Article visualizing action - innovation daily

Visualizing Action: A Recipe for Boston Innovation Success
By Debra M. Amidon, Founder and CEO ENTOVATION International Ltd.
and Oliver Schwabe, Principal, Eurofocus International Consultants Ltd.
In an era of Big Data, we are challenged to identify signals of progress. In this kaleidoscopic
economy where complexity and change are the norm, classical financial indicators are no longer
sufficient. Intangible or intellectual value parameters - where knowledge, innovation and
collaboration are integral - must be considered. Here we demonstrate a unique tool for social and
organizational networking analysis to provide insight with a picture for strategic planning and
economic development.
The Innovation Frontier:
In 1994, W. Edwards Deming highlighted management is all about being able to predict
what will happen and then making those decisions to bring an organization the greatest
benefit.1
In the fuzzy world of intangible value, select predictors (aside from the classical
financial metrics) are difficult to determine. Traditional accounting mechanisms do not
provide much light on intangibles.
Further, since knowledge is growing at a geometric rate, we may be approaching the
singularity2
of which Ray Kurzweil writes; and we should not expect that acceleration to
slow soon. The pervasive Internet and ERP solutions have enabled a shift from vertical to
distributed organizations and the rise of ‘the enterprise’.
More than a decade ago, a monograph including the ‘Economics of Intangible Value’3
,
was commissioned by the Canadian Society of Management Accountants4
; and
TrendMonitor International documented the trends according to valuing, counting and
trading. Furthermore in a research report, ‘Creating the Knowledge-Based Company’5
,
measurement was determined to be the area in this new knowledge field showing the
largest gap between management expectations and achievement. Measurement of
intangible value (perhaps an oxymoron) is the least understood and – at the same time -
the most critical activity for success.
In an effort to make sense out of all this new reality, ‘innovation eco-systems’6
have
become the new modus operandi. How can we reliably predict how to mold
1
W. Edwards Deming, The New Economics [Cambridge, MA: The MIT Press 1994, Pg. 101]
2
Kurzweil, Ray. The Singularity is Near: When Humans Transcend Biology[NY: Penguin Books 2006]
3
Visit: http://www.entovation.com/assessment/trends.htm
4
Amidon, Debra M. et al. Collaborative Innovation and the Knowledge Economy, [Toronto, Ontario: Society for Management
Accountants. 1998]
5
Skyrme, David J. and Debra M. Amidon, Creating the Knowledge-Based Business [UK: Business Intelligence 1997]
6
Sahasrabudhe, Amit et al, Performance Ecosystems: A decision framework to take performance to the next level [Palo Alto, CA:
Deloitte Development LLC. 2012]
© 2013 Debra M. Amidon and Oliver Schwabe. 1

organizations for sustainable value in our digitized, networked, knowledge-focused,
innovation-driven and complex era?
Clearly, the ability to innovate, and thus adapt to an uncertain future, is the most
valuable asset of an enterprise. The challenge lies in understanding what relevant
variables can and should be measured. There is some guidance.
Calibrating Performance:
In a trilogy of books on Knowledge Economics7
, with 27 authors of from 17 countries, a
modern economic foundation emerged with three Laws of Knowledge Dynamics:
 The First Law: knowledge multiplies when shared. Knowledge – best referenced
and measured in the form of Intellectual Capital (IC) – is the prime asset of 21st
Century management. [e.g., The DENSITY of a network is the primary
performance metric from a network perspective.]
 The Second Law: value is created when knowledge moves from its point of origin
to the point of need or opportunity. The real benefit of knowledge lies in action;
innovation is the process where knowledge is put into motion or used. [e.g., The
(geodesic-) DISTANCE among participants of a network is the primary
 The Third Law: mutual leverage provides the optimal utilization of resources - both
tangible and intangible. Collaboration - the value of leveraging knowledge of
one another - creates greater wealth and sustainability with profound network
effects. [e.g., The in-degree CENTRALITY of network participants is the primary
These Laws play a role in how companies approach their strategic thinking even when
not stated explicitly. They are even more integral when considering innovation as
business strategy.
In last half of the last century with the quality movement, managers discovered the
customer as central to marketing strategy. In their ground-breaking book8
, Treacy and
Wiersema outlined the new climate of ‘hyper-competition’ and the resultant need for
companies to be expert in one of three arenas: operational excellence, product/service
leadership or customer intimacy.
Today, we manage an environment of ‘hyper-collaboration’, in which human and
technical interactions need to be diagnosed, monitored, and even incentivized. It is not
only customers from whom we need to learn; but the knowledge of all stakeholders (e.g.,
suppliers, distributors, external research and media sources as well as competitors) needs
to be harnessed. The innovation eco-system, in its entirety, becomes the ‘enterprise’ and
the unit of performance measurement. We need a new planning platform - beyond the
TBL reporting originally developed by Novo Nordisk (see below).
7
Amidon Debra M., Piero Formica and Eunika Mercier-Laurent (Eds.), Knowledge Economics: Principles, Practices and Policies
[Estonia: Tartu University Press 2006]
8
Treacy, Michael L. and Fred Wiersema, The Discipline of Market Leaders: Choose your Customers [Reading, MA: Addison-
Wesley, 1995]

