Posts tagged Innovation

It’s sometimes jaw dropping how complex technology we take for granted is. How the Internet works is not a walk in the park. If you wanted to gain some functional knowledge about tech infrastructure and programming, check out Albert Wenger’s Tech Tuesdays posts.  He is a parter at Union Square Ventures. (In case you weren’t aware, his partner, Fred Wilson, has equally informative MBA Mondays posts.)

Browse some of his posts on Tech Tuesday below:

• Overview of how the web works
• Web servers
• HTML
• CSS
• Javascript
• Programming language syntax
• Literals, Variables, Constants

These are some highlights.  Subscribe to Wenger’s Tumblr to follow as he continues…

Earlier this week I participated in a spirited webinar on the topic of “real world outcomes”.  I prepared notes going into the discussion (see previous post) and the conversation touched on many of these points.

I promised to share interesting perspectives that arose over the course of the conversation and Q&A.  I’d summarize the major themes as follows:

• There are challenges to achieving the value of “third horizon” data (integrated sets of diverse medical and non-medical data): (1) Linking data sets across institutions, (2) scaling data and analytics infrastructure across organizations, (3) patient, payer, regulator trust in real world data and analytics methods
• Recent trends provide reasons to be encouraged about achieving value of “third horizon” data: (1) Analytics techniques are being refined, (2) Convergence tests give confidence in real world data, (3) Policy proposals encourage open transfer.
• Generating real world outcomes insights is just part of the equation.  The other side of the equation is what does one do with the insights to encourage physicians, patients to take action and modify behavior.

As a strategist and supporter of entrepreneurs in healthcare, it is discussions like these that help illuminate the gaps in current practice, technology, policy and the potential for solutions of tomorrow.

Today I am participating in a webinar with an esteemed panelist of experts in the field of “real world outcomes”.  The topic dovetails nicely with a basis of innovation in biopharma, which I wrote about in this post.  

In preparation for the discussion, I prepared a few notes on my personal view of the exciting potential reflected by this topic: 

What is “real world outcomes”?

Real world outcomes is a moniker for a broad range of topics related to consumer value of healthcare products and service.  I view real world outcomes as a continuum encompassing three elements: (1) Inputs, (2) Process, and (3) Outputs.  

• As an output, real world outcomes is an analytical measure of the health impact - safety, effectiveness, cost, satisfaction - of interventions outside the realm of controlled clinical trials.  Real world outcomes are an important complement to the body of analysis based on controlled clinical trials sponsored by biopharma and device firms.
• As a process, real world outcomes can be a painstaking labor of aggregating, normalizing and standardizing information that describes consumers’ and service suppliers’ experience in the health system, and then devising analytics methodologies to generate actionable output.
• As an input, real world outcomes is a growing body of information being generated by many stakeholders in healthcare using various “media” to describe the clinical, financial, and behavioral experience of consumers and suppliers of healthcare.  

How is real world outcomes evolving?

The field of measuring value of healthcare interventions has a long history from the beginning of medicine.   One can frame the evolution in three phases: (1) Phase 1 - Claims-based analysis, (2) Phase 2 - “Small-data” outcomes research, (3) “Big data” outcomes research.

• Phase 1: Much of real world outcomes analysis has been generated using medical and pharmacy claims data.  Because claims data is an administrative instrument, use of this information alone yields high-level insights answering the question “what happened?”
• Phase 2: Post-approval registry commitments and local investigator-sponsored studies complemented claims data with controlled clinical trial like medical data about patients experiences.  We are squarely in this phase today and gleaning greater insights answering the question “why things happened?”
• Phase 3: As more data comes online as a result of government incentives, lower costs of information technology, consumer-generated information and relevance of data from outside of healthcare, future insights describing personal experiences of large numbers of patients suddenly become possible.

Why is real world outcomes important?

The short answer is that trends in the environment necessitate stakeholders to consider new models of collaborating to access inputs, develop analytics processes and develop integrated products and services for improved outcomes.  The affordability, access and qualityt of care depends on it.

