Announcing our new book, The Rainforest Blueprint: How to Design Your Own Silicon Valley

Dear Friends:

Today, we’re proud to announce the publication of a new book, The Rainforest Blueprint: How to Design Your Own Silicon Valley! It’s a practical, 66-page, full-color, lively guide to unleashing an innovation ecosystem in your company, organization, or community. It’s an insightful, fast, and entertaining read.

We know that some people couldn’t find enough time to read the original Rainforest, which clocked in at 304 pages. The Rainforest Blueprint is for you!

The Rainforest concept is about ideas and tools that can transform the world. Therefore, we want to share this book far and wide, to reach as many people as possible. Please help us spread the word via Facebook, Twitter, or whatever medium you prefer. Pony express works too.

In exchange, we are pricing this low. Ridiculously low. It’s only 99 cents for the eBook. But the digital version pales in comparison to the print version, which is beautiful, vivid, and designed to feel like an immersive experience, not just an ordinary book. The print book is only $9.99. Either version is a steal. Better yet, get both versions, and share them with friends and colleagues!

To view the print version, click here (http://www.amazon.com/dp/0988274612),and to view the eBook, click here (http://www.amazon.com/dp/B00CVKYRX8).

Thanks so much for your support. Keep remembering to dream, trust, and pay it forward!

Complexity – it’s not simple: Solving the right problem Part 3

Notes on the practice of innovation and technology commercialization.

I did not expect these ideas on solving the right problem to expand into three blogs, so let’s wrap up this topic for now. We talked about identifying problems and also discussed fallible indicators which support decision making. Lastly, some tentative hypotheses about indicators and decision making in complex environments (spaces) such as Rainforests were introduced.

Indicators related to technology commercialization outcomes will always have different levels of fallibility. The Association of University Technology Managers (AUTM) annual survey of US and Canadian universities and teaching hospitals focuses on a relatively small indicator set.  I list these here so you can assess them for fallibility.  Also note that one indicator may in turn depend on other indicators.

• number of staff employed in technology transfer offices

• research expenditure

• legal expenditure and reimbursement

• patent related activity

• start-up activity

• licenses and options

• license income

For many developing countries, or indeed developed ones, these indicators are not sufficient for capturing contract research, skills development, indirect benefits, or other outcome-related metrics. Remember, there is a difference between outputs and outcomes. Indicators are the critical step between identifying a problem (discussed in Part 1 of this blog) and determining possible practical solutions in the appropriate problem context.

Not recognizing this frequently leads to ‘jump to’ solutions also described in Part 1 of this blog. This may happen because our personal networks are not sufficiently open to new thinking; hypotheses 1 and 3 from this blog Part 2.  In his 1984 book Decisions and Revisions: Philosophical essays on knowledge and value, Isaac Levi – now John Dewey Professor of Philosophy Emeritus at Columbia University – described seeking to identify potential answers to questions as a strategy to expand our personal body of knowledge (“knowledge corpus”). However, Prof Levy notes that all knowledge expansion bears the risk of importing error.  Refusing to expand our body of knowledge of course incurs no risk whatsoever. 

While reading Levy’s explanations recently  I came across the paul4innovating three-part blog of May 1, 2013, which I recommend reading, The Innovation Bunker – Our Cognitive Traps about minimizing cognitive traps which states:

“I suspect we are all cognitively trapped most of the time. We are all more ‘hard-wired’ than we would care to admit too. That cognitive bias that ‘permits’ us to make constant errors of judgement, ignore often the advice around us and certainly gloss over the knowledge provided or staring us in the face. Innovation does need us to break out of these cognitive biases if we want to really develop something very different, more transformational.”  I interpret Professor Levy as suggesting that another cognitive trap is our reluctance to expand our body of knowledge in case we introduce error.

These ideas also re-appeared in a recent paper in Research Technology Management, a journal for R&D managers:  Reframing the Search Space for Radical Innovation. Searching to identify ideas for radical innovation, companies may frame their searches within the frame of existing markets or well understood applications. But, limiting peripheral vision in this way may not recognize discontinuous innovation shifts occurring.  The paper notes however, as did Levy, that reframing an existing cognitive frame presents a significant risk.