Slide no 6 • Mads Øvlisen, Novo Nordisk A/S, Denmark • 8 Nov 2005
Copyright© Novo Nordisk A/S, Denmark
Source: Evolved in 2004 by Debra M. Amidon with Novo Nordisk from Cannibals with Forks by John Elkington (1997)
Towards Knowledge Era
FutureLongerWiderTime11
BlendedSoftHardValues9
RelevantOpenClosedTransparency10
InnovationSolutionProductDeliveries8
CollaborationCooperationCompetitionMarkets7
CultivateFacilitateAdministrateLeadership6
LearnBalanceControlReporting5
ImpactOutcomeOutputMeasures4
StrategicInclusiveExclusiveGovernance3
SymbioticSynergeticSubversionPartnerships2
KnowledgeInformationDataTechnology Focus1
Knowledge eraInformation era -
Triple Bottom Line
(TBL)
Industrial era -
Single Bottom Line
Business parameterNo.
Figure 1: Knowledge Era Trends9
Together with Bryan Elliott Davis, founder of the Kaieteur Institute of Knowledge
Management (Canada), we examined hundreds of examples of what we call
Knowledge Innovation Zones [KIZ]10
and a number of Intellectual Capital (IC) indicators
under development11
(e.g., the World Economic Forum, the UN, The World Bank, Milken
Institute, Robert Huggins Associations, Booz Allen Hamilton, Regional Indexes, City Annual
Reports, EUROSTAT, WIPO, The Economist, to mention a few), we developed the Triple
Knowledge Lens [TKL]12
– the triangulation of the Knowledge-based ECONOMY (Markets,
Business, and Commerce), Knowledge-based SOCIETY (Networks, Communities and
Culture), and Knowledge-based INFRASTRUCTURE (Organization, Environment and
Technology).
The Triple Knowledge Lens [TKL] was further refined as Intellectual Capital – Human
Capital and Structural – in the form of a new Innovation Value Proposition (see Figure
below) with 15 value capital drivers – complete with variables that influence the drivers in
a fully functioning system.
For our research study, these were the performance metrics determined to be most
relevant to positioning and could be useful as social media diagnostics. Successful
leadership in the Knowledge Economy requires a dynamic balance of all 3 axes – not
one at the expense of another.
9
Amidon, Debra M. and Bryan Elliott Davis, “Triple Knowledge Lens” [Spain: IC Magazine February 2006]
10
Visit: www.inthekzone.com
11
Visit: http://www.inthekzone.com/pdf/KIZ%20-%20External%20Indicators%20Inventory%20v1%201b.pdf
12
Amidon, Debra and Bryan Elliott Davis, A Preview: The State of Knowledge Innovation Zones (KIZ) [IVG April 2006]