The long answer involves a recognition that the potential of Phase 3 depends on tackling a long and daunting list potential barriers to the powerful future.For example:

Over the next few days, I’ll summarize the discussion and Q&A.  I expect it to surface interesting perspectives..

This post initiates a series of posts over the course of this year to contextualize opportunities for business innovation from the perspective of various health system stakeholders.  First off, Pharma.  (Next up, Devices & Diagnostics.)

Where is the Pharma industry today?

The industry is in the midst of a multi-year evolution that can be described by three phases:

• Phase 1: The Blockbuster Phase
• Phase 2: The Globalization & Specialization Phase
• Phase 3: Redesign Phase

Pharmaceutical firms grew in size over the two decades from 1970s to the 1990s by discovering, developing and acquiring small molecule products shown to safely and effectively to treat large populations afflicted by chronic disease. Blockbusters, as they came to be known, created high-multiple companies that were darlings of the investment community.  As limitations of chemistry-driven discovery of medicines became more and more difficult to overcome, many in the industry have looked to foreign markets for geographic diversification and also have taken advantage of advances in science to develop biologic-based treatments for more complex (specialty) diseases afflicting smaller populations.  The industry as a whole is currently operating in this phase of the evolution.  Experiments abound to seek improvements in R&D approaches to develop effective medicines for the most complex patients and in distribution of medicines across current and new geographies. 

Few companies are now boldly entering the next phase of the evolution to attempt to refashion the the role of pharma in the healthcare system and directly address important trends ocurring both inside and outside of healthcare:

• Individuals are suffering from chronic illness at higher rates and cost.  (Chronic disease being defined as Cardiovascular, Respiratory, Cancer, Diabetes, Mental Illness.  See this previous post for cost estimates.)
• Decline of return-on-healthcare spending (i.e., poor health outcomes in return for increasingly high healthcare spending)
• Government activism to address unsustainability of the current structure of healthcare financing and delivery by (a) changing incentives through new reimbursement models, (b) encouraging coordination of care through new delivery models, and (c) stimulating modernization of information technology. 
• Employers in the U.S. shifting greater burden of healthcare financing and decision-making to the consumer.
• Mobile and internet-based technology is more ubiquitous than ever

The redesign phase demands biopharma to experiment with better operating models, technologies and economic models, or new ones altogether.

Basis of innovation

The above trends present biopharma firms entering into the third phase two (and not mutually exclusive) options:

1. Continue to march up the technology chain with more advanced systems and process to develop “precision medicines” that require high levels of investment to meet the needs of higher demanding consumers with heretofor unmet clinical need.  Consequences: smaller and smaller consumer bases and higher and higher prices.
2. Do more with less using new approaches to apply information, technology and collaboration that lower cost, barriers to access and create new channels to help consumers curb chronic disease.  Consequences: unknown business models that change economics of an industry.

Those familiar with Clayton Christensen’s model of disruptive innovation will recognize these options as the paradox he coined The Innovator’s Dilemma.  The industry is organized ideally to choose Option 1.  However, Option 2 may be viewed as a threat to the core business and unattractive from an economic point of view, hence de-prioritized.

Tools for innovation*

Regardless of the choice of basis of innovation above, innovators should consider a number of tools for innovation.  The strategies to apply these tools will vary based on corporate context and the extent to which the focus is on option 1 or option 2.  The discussion of strategies can be left to the comments.  Innovators seeking opportunities for innovation might consider utilizing the following tools and approaches to redesign or recreate the pharma value chain:

• Personal diagnostics
• IT-enabled consumer services
• Incentive models for behavior change
• Outcomes based measures of consumer value
• Deeper collaboration with customers and suppliers

Technology advances writ large are enabling the tools and approaches above.  In the past several years, innovations have delivered biopharma products that personalize, localize and de-specialize medicine.  Considering the building blocks for innovations, welcome comments on strategies ot utilize the tools and approaches to redesign biopharma. **

* The discussion above takes the focus on operational efficiencies as a given.  Biopharma and other sectors of healthcare will continue to explore cheaper and more cost-effective methods to perform operational functions such as manufacturing, distribution, sales and customer support.  As a result, I haven’t elaborated on tools for innovations in this area (mostly relying on outsourcing, offshoring or enabling with information technology).

