mobile Human Machine Interfaces, open IT protocols, cloud-
based VoIP services) and software services (such as CAD CAM) enable rapid prototyping, elicit
market receptivity, and allow faster testing of product inventions and new service offerings.
When it comes to funding the innovation process, there are consumer and enterprise crowd-
funding venues and technologies for securing financial contributions, which can foster
innovation competitions and deployments. Crowdsourcing sites, online chat rooms and
collaboration hubs in use across leading corporations and their ecosystems foster faster and
more robust innovation, and with today’s mobile devices, businesses can engage, collaborate
with, serve and mobilize people like never before.
The good news is that there are also many experts and organizations providing these essential
tools and capabilities. They can support organizations in upping their innovation game to meet
today’s challenges.
In the field of technology-enabled data gathering and innovation conceptualization, for
example, an innovation consultancy that’s been recognized as a World Economic Forum
Technology Pioneer is Imaginatik, which provides enterprise-wide, crowd sourcing and
collaboration Software as a Service (SaaS) to drive and manage the innovation process.

10. Imaginatik’s “Innovation Central,” “Discovery Central,” and “Results Engine” platforms can pull
insights from diverse and varied participants to help organizations assess, prioritize, and
realize opportunities.
The innovation specialist, Doblin, a division of Deloitte, has amassed longitudinal data on all
kinds of innovations across what they view as “10 Types of Innovation” and across multiple
industry sectors and landscapes.
This baseline information can support innovation insight gathering, assess and corral possible
convergences, identify new innovation spaces to occupy, affirm distinct value in an innovation
hypothesis, or even refute proposed propositions as insufficiently distinct in creating value.
Doblin has historically noted that the rate of the typical innovation’s success is usually well
below 10%, and that by managing across all 10 types and dimensions of innovation, success
rates can be boosted many fold.
Another innovation consultancy, Optimity Advisors, has looked at collaboration from a social
perspective and is now advising on harnessing massive networks via Wiki Management. The
firm notes that “the power of networks is reshaping both the work we do and the way we
work.” They suggest that “designing organizations for mass collaboration demands a new and
very different model – Wiki Management.”
Business Models Represent the Latest Innovation Opportunities
Regarding the all-too-critical business plan development process for go/no-go determinations
and product investment prioritizations, there’s plenty of regulatory, investment filing and
population data (and plenty of industry trade articles on the Web) that can be assessed and
pieced together to project potential sources of revenue, transactional volumes and costs, and
to develop a traditional, compelling business case.
However, while rapidly creating new products is so very necessary, if a company’s strategic
plans and business cases focus primarily on new product developments, it’s quite likely that
the company will miss a major new source of sustainable innovation: the business model
itself.
The GE Innovation Barometer notes that “fifty-two percent of senior executives believe that
the development of new business models will contribute the most to their company’s
performance going forward, representing a six-point increase when compared to how it has
traditionally contributed to their innovation portfolio.”

11. The potential value in developing new business models is affirmed in a Doblin report, which
emphasized the potential untapped opportunities in expanding from molecules to new
business models for biopharmaceutical companies. The report states that “new commercial
models represent the biggest change in the way biopharmaceutical companies have been
engaging with stakeholders since the rapid expansion of the direct-to-consumer marketing
channel in the late 1990s.”
In its analysis of more than 1,500 publicly announced innovations in the pharmaceutical
industry during 2010, Doblin observed a biopharma industry focus on innovating for core
processes, product performance, networking, and channel. Doblin concluded that what the
industry had not done as much, however, was seize opportunities to “create new customer
experiences, offer value-added services, or define truly new business models.”
Given this, Doblin cautions that even more data will be needed when assessing and forging
new business models.
The report notes:
“To transform existing commercial models and create new models, companies can benefit by
taking an expanded view of what innovation can mean—including new services, experiences,
and business models…Greater value can come from innovations that differentiate a company’s
relationship with customers and other stakeholders by, for example, building a commercial
model that gives physicians information when, where, and how they want it delivered. Other
innovations could emphasize new services, such as simplifying patients’ access to products or
improving patients’ adherence to treatments.”
There’s no question: organizations today have at their disposal new tools, technologies, and
processes for enabling innovation in products, services, and business models.
But while these instruments can reveal deep insights gleaned through data and dramatically
advance innovation, the core element in the innovation process that needs to be better
understood and nurtured is the human element.
Driving innovation requires passionate people to pursue insights and push through adversity,
persevering despite the setbacks and failures that occur in the innovation process – a topic
discussed in the next installment of this series.
-

12. 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 and 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.”
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.”
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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13. 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.
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."

14. 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.
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.

15. 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.

16. 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
enabled 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.

17. 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.
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.

18. 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.”
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.

19. 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.

20. 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.
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.
An affiliate of the U. S. Chamber Of Commerce
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.

21. 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.
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.

22. 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.
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

23. 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.

24. 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.
In this case, container refers to the development of technology spaces for content.
As Collins describes it:
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.”
- Container Management tackles 3 aspects of innovation: 1.)
Accelerating Change; 2.) Increasing Complexity of Issues; and
3.) Ubiquitous Connectivity.
- Container Management 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.

25. “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.
“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.

26. 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.
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.”
KEY FINDINGS FROM THIS STORY:
There’s 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 provided a great future-state
model. 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

27. 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.

28. S erendipity 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
and Microsoft Research. The paper describes how computer scientists have been
generating “serendipity-inducing systems.”
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 sagacity and assets, who can make things happen.
Also, get the organization to extend outside their existing network for insights.
Seek serendipity—insights of previous unknown, delightful data – using
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 he/she’ll be
able to appreciate a serendipitous connection when he/she stumbles 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 insights requires key attributes to convert insights to yield:
• 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.

29. 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
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.

30. 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 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?”

31. 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.
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.