©2013. Strictly Company Confidential. All rights reserved.
Human CapitalHuman CapitalHuman Capital
Relational
Capital
RelationalRelational
CapitalCapital
Structural
Capital
StructuralStructural
CapitalCapital
TKL Factors for
Eco-system Positioning
Optimal
Leverage
OptimalOptimal
LeverageLeverage
- Amidon and Davis
www.inthekzone.comwww.inthekzone.com
 Strategic Capital
 Organizational Capital
 Intellectual Property Capital
 Technological Capital
 Environmental Capital
 Diversity Capital
 Brand Capital
 Network Capital
 Cultural Capital
 Social & Community Capital
 Knowledge Capital
 Leadership Capital
 Innovation Capital
 Entrepreneurship & Creative Capital
 Reputation Capital
Figure 2: The Triple Knowledge Lens
What was labeled Intellectual Capital in 198713
can now be categorized with a
taxonomy defining a variety of intangible variables: This categorization (below) is what
shaped the methodology later described in the Boston Innovation Case, a Knowledge
Innovation Zone or KIZ.
Value Driver Label Description
1. Knowledge Capital “Gravity” The power, depth, and breadth of the knowledge assets in
your personal portfolio including specialized know-how,
experience, and knowledge mastery. [e.g., number of web
pages indexed by search engines]
2. Leadership Capital “Fidelity” Recognition as having outstanding management qualities,
skills, and capabilities for direction forward.[e.g., the relative
ratio of centrality in-degree to centrality out-degree]
3. Innovation Capital “Brightness” Proven and consistent capabilities regarding the
incubation, development, production and of marketing of
innovative designs, processes, and systems. [e.g.,
eigenvector centrality]
4. Entrepreneurship Capital “Agility” Recognition for exhibiting entrepreneurial instinct, passion,
zeal, drive, and success. [e.g., geodesic distance]
5. Reputation Capital “Awareness” Having a positive image and standing in your field as
perceived by others. [e.g., Page-Rank in overall ecosystem]
6. Diversity Capital “Bandwidth” Proactively maintain, cultivate, and respect variety in your
relationships, networks, and community connections. [e.g.,
variance of organizational types with reciprocated
connections]
7. Brand Capital “Authority” The degree your identity has visibility, presence, and
positive mindshare in the marketplace. [e.g., relative
number of authoritative sites linking to a website]
8. Network Capital “Influence” The degree of depth, density of far-reaching connections
and influence within those networks. [e.g., relative (sub-)
network density and centrality]
9. Cultural Capital “Coherence” Respect and trust your unique constellation of values and
the ethos reflected in your mindset, way of thinking, spirit,
learning desire, imagination and creativity.[e.g., structural
integrity of the network]
10. Social & Community
Capital
“Spread” Degree of active involvement as contributor, participant,
and representative of all that’s good within those social
ecologies. [e.g., density and geodesic distance of the
13
Amidon, Debra M. and Dan Dimancescu. Managing Knowledge Assets into the 21st
Century [Cambridge, MA: Technology
Strategy Group 1987]