** Full disclosure: I am currently employed by a biopharma.

Over the course of this year, I will provide my views of the context for innovations (see prior post on areas of interest) from the perspective of these five healthcare stakeholders:

1. Biopharma manufacturers
2. Device & Diagnostics manufacturers
3. Health insurance companies
4. Self-insured employers
5. Health delivery networks

Conversations with investors, entrepreneurs, current and former colleagues have led me to a conclusion (unscientific, granted) that a major reason we don’t benefit from more impactful business innovations in our healthcare system and attracting talented innovators who can address poor return on investment of our health system is because the status quo is complex and not well understood. 

These series of posts, I hope, will play a small part in reducing complexity and attracting more talent and impactful ideas.  I anticipate the posts will offer high-level frameworks which can be expanded upon and explored in the comments or in separate posts where there is interest.

As the saying goes, “it all starts with the data”.  Stephen Wolfram’s latest posting illustrates the power of what can be done with data about activities from email time, keyboard strokes, in person and phone meetings, and walking.  The above image summarizes his average daily rhythms on all of the data he has collected over more than a decade.  Impressive stuff.  

It begs the question, now that he has collected the data, what does he want to do with it?  What insights does he take away and how where does he see opportunities to change his behavior?  And, how will he go about actualizing it?

To read his post, click here. 

Scott Anthony, Innosight’s Asia practice lead recently wrote in a HBR blog that to create innovative products or solutions, one needs to:

..understand your customers better than they know themselves so you can predict what they want without having to ask them to articulate what they want.

How does one achieve such an understanding?  Is it the “A.G. Lafley” way (i.e., a scientific approach based on rigorous customer interviews)?  Or is it the “Steve Jobs” way (i.e., an artistic approach based on a future vision)?  The answer is that the tool one chooses depends on the type of innovation that is being sought.  

It helps to define innovation.  When you ask two people to define innovation, you often get three different answers.  For purposes of this topic, consider two types of innovation that sit on ends of a spectrum:  

• On one end, incremental innovation represents innovations that are bite-sized improvements to a product or service that reduce cost, time or improve quality.  
• On the other end, transformative innovation represents innovations that create new markets or categories offering customers new ways of performing tasks or enjoying themselves.  

A gradient of innovations exists between the two ends of the spectrum.  It is easier to talk about innovation by first defining they type of innovation one is seeking or where it may lie on the spectrum.

Tools for incremental innovations
For incremental innovations, the insights most often lie with the product or service’s lead users, those users whose desires are not fully met.  The traditional approach used by marketers and strategists seeking incremental innovations is to ask lead users what they want.  Satisfaction surveys, in-depth interviews, focus groups, prototype co-development are the tools de jour.  Kevin McFarthing, formerly of Reckitt Benkinser, writes these tools allow one to pull together “consumer habits and product usage, together with attitudes and emotions around the product category.”  The confluence of habit and attitude can be the source of real insight.

Tools for transformative innovations
The common problem when seeking insights for transformative innovations is that the tools that work well for incremental innovations lead one astray when seeking transformative innovations.  Deriving insights for transformative innovations by only asking lead users what they desire does not work well.  Tools for incremental innovations are probably still necessary, but not sufficient.  As Anthony alludes to, insights for transformative innovations demand tools that help one understand consumers better than they understand themselves.  So asking lead users is not enough.  Consider these tools for insights leading to transformative innovations:

1. Observation of non-users and lead users.  An example from A.G. Lafley’s career provides a good example:

Customers regularly rated the packaging of Tide’s laundry detergent as “excellent.” Then why, Lafley wondered, did he never see a customer open a package by hand, relying instead on scissors or nail files?  It turned out that customers didn’t want to risk breaking their nails on the so-called excellent packaging.