Difficulties in identifying the right problem, understanding the degree of fallibility of an indicator, and cognitive traps are all characteristics of those complex ecosystems which support innovation.  These are the ecosystems in which we will increasingly live and work. Attempting to avoid such troubles by retreating into more ordered domains will only reduce our access to new ideas and thus reduce innovative activity. 

References to philosophers such as Levy, whose writings are somewhat dense with the language of symbolic logic, may seem disconnected from practical problems of technology commercialization and innovation ecosystems. I have tried to show that it is valuable to expand our knowledge of these domains, and that doing so increases our ability to make better practical decisions.

We can expect problem solving for innovation and technology commercialization in Rainforests to throw up challenges; our hypothesis H5 – that the fallibility of multiple fallible indicators is increased in complex spaces (such as Rainforests) indeed holds.

In the next blog I will try and show how these challenges become less intimidating and how new and energizing good practices can be developed, once the characteristics of such complex spaces are understood.

Next time: The ties that bind us: networks, strong links, weak links, and expanding our knowledge.

Can You Create a Capital Ecosystem to Drive Growth and Returns?

T2VC is proud to announce the following special event…

Learn the true lessons of the Silicon Valley capital experience.
Join the first certified trade & policy mission of its kind.
Gain skills to create your own capital ecosystem in a hands-on workshop.

The International Trade Administration of the U.S. Department of Commerce is proud to present the first Certified Reverse Trade & Policy Mission for Global Institutional Limited Partner (LP) Investors.  This trade and policy mission is designed for worldwide LPs and those responsible for creating capital ecosystems to meet leading U.S. private equity and venture capital general partners (GP) to learn tools to improve LP portfolio performance and lessons to apply for growing markets.

What are the benefits of participating?

• The inward trade and policy mission to the United States will be hosted in the vibrant capital ecosystem of Silicon Valley.
• Participants will meet general partners from many of the USA’s leading venture capital and private equity firms.
• Attendees will gain insider insights on how the capital ecosystem functions in Silicon Valley and the rest of the United States.
• Attendees will learn strategies to improve portfolio performance.
• The trade and policy mission will be structured as a professional development workshop on the latest investment portfolio design techniques, particularly frameworks, case studies, and tools from the capital ecosystem of Silicon Valley and the United States. 
• Workshop speakers will include leading investment practitioners and experts on how to enhance the performance of capital ecosystems.

By the end of mission, our goal is that you will have: (a) contacts with dozens of hard-to-access venture capital general partners in Silicon Valley and from across the United States; (b) gained insights into how the U.S. capital ecosystem functions; and (c) learned new tools that you can apply immediately to generate higher portfolio returns by growing your domestic capital ecosystem.

Mission dates:

• September 15-18, 2013   Apply Now!
• December 15-18, 2013
• March 16-19, 2014
• June 15-18, 2014

Only institutional and government LP investors and capital-related policymakers may apply.  Applications will be reviewed and you will receive a response within 1-3 days.  Learn more and apply at www.rainforest-architects.com.

This mission is organized by T2 Venture Capital, the private sector program manager.  T2VC is a Silicon Valley firm that builds both startup companies and the ecosystems that grow them.   Their workshop—the Rainforest Architects—gives leaders access to the latest tools, thought leaders, and peer networks for designing robust ecosystems..  This cutting-edge program is produced in partnership with colleagues from Stanford University and numerous other institutions. 

The “U.S. and Foreign Commercial Service” support the goals of this event, but does not endorse the specific products, or views of the participating organizations.  General Partners are selected to participate based on criteria set by T2 Venture Capital.  The United States Department of Commerce, International Trade Administration is not involved in recruiting and or selecting general partner participants.

For more information please contact your local United States Embassy, Foreign Commercial Service; or:

Mr. Randy Mitchell
Senior Trade Strategist for Private Equity and Venture Capital
U.S. Department of Commerce
International Trade Administration (ITA)
Office of Financial Services Industries (MAS/OFSI)
E-Mail:     randy.mitchell@trade.gov
Office:     1 202 482 2967
Mobile:    1 240 776 2208
Post:         1401 Constitution Avenue, NW Room 1800A, Washington, DC 20230

Promoting U.S. economic growth by stimulating and facilitating greater levels of foreign business investment in the United States. 