network]
11. Strategic Capital “Integrity” Formulated business plans in place, business designs, and
business models. [e.g., relative number of top level external
supply-chain links]
12. Organizational Capital “Structure” Enterprise structures and capabilities in place that provide
you with a collaborative advantage across functional,
industry and geographic boundaries [e.g., web-farming
looking for comments made on the company by
employees, customers, suppliers]
13. Intellectual Property
Capital
“Protection” Extent to which you have explicit control of valuable
proprietary assets. [e.g., relative number of patents,
copyrights etc. registered in the company name]
14. Technological Capital “ICT Enablement” Degree of sophistication and prowess of the information
technology infrastructure. [e.g., web-farming looking for
technology related news on the company]
15. Environmental Capital “Greenness” The degree to which socially responsible, sustainable, and
green values have been internalized into your current
practice. [e.g., relative number of connections to relevant
umbrella organizations]
Risk Complexity The reliability with which the future dynamics of the
ecosystem can be predicted. [e.g., relative strength of
reciprocal connections]
Figure 3: 15 value Driver Approximations
Case Example: The Boston Innovation Landscape
In many competitive innovation ranking reports, the United States is slipping; and the slide
to mediocrity is imperceptible. In the Atlantic Century II14
, it is reported, the United States
ranks 43rd
out of 44 nations. In the same report, however, if Massachusetts were a
country, it ranks #1 in the world – ahead of Finland, Sweden, Singapore, Denmark,
Japan, South Korea and Belgium. What are the differentiators; and can we easily
visualize?
The same ITIF organization produces a New Economy Index15
comparing all the States in
the United States; and Massachusetts has led the ranking for the last five years.
Additionally, Boston is the #1 World Innovation City16
. Boston is the #1 Digital City in
America17
; and Boston Convention Center is the #1 in the country18
. The State ranked #1
in the Race-to-the-Top education competition19
; and is a lead recipient of Federal R&D20
across several industry sectors as well as major marketplace for Venture Capital21
.
Arguably, it represents one of the most prominent zones of innovation in the United States
and the world. Might we glean some insights as to why?
Recently, Boston was the destination venue for a week-long innovation tour22
by 52
CEO’s from four Regions of Northern Italy. As preparation, a Massachusetts Knowledge
Innovation Zone [MA-KIZ] ChoiceBoard was compiled as exemplars of the local region
innovation leadership. The program, sponsored by CONFINDUSTRIA (the Entrepreneur
14
Atkinson, Robert, The Atlantic Century II: Benchmarking EU & U.S. Innovation and Competitiveness [D.C.: ITIF, July 2011]
15
Atkinson, Robert, The 2012 State New Economy Index [D.C.: ITIF, December 6. 2011]
16
Innovation Cities Top 100 Index 2011 [Australia: Think2Know, October 11th
, 2011] Visit: http://www.innovation-
cities.com/innovation-cities-index-top-cities-for-innovation-2011/
17
10th Annual Digital Cities Survey – 2010, Visit: http://www.digitalcommunities.com/survey/cities/?year=2010
18
Visit: http://www.advantageboston.com/boston/awards.aspx
19
Visit: http://www.bostonfoundation.org/Content.aspx?ID=11520
20
Visit: http://www.usinnovation.org/state/pdf_cvd/MassachusettsR&D2012.pdf
21
Visit: http://www.nvca.org/index.php?option=com_content&view=article&id=255&Itemid=103
22
Viist: http://www.entovation.com/mailing/E100-En-Route-to-Boston-A-Global-Innovation-Landscape.htm

Association of Italy), was organized as 6 Case Stories with CEOs and 10 modules ranging
from MIT; Boston Innovation District; Harvard University; Kendall Square; Babson
College/Olin College of Engineering; IBM/Consulates; Legal Sea Foods Quality Control
Center; MOITI; Collaboration Gene; and the Best of Boston. It was intended to survey the
local innovation branding, activities of start-up companies, the changing roles of
executive managers from the perspective of the City of Boston, the Commonwealth of
Massachusetts and the New England Region. Care was taken to position all in a global
context and future management challenges; and over 65 local experts participated. The
learnings from this activity were applied to the subject of this article.
Our visualization analysis was based a diagnosis of 15 of the ChoiceBoard organizations23
with methodology that is easily transposed into any other context. Organizations
evaluated included: AIM, Artaic, Babson College, Boston University, CleanTechOpen,
Deloitte, EMC, Entrepreneur’s Network [ENet], Hult International University, iRobot, Mass
Challenge, MassTLC, Swissnex, TEDxBeaconStreet, and Xconomy.
How can we use our diagnostics to create visuals that capture the activities creating the
dynamic exchange of knowledge that typifies a sustainable innovation zone? We
assume that Density, Distance and Centrality – according to the 3 Laws of Knowledge
Dynamics – represent ‘goodness’.
Then, we examined underpinnings of the innovation fabric - the organizational network
diagnostics of the zone. The focus of this analysis lies in demonstrating how digital
ecosystems, as reliable approximations of the ‘real’ world, can be visualized. Thus, they
can be used to:
 identify where in the ecosystem an organization wishes to ‘play’,
 define tactical measures for moving toward the desired position,
 propose a way to monitor progress, and
 set the stage for a Knowledge Innovation strategy which would embed the
needed new behaviors in their organization.
We also assume those digital networks, being products of human collaboration (and
hence living systems), reflect “brick and mortar” reality and thus provide actionable
insights based on the laws of knowledge dynamics: density, distance and centrality.
Methodology
The 15 selected organizations were subjected to a web-crawl diagnostic approach
developed through several EU studies2425
and supported by a custom designed web-
crawling application provided by Eurofocus International Consultants Ltd.
The method essentially completes a series of continuously refined web-crawls to identify
linked websites, refines the generated network view based on a set of focused
innovation value drivers [See Figure 3] and then aggregates these into an overall
ecosystem view based on filtering techniques developed over decades.
23
Visit: http://www.networkpredictor.com/index.php?
option=com_content&view=article&id=52&Itemid=55&b8dccd02318e8ad5c9205b43f6552480=502de25e175fb67d24fe47fe892219d
5
24
Allee Verna et al, “Effectiveness of ICT RTD Impacts on the EU Innovation System: Final Report,” Evaluation [Brussels:
European Commission, DG Information Society and Media Directorate C Lisbon Strategy and Policies for the Information Society,
Unit C3 – Evaluation and Monitoring, December 11, 2007]
25
Daal, C., et al, The Skåne Regional Innovation System A value network perspective: Summary of research results Final Report
[Skåne Region 2009]