Hence, an opportunity for packaging innovation that lies somewhere in the middle of the innovation spectrum.  He observed, rather than asked, users for the insights that led to an innovation.

2.  Computer analysis of user-generated information.  Luckily with today’s advances in computing power and decline of data storage costs, it’s not necessary to camp out in a customer’s home to observe a hidden data point.  It now affordable to “pivot” a terabyte of data in under three seconds and churn out previously hidden patterns.   Take for example the story of Target’s Guest Marketing Analytics Group.  Privacy issues notwithstanding, information about people, how they act, when they act and what motivates them is everywhere and relatively accessible to data scientists.  The volume of data available to retailers is staggering:

1. Demographic information - age, marital status, number of children, address
2. Economic information - job history, salary, tax payments, home ownership
3. Education information - high schools, colleges, advanced degrees
4. Preferences - online behavior, political leanings, reading habits, charitable giving

Insights for transformative innovations be it products, services or business models lurk in the explosion of data, just waiting for someone to identify the hidden insights, validate it against intuition, and use it.  This is an exciting tool to capture insights for transformative innovations.

Dave Chase’s writing on the topic of innovations in healthcare provide great texture for Christensen and Hwang’s disruptive innovation theory. He’s killing it.  And, he’s putting it into practice at Avado. 

In case you haven’t been following Dave’s writing, below is a collection of his most recent columns:

• WWJD? The CEO Every Healthcare Leader Should Learn From (Feb 2012)

As healthcare goes through massive changes, health system CEOs would be well advised to study what newspaper industry leaders did (or perhaps more appropriately, didn’t do) when faced with a similar situation.

• Why Google Health Really Failed—It’s About The Money (June 2011)

Since then, there’s been a lot of bits spilled offering explanations, but they all missed the most critical item. Money. Or in the language of healthcare—Reimbursement.

• Why It’s Good News HealthIT is So Bad (Feb 2012)

Not only are entrepreneurial ventures popping up like weeds, healthcare providers are getting far more aggressive about trying new models without doing the equivalent of organizing the Roman Legions.

• Nimble Medicine (Feb 2012)

Disruptive innovators such as Qliance and WhiteGlove Health rethought the care delivery and payment models from the ground up. Their results have been impressive.

• Money Ball for Medicine – Business Models for Healthcare (Jan 2012)

These are healthcare providers who’ve applied technology to enhance their competitive advantage. Traditional healthcare providers should be on notice about these types of disruptive innovators.

• Healthcare Field of Dreams In Idaho: Health System Opens Innovation Center (Jan 2012)
  

There are innovation centers at pharmaceutical and insurance companies but they don’t possess the advantage of a direct connection with individuals and must take a broader view. By taking an approach that leads with the community and individuals, rather than an institution, there’s a great opportunity for technology companies to test their wares in the real world with St. Luke’s direct connection to individuals, community and business leaders critical to having a broad-based success

• DIY Health Reform: Employers Solving Healthcare Crisis One Onsite Clinic At A Time (Dec 2011)
  

As more employers learn of the great benefits from a well-executed onsite clinic model, they will continue this Do it Yourself Health Reform trend that is happening one employer at a time.

• Walmart’s Early Christmas Gift To The HealthTech Community (Dec 2011)
  

Healthcare remains a paradox of cutting edge medical technology while being an information technology backwater. While the kneejerk reaction to many has been to see the downsides of Walmart’s entry, there’s a clear upside to jumpstarting disruptive innovation.

• Healthcare Disruption: Pharma 3.0 Will Drive Shift from Life Science to HealthTech Investing (Part I of III) (Jul 2011)
  

Based on my past (non)experience with pharma, it has been remarkable the number of pharma companies that are now proactively reaching out to software companies who can help them enter with new services focused on outcomes that have little or nothing to do with what I would traditionally associate with pharma.