OR:

Ms. Christina Wu
T2 Venture Capital
christina@t2vc.com

Fallibility and the Making of Good Decisions: Solving the right problem Part 2

Management guru Peter Drucker noted that “making good decisions is a critical skill at all levels.” In mid April 1912, a decision was made based on an observation which proved to be fatally flawed. For ships sailing the North Atlantic routes at night in conditions where icebergs could be expected it was common practice to detect presence of an iceberg from the white foam splashing against the base of its dark bulk so that a decision could be made to steer the ship port or starboard to avoid a collision. Under the prevailing conditions of an ocean smooth as glass the lookouts on the Titanic saw no such indicator, and the rest is history.  A more mundane example of an indicator is when we look for the presence of dark clouds in the sky to see if it’s going to rain and whether to make the decision to take a umbrella when we venture out. As we know from experience it may not rain; this indicator is unreliable or “fallible.”

We constantly, and unconsciously, make decisions based on multiple fallible indicators. Ideally, indicators should be clearly defined, reproducible, understandable, and unambiguous. As we have just seen, these features are not always possible.

Indicators are the critical step between identifying a problem (discussed in Part 1 of this blog) and determining a possible practical solution in the appropriate problem context. Not recognizing this frequently leads to ‘jump to’ solutions also described in Part 1 of this blog.

As Kenneth R. Hammond points out in his fascinating 2007 book Beyond Rationality: The Search for Wisdom in a Troubled Time:

“Because indicators vary considerably in their fallibility, from complete fallibility to perfect infallibility, whether the fallibility is due to random or deliberate factors, it is essential that we be able to measure their degree of fallibility so that we can discriminate among them. These measures simply indicate, in one form or another, how often an observable indicator is associated with an observable fact, condition, or event.”

In selecting a possible policy solution to a technology commercialization problem we may use multiple indicators to select one or more possible solutions. These might be (1) off-the-shelf solutions, modified according to the problem’s context, (2) re packaged existing solutions, or (3) new solutions formed from theory or practice.

In many technology commercialization applications we also wish to know how well solutions will scale up for widespread applications. There is a paradox in how we approach scaling of innovation. In theory we test an innovation in order to determine whether it works and has potential for scaling up, but in practice the decision to move toward scaling up must often be made on the basis of inadequate information, producing fallible indicators, or indicators of unknown reliability, and also before all contextual conditions are in place (context was discussed in Part 1 of this blog).

Next month in the final part of this blog we will finally reach the promised investigation – after this necessary detour – of how problem solving in less structured Rainforest ecosystems may differ from problem solving in more structured environments.  What Rainforest elements impact on problem solving? Is identifying problems and possible solutions easier or harder in the Rainforest?

In the meantime let’s wax philosophical and state some hypotheses to chew over and test next time. “Wait” I hear you say “what’s philosophy got to do with technology commercialization?” I hope to demonstrate that the answer is “a lot.” These hypotheses are H1 to H5 namely:

H1. The fallibility of multiple fallible indicators is reduced in spaces where the characteristics are a balance of strong and weak links, with a sufficient number of weak links for stability but still enable access to divergent opinions and experiences (we will discuss weak and strong links in a future Blog).

H2. The fallibility of multiple fallible indicators is reduced in spaces where the characteristics are low transaction costs and high trust levels.

H3. The fallibility of multiple fallible indicators is reduced in spaces where the characteristics are efficient boundary spanning organizations.

Note what connects H2 and H3 is not just reduce transaction costs but transaction value (see The Rainforest book for a discussion)

H4. The fallibility of multiple fallible indicators is reduced in spaces where the characteristics are ordered domain focused on efficiency (such as Plantations), where the whole is the sum of the parts, and where optimizing the parts optimizes the whole.

H5. The fallibility of multiple fallible indicators is increased in complex spaces (such as Rainforests) where the characteristics are such that small actions may change the nature of the system. As a result to optimize the whole system, sub-optimal behavior of each of the components needs to be allowed.  See my February Blog Imperfect Works.