The result below illustrates the “Massachusetts-15” innovation ecosystem in which the
aggregated organizational networks are displayed. Connections and edges are not
displayed for the sake of simplification. Further layout calibration was completed based
on the approach developed at the Digital Methods Initiative26
in the Netherlands.
Figure 4: The Massachusetts-15 Innovation Ecosystem
This digital ecosystem consists of 2,482 organizations and the 3,398 reciprocated links
between them.
For illustration, the following figure uses ‘AIMnet’ – the network of the Association of
Industries of Massachusetts27
[AIM] – founded in 1915 and comprised of enterprises
employing one out of every five workers in the Commonwealth and representing almost
every sector of the economy.
26
Visit: https://wiki.digitalmethods.net/Dmi/WinterSchool2013
27
Visit: http://www.aimnet.org

Figure 5: Top-Level View of the AIMnet Ecosystem
The blue “CP” icon identifies the current position of AIMnet within the digital ecosystem.
The green icon “SS” identifies the “sweet spot” or center of the digital ecosystem – that
position where we believe the potential for value-creation by an organization is highest.
Based on the distance of AIMnet to the center of the network, a basic “grade” can be
assigned ranging from “A” if located in the middle of the ecosystem to an “F” is located
at the periphery of the ecosystem. AIMnet is given a B grade in this analysis.
A further perspective of relevance illustrates the AIMnet-centric view of the network as
highlighted in the next figure. It provides an opportunity to see some of the prominent
connections as well as contrast a pure web diagnostic view with one more focused on
the intangible performance measures of an innovation eco-system designated in the
ENTOVATION Navigator.
Figure 6: The Digital Ecosystem of AIMnet