• Healthcare Disruption: Providers Will Use HealthTech to Differentiate and Produce Better Outcomes (Part II) (Jul 2011)
  

Healthcare providers must reinvent themselves or they’ll meet a similar fate to the Denmark hospitals that are now closed. A key part of their reinvention will be enabled by a new generation of technology solutions.

• Healthcare Disruption: Providers Are Making Newspaper Industry Mistakes (Part III) (Jul 2011)

Those that avoid sticking to the old tried and true methods of differentiation that worked in the past will be light years ahead as the transformation of healthcare takes hold. If they don’t, employers who are paying the bulk of healthcare costs are taking matters into their own hands and building their own onsite clinics.

Over separate conversations this week, the topic of “convergence” in healthcare surfaced multiple times. The lines between stakeholders in the healthcare ecosystem used to be discrete. Now, they are getting more fuzzy and interesting than ever. In the innovation parlance, “the white spaces are shrinking”. This trend is going to have profound effects on how we think about products, services and business models.

Three of the many examples of convergence at play:

1. Convergence of products.

Traditionally, regulated healthcare products have been categorized neatly into diagnostics, devices, and drugs. Regulatory agencies structured monolithic bureaucracies around these tidy categories. Unfortunately for our regulatory systems and innovation, as a by-product, science and technology have shrunk the distance among these products. Drug-device combination products are not uncommon (e.g., drug-eluting stents). Companion diagnostics (aka theranostics) are very likely to be the only successful approach in the oncology and specialty pharmaceuticals space. It is no longer good enough to have expertise in just one category.

2. Convergence of providers and payers.

Thanks to the unsustainability of healthcare costs and sometimes illogical (at least in retrospect) market access choices by health plans, forces are driving converging of the roles of payers and providers. Few organizations have started as integrated care management organizations (e.g., Kaiser Permanent, VA health system, Geisinger, Intermountain Health). But, recent government activism has encouraged certain behaviors amongst health insurers and providers to take greater accountability for population health is driving broader convergence among providers and payers. The Accountable Care Organization concept is a convergence of traditional roles of providers (to deliver care) and payers (to manage economic risk). Health insurers have sought refuge in less regulated sectors of healthcare by entering the provision care (example).

3. Convergence of business models.

Business models in healthcare are ripe for disruption. It’s the “known unknown” that healthcare cost inflation is bankrupting the U.S. budget. The fee-for-service business model is a key culprit (although cultural values are also to blame). Value-based business models which prevail in almost every unregulated sector of the economy are poised to replace fee-for-service healthcare sectors. Case in point: the return of capitated or bundled payments for the Medicare End Stage Renal Disease program.

As entrepreneurs, it’s worthwhile considering what effect convergence in healthcare may have on product or business model choices in the not too distant future. It’s also interesting to consider what opportunities it creates to think forward and design products and business models in areas that will be likely to converge in the future.

In my day job I am privileged to interact with entrepreneurs and early-stage companies who have something to offer my (large) employer. I hope to continue to meet impressive entrepreneurs and help advance their innovations through collaboration and investment. In observing some successful (and some not so successful) interactions, I thought it would be helpful to share five “best practices” for entrepreneurs when they approach a large company:

1. Do the homework

“Winging it” or using a “stapled presentation” is often not a successful approach for an introductory conversation. It can work if you are experienced or have sat at both sides of the table. There is usually plenty of available information through public sources, network connections, etc to piece together areas of interest and strategic needs of large companies. Doing the homework sets the stage for a substantive discussion after the pleasantries.

2. Explain the “why”

It’s tempting for entrepreneurs to jump into a demo of a product or service. After all, blood, sweat and tears have been shed to develop it. This is the “what” or the “how. What sets introductory discussions apart is an explanation of values, motivations, and the mission of your company. Establishing a connection at a deeper level than product alone hooks in a connection that can last longer.

3. Be honest

It’s also tempting to over promise the capability of a product or service in hopes of getting a foot in the door. It’s often transparent when this is happening. When it’s not and discovered later, it puts everyone in an uncomfortable position. Not worth it. Being self-aware and honest about capabilities in a paradoxical way can actually advance a discussion and relationship further.

4. Discover the strategy

One of keys to positioning a solution to a large company is to understand the company’s strategy at different levels of the organization and relate to it. First, showing that you’ve done your homework is a plus. Second, thinking through the implications of corporate, business unit and product strategy implications on how your product may be viewed allows the possibility of discovering a unique application of your product or service. Third, if few strategy signals exist, say so and start off the conversation to probe and uncover it.

5. Follow-up

The most effective managers are those who provide clear direction but also follow-up to check on progress, not just for accountability but also to coach along the way. The same idea works for entrepreneurs. Note next steps. Summarize them. Set expectations. Take prompt action. Nothing impresses more than fast, complete and effective follow-up.

These “best practices” go both ways. Large companies don’t always make it easy for entrepreneur to deliver innovations. This is a subject for another post but would be very interested in your suggestions for “best practices” for large companies when entrepreneurs approach them…

“Healthcare is regulated.”  ”We have to please regulators.”  ”One word: Regulation.”  Comments like these are almost always posed as objections to pursuing innovation in healthcare.  Entrepreneurs are optimistic and visionary people, and are not easily discouraged.  In light of regulation in healthcare, should they take these comments about healthcare regulation more seriously?   

Yes and no.  There are two sides to the debate.  

Yes, disruptive innovations are challenged.

Dr. Leslie Curtis and Dr. Kevin Schulman make interesting observations on the effect regulation has on innovations in the healthcare sector.  You can access the paper here.  They provide a useful summary of Clayton Christensen’s disruptive innovation theory, then state their observation that regulation in healthcare raises the threshold for innovative products and service models to enter the market to serve “non-consumers” who have a lower performance requirements.  Regulatory requirements, they argue, cause costs to rise and indirectly give advantages to incumbents.  

Curtis and Schulman provide two examples of potentially disruptive innovations that face the burden of regulation:

1. Managed care business models failing to take root as they were cornered by legislation designed to protect consumer interests.  
2. Hypothetical HealthIT platform to enable physicians to remotely monitor diabetes patients’ glucose levels will not gain traction due to reimbursement incentives.

At the market level, disruptive innovations like these are challenged to be viable by regulation.

No, disruptive innovations are still possible.

Entrepreneurs need not be discouraged.  Potentially game-changing innovations are not impossible in healthcare.  In many cases regulation does not pose an insurmountable barrier.  Christensen and others have pointed out several examples of such innovations:

1. Home glucose monitoring
2. Angioplasty and coronary stenting
3. Retail healthcare clinics

These examples have several characteristics in common: (1) Low-tech, (2) Self-directed or delivered by lower-skilled practitioners, (3) Lower-cost, (4) Serve current non-users, (5) New value network.  Entrepreneurs should therefore first consider product and service opportunities with similar characteristics and that avoid the evidence and monitoring requirements placed by existing regulations.  

To support entrepreneurs, policy makers should consider the unintended consequences regulation has on innovations that may achieve the “triple aim”: reduced cost, broader access and higher quality. 

betaworks crafts the future of the social web, and is a uniquely positioned company to know about when it comes to sparking innovation.  If you haven’t heard about it, this is a good article that provides a taste of what makes it special.  

Since 2008, John Borthwick has assembled a rockstar team and produced some of the most impactful social media companies out of New York.  So when he writes, it’s worth taking note.  His recent investor letter, as reported by Sarah Lacy, contains useful insights to ponder:

1. Proliferation of devices that are connected to networks is accelerating the rate of innovation
2. Connected devices are enabling real-time services and real-time networks
3. Networks of people, ideas and participation matter more than networks of devices
4. Great design has become increasingly vital as computing gets less expensive

These insights contain powerful implications to the themes I have been following, and will continue to explore this year.  

You can find the full investor letter here:

Betaworks Shareholder Letter

Last year, I had the pleasure of working with a distinguished and experienced team to curate the DPharm conference in Philadelphia in September — a TED-style event showcasing innovations and leading practitioners in Pharma R&D with a slight focus on clinical research.