The red icon “HS” marks a “hot spot”, therefore a region of notably high level of
connectivity. Additionally, a review of the website through the use of HubSpot’s
Marketing Grader solution28
enabled identification of key social media elements of the
AIMnet presence.
Finally, a high level assessment based on the value-driver approximations allowed for
verification of overall positioning. Take note that digital presence, from a high level, is not
sufficiently mature to identify relevant ecosystem pivot points that point to efficient
optimizations. The label ‘pivot’ - versus a ‘tipping’ - is consciously chosen as a ‘pivot’ may
involve a turn, spin around, revolve or rotate whereas ‘tipping’ (i.e., a tilt, lean, angle.
Incline or slant) options are more limited.
Verification involved: (1) applying the value-driver approximations of the organizations
and then (2) correlating the relevant scorings with the performance diagnostic grade for
the organizations in the overall ecosystem. This correlation validates the effectiveness of
the ecosystem mapping method as a reliable approximation of innovation capability
and potential for value-creation.
Each of the 15 organizations were evaluated in this manner and then the generated
ecosystems aggregated, as pieces of a puzzle, into the overall ecosystem illustration as
shared above. The network data gathered for each of the 15 organizations was
tabulated (below) based on the Triple Knowledge Lens performance metrics.
FirstLawofKnowledge
Dynamics(Density)
SecondLawofKnowledge
Dynamics(Distance)
ThirdLawofKnowledge
Dynamics(Centrality)
OverallTKLScore
AIMnet 10 1.92 18.95 57.6
Artaic 4 0.96 2.83 15.36
Babson College 3 2.28 29.96 34.2
Boston ENet 1 3.47 4.02 17.35
Boston University 2 2.16 39.57 17.28
CleanTechOpen 2 1.93 44.90 3.86
Deloitte 0,5 1.81 8.88 0.905
EMC 1 2.01 40.36 12.06
Hult University 2 2.96 8.96 41.44
iRobot 2 2.3 5.22 13.8
Mass Challenge 1 2.1 94.45 4.2
MassTLC 0,4 2.78 60.99 3.336
Swissnex Boston 1 2.73 61.20 10.92
TedxBeaconStreet 1 2.13 5.95 8.52
Xconomy 3.0 1.9 23.02 5.7
Average 2.26 2.23 29.95 16.44
Figure 7: TKL Scoring of the Massacshusetts-15
There are 4 rankings provided: one for each of the 3 Laws of Knowledge Dynamics and
an Overall Score. The scores are simply an artifact of the process of evaluation. Relative
ranking is the significant factor. It should also be noted that all 15 enterprises were
selected from the ChoiceBoard because of their innovation prowess.
28
Visit: http://marketing.grader.com/

The below figure illustrates the potential correlation between awareness (Page-Rank) of
an organization within its own eco-system and its awareness (Page-Rank) in the overall
ecosystem. The finding indicates that the positioning of an organization within the overall
ecosystem relates strongly to how to shapes its own ecosystem.
Figure 8: Scatterplot correlation of Page-Rank (Awareness)
In order to identify the key innovation players in a KIZ, it is hence potentially sufficient to
determine those organizations with the highest Page-Rank in the regional or industry
ecosystem. Once these are known, the ecosystems themselves can be developed
leveraging these with the P7
methodology, while start-ups / ventures in the zone might
need to align themselves as intensively with these key innovation players.
Keep in mind that AIMnet is one of many organizations selected through the Knowledge
Tour research as a suitable participant on the MA ChoiceBoard; and hence, by default,
belongs to the more influential of the 2,482 organizations identified as participating in the
MA-15 focused digital ecosystem. Further research and expansion of the effort to include
all participants of the ChoiceBoard will help verify this.
Is AIMnet the “key” player in the MA-15 ChoiceBoard KIZ? It is definitely one of the major
influencers of the KIZ Knowledge Innovation dynamics. Each of the organizations has
relative strengths and contributions to the overall eco-system and likely has influenced
the exceptional ranking of Massachusetts in the nation and around the world.
Initial Findings
The intent of the innovation research was to explore whether the TKL performance of an
organization in their ecosystem could be approximated using advanced organizational

network mapping techniques and custom-designed web-crawling/grading solutions in a
rapid, reliable and practical manner.
1) Through the simplification of research-based performance metrics of Knowledge
Innovation systems (i.e. TKL and the value-drivers) we found it was possible.
2) This result promises the potential to introduce reliable performance monitoring
solutions as support for ecosystem development approaches and governance.
3) While traditional organizational network analysis focuses primarily on centrality of
an organization in the network, our research study demonstrated the TKL
perspective leads to a more balanced view of performance diagnosis because it
considers multiple perspectives of relevance.
4) Focus on the key competence of Knowledge Innovation capabilities of an
enterprise offer an entrée to moving the enterprise and its stakeholders into their
sustainability sweet spot.
5) The study validated a rapid innovation capability assessment method for
organizations that can be performed externally and with reasonable effort.
6) It also validated a technical solution and method for quickly and easily
generating visual maps of an organization’s (digital) ecosystem with sufficient
richness to highlight actionable decision-making to improve value-creation. This is
especially relevant considering solutions and methods available to-date require
significantly greater effort and generate fewer insights.
7) The research study furthermore suggests a way to monitor the position of an
organization’s ecosystem in the market-space and a way to compare the value-
creation of an organization to that of others in the market-space.
The web-crawling solution provides an initial map of the market space relevant to the
inquiring organization. The challenge, then, lies in calibrating this map with the detailed
TKL value-drivers in order to indicate the relative competitive advantage of the
organization. The question that arises is whether it is possible to validate this scoring
against relevant third-party measures; so further validation research is to be explored.
With these insights, what are the tools and processes to move an enterprise within the
ecosystem? How do we move these organizations (and their stakeholders) toward their
desired sweet spot?
Action: Operationalizing Results
We are amidst what MIT professor Michael Stonebraker, a co-founder of seven Big Data
companies, refers to as a ‘data tsunami’.29
In Massachusetts alone, it is reported there
are at least 100 Big Data companies, dozens more in stealth mode and thousands of
professions who are users of big data technologies. Most are already familiar with the 3
V’s – Volume, Velocity, and Variety – originally outlined by Gartner; and the 4th
enhancement - Variability - added by IBM. Now, the literature and conference
29
Big Data and Analytics [Boston, MA: Massachusetts Technology Leadership Council, 2011] Visit:
http://c.ymcdn.com/sites/www.masstlc.org/resource/resmgr/masstlc_content/masstlc_bdr.pdf

presentations includes (at least) three new additions: Value (and Valuation), Vision and
Visualization.
This resulting 7V Factor30
provides a challenge for the most adept management team.
We need to rethink our approach to managing a future which is economically viable
amidst inevitable kaleidoscopic change. We need to use all tools and analytics
available, such as those represented here, to visualize action. It is a first step – an entrée
into innovation implementation.
Armed with the tactical and strategic insights from the web innovation diagnostics, a
prescriptive framework is provided as the P7
KIZ Assessment31
– a social systems design
methodology to manage programs from concept through full-scale implementation.
Knowledge, as the asset of abundance to be managed, has a magnifying effect as
represented in the P7
(i.e., P to the 7th power). P7
targets the flow of knowledge – amidst
the network connections - with a new mindset and systematic assessment process based
upon inspiration, insight and interaction. The P7
KIZ assessment explores the following
perspectives – ingredients for success:
 P1
Smart Innovators have a sense of purpose
 P2
SmartInnovators guide with a set of principles
 P3
Smart Innovators understand the full process of innovation
 P4
Smart Innovators gauge financial and non-financial performance
 P5
Smart Innovators want governing policies – ethical and transparent
 P6
Smart Innovators use ‘bench-learning’ to monitor practices
 P7
Smart Innovators know prosperity depends upon stakeholder innovation
©2009. Strictly Company Confidential. All rights reserved.
5. Policies
3. Innovation
Process
6. Practices
2. Principles 7. Prosperity via
Stakeholder Innovation
1. Purpose
4. Performance
Design Phase Development Phase Deployment Phase
Figure 9: The P7
KIZ Methodology
Organizations, by nature, are organic and operate within their (digital) ecosystem
-whether they know it or not. These ground-breaking intangible performance metrics
allow management to capitalize on their positioning from a network eco-system
perspective that is not part of current management paradigms. The foundation for
building ‘collaborative advantage’ can be laid – a strategy which can be seminal to
success.
30
Amidon, Debra M. presentation at the World Summit on Innovation and Entrepreneurship [WSIE 2012] in Boston, Massachusetts
[September 28th
2012]
31
Amidon, Debra M. “KM Coming of Age” [UK: The Ark Group December 2012]