Life Science Leader Chief Editor, Robert Wright, punctually blogged about the event (“Yo Adrian! - The Disruptive Innovation Event Was A Knockout”). Although three months have passed since the conference, I’m finally getting around to highlighting three themes that surfaced from the 25 speakers that underscore the promise and challenge of innovation in Pharma R&D:

• The Pharma industry is only just scratching the surface of transformative approaches to developing and testing new products. Scientists, physicians, patients, technologists and strategists have enormous potential to re-design development and testing approaches as the industry shifts goals from population-based, blockbuster products to precision-based, personalized products. This shift demands a lot of everyone. For example, it requires re-thinking the role of the patient in clinical research. Requires novel applications of information technology and science. It also demands new skills of leaders. Greg Simon (Pfizer), John Orloff (Novartis), Parvis Ghahramani (Forest Labs), Tomasz Sablinski (Celtic) and Diane Shoda (Pfizer/NEWDIGS) peeled back the complexities, thinking and actions required to make exciting strides using science, technology and business models.

• We can better apply the full-spectrum of clinical research options and utilize insights thereof appropriately. The first step is appreciating the full spectrum of options. Clinical research is no more a monolithic practice of prospective double-blinded placebo randomized controlled trials. Yes, RCTs are the “gold standard” for regulatory approval of new medicines. But, “real world” studies serve an important role. Retrospective and prospective analysis of the real-life experience of patients’ experience with therapies, care pathways, incentives can also provide important insights to transform health care. Steve Labkoff (AstraZeneca) and Ben Heywood (PatientsLikeMe) provided relevant examples of the latter.

• The role of innovator in clinical research is not for the faint of heart, and we need more. This was perhaps the most valuable takeaway for many. It’s obvious to many that successfully launching a new initiative with external partners demanded seemingly super-human levels of insight, perseverance and courage. It was much less obvious how much these qualities needed to be applied to move organizations internally as well. Fortunately, with practice the skills of an innovator can be developed. Designing a creative solution and finding a way to implement it - the essence of innovation - can be learned. Miguel Orri (Pfizer), Jon Platt (?WhatIf!), Randy Spaulding (Spaulding Clinical) and others shared their experiences of how they got things done.

Over 250 people attended the event. The speakers were all impressive. The feedback was encouraging, especially for an inaugural event. One attendee’s comment summed up the caliber of the crowd:

This was the first conference where I felt I learned with people who can truly change the world.

I was honored to be a part of it. As we look forward to the 2012 in Boston, please feel free to reach out or comment below areas of interest you’d like to see part of the 2012 event in Boston.

Gareth Cook, the brilliant Pulitzer Prize winning science writer tackled the concept of Open Innovation in this November 2011 essay that appeared in the Boston Globe, “How Crowdsourcing is Changing Science”.

He tells the story of how crowdsourcing evolved from a concept to simply tap into unused computing capacity into a much more complex and powerful concept of tapping into creative genius of diverse experts.   This how he eloquently puts it:

What marks this as an important milestone in the history of science is the new way it harnesses the power of the mind. There are many tasks that are beyond the grasp of even today’s computers, particularly those which involve interpreting complex images. Like identifying cancer cells. Or categorizing galaxies. Or picking out letters of ancient Greek, written in a faded ink with a fast, messy hand, without breaks between words. The Internet, it turns out, is a brilliant way to feed those problems into an array of the planet’s true supercomputers — human brains.

Cook provides the example of FoldIt to bring home the point that pockets of today’s networked scientific community can do things that were heretofore not possible.  Kaggle and others provide similar validation.

Crowdsourcing scientific insights at scale, however, won’t come without challenges.  For one, scientists are not accustomed to this style of work.  The culture must evolve.  In addition, data ownership and intellectual property rights are “fuzzy”.  Lawyers generally don’t like fuzzy…

I believe these challenges will be overcome.  The democratization of discovery is too powerful of a concept to stop.