Conclusion
Today, we need to manage the innovation environment – not leave it to serendipity.
Managing is a function of creating the conditions where innovation can occur – where
ideas flow efficiently into and within the system and are converted into viable products
and services that create highest value.
The current research, by default, provides, a static ‘snap-shot’ of the Massachusetts
innovation ecosystem. It is a useful starting point for introducing a repeatable and
empirical monitoring capability of ecosystem development and performance. As the
number of these digital ecosystems mapped globally grows, comparative diagnostics
are possible. The insights generated, while supporting business planning, create a
foundation for coherent innovation strategies and relevant performance.
Being able to visualize market-spaces, diagnose current and potential value-creation,
defining an action strategy to maximize positioning and determining optimal stakeholder
constellations are critical management capabilities in today’s economy. The jury is out
whether this network perspective can be considered as a ‘new game in town’ or
whether it is actually leading to a change in the ‘rules of the game’.
We are in what seems to be a chaotic environment trying to drink from a data hose.
This digital ecosystem perspective offers a simple – but not simplistic - and straight-
forward approach for improvement. This method is suitable for static or dynamic
monitoring of value-creation capability in a complex systems environment. Pragmatic
actionable interventions can be identified; and all sets the stage for embedding a
Knowledge Innovation strategy in daily business planning and operations.
The 21st century has given birth to the knowledge-based economy, society and
infrastructure establishing a foundation for innovation-based real-time performance.
Changes in several fundamental management parameters have a kaleidoscopic effect
on managing a company or a country. The Knowledge Era – in contrast to the Industrial
or Information Eras - demands solutions that are symbiotic, collaborative and innovative
in which people and communities are nurtured.
The research study has demonstrated that digital ecosystem analysis serves as a powerful
foundation for a better understanding of how the laws of knowledge dynamics and
associated value-drivers are performing. The ensuing diagnostics lead to straight-forward
operational measures defined by current search engine optimization (SEO) approaches
which demand daily attention by management.
We now have techniques to make the intangible more visible. Whether it is a new
‘game’ or new ‘rules’: now is the time to create the playground, determine the players,
cultivate the interaction and mine the results.
Knowledge Innovation®
is a registered trademark of ENTOVATION International Ltd.

A global innovation strategist, Debra M. Amidon, founder and CEO of ENTOVATION
International Ltd [Wilmington, MA USA], is considered an architect of the Knowledge
Economy demonstrating how theories can be applied for practical results. An international
thought leader and author; she has published 8 books in foreign translations, including The
Innovation Superhighway – acclaimed as the “Innovation Book of the Decade”. Debra has
delivered hundreds of articles and keynote presentations in 38 countries on 6 continents. Her
clients include Fortune 50 companies, government agencies and enterprises such as the EU,
OECD, IADB, UN, the Asian Productivity Organization, the Arabian Knowledge Economy
Association and The World Bank. She has advised governments on innovation strategy, such
as France, the UK, Singapore, China, India, Colombia, Australia and Saudi Arabia. With her
notable E100 Network, her seminal concepts – intellectual capital, knowledge innovation,
and stakeholder innovation collaborative advantage - have become the standard-to-
emulate. In 2012, Debra hosted the World Summit on Innovation and Entrepreneurship in
Boston. Debra holds degrees from Boston University, Columbia University and the MIT where
she was an Alfred P. Sloan Fellow.
Contact details: 2 Reading Avenue, Wilmington, MA USA 01887, T: +01-978-988-7995, E-mail:
debra@entovation.com, URL: www.entovation.com, www.inthekzone.com.
As experienced strategist and entrepreneur, Dr. Oliver Schwabe has enjoyed several decades
of experience in organizational change management and business intelligence with an
emphasis on value creation through technology innovation and network-centric principles.
Drawing on his skills in bringing compelling strategy blueprints, sustainable business blueprints
and effective technology blueprints to life, Oliver heads up Eurofocus International
Consultants Ltd which is responsible for helping global clients move effectively from
hierarchical to network centric business structures through system dynamics and network
analysis driven transformation efforts. Currently Eurofocus is focused on its Network Predictor
research venture which specializes in the development of software solutions and methods for
the discovery and diagnosis of digital ecosystems. Building on extensive experience in virtual
facilitation, online support, learning, organization design and leadership he helps clients
nurture sustainably successful strategies based on the principles of the knowledge economy.
Oliver has a doctorate in Business Administration and is a faculty adjunct to Capella University
and the Open University Business School. He is affiliated with the ENTOVATION Group Alliance
as the Fellow for Knowledge Products and Services.
Contact details: Eurofocus International Consultants Ltd., Wassergasse14, 55234 Wendelsheim,
Germany; T: +49 (0) 6734 916776; E-mail: Oliver.schwabe@euro-focus.com; URL:
http://www.networkpredictor.com; http://de.linkedin.com/in/oliverschwabe

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