Скачать презентацию Leadership of Technological Change Ten Areas of Strategic Скачать презентацию Leadership of Technological Change Ten Areas of Strategic

4e072b985fe06de2fbadf96cc9ac585a.ppt

  • Количество слайдов: 35

Leadership of Technological Change Ten Areas of Strategic Disruption, Opportunity and Threat World Future Leadership of Technological Change Ten Areas of Strategic Disruption, Opportunity and Threat World Future Society 2013 July 2013 Chicago, IL John Smart, President, Acceleration Studies Foundation accelerating. org/slides | @johnmsmart

Foresight Education Acceleration Studies Foundation A 501(c)(3) Nonprofit There are now 22 universities where Foresight Education Acceleration Studies Foundation A 501(c)(3) Nonprofit There are now 22 universities where you can get a grad degree in foresight, and at least six good certificate programs, including SU. FERNweb. org Los Angeles New York Palo Alto FERN networks foresight grad students and helps them find good jobs. Global. Foresight. org Global. Foresight is a wiki of foresight orgs, resources and people. © 2011 Accelerating. org

Theory of Change What Drives Accelerating Change? Theory of Change What Drives Accelerating Change?

Strategic Vision: What’s Your Theory of Change? Of Progress? Acceleration Studies Foundation A 501(c)(3) Strategic Vision: What’s Your Theory of Change? Of Progress? Acceleration Studies Foundation A 501(c)(3) Nonprofit Good theories of change include values, and an idea of progress. My bias: I’m in a group of scholars who study complex systems from • Evolutionary “evo” variation, • Computational “compu” selection, and • Developmental “devo” optimization approaches. More at: Evo. Devo. Universe. com Los Angeles New York Palo Alto Bury, 1920

Evolution, Computation, and Development: Three Drivers and Two Patterns Found in All Complex Systems Evolution, Computation, and Development: Three Drivers and Two Patterns Found in All Complex Systems Acceleration Studies Foundation Utility Computation A 501(c)(3) Nonprofit Adaptation/Selection Partial predictability/optimization “Trees” “Funnels” Diversifying, Local Unifying, Universal Chance Necessity Evolution Development Unpredictable/ Not optimized Predictable/ Optimized The Structure of Evolutionary Theory, Gould, 2002, p. 1052 Los Angeles The Plausibility of Life, Kirschner & Gerhart, 2005, p. 219 New York Evo Devo Universe? , Smart, 2008, p. 18 What Technology Wants, Kelly, 2010, p. 123 Palo Alto © 2013 Accelerating. org

The “ 95/5%” Evo/Devo Ratio: Most Change is Bottom-Up Acceleration Studies Foundation A 501(c)(3) The “ 95/5%” Evo/Devo Ratio: Most Change is Bottom-Up Acceleration Studies Foundation A 501(c)(3) Nonprofit 5% Devo Nearly all (perhaps 95%) of the decisions and events that create or control complex systems appear to be bottom-up evolutionary processes. Only a small critical subset (~5%) are top-down, hierarchical, developmental processes. Planning and policy leadership often forgets this. 95% Evo Roughly 20 X More Change is Bottom-Up than Top-Down Examples: ▪ Almost all genes in an organism create evolutionary variety vs. a special subset (3 -5%) that form the developmental toolkit. ▪ Almost all thoughts in an organism are unconscious, vs. ~5% conscious. ▪ Almost all behaviors of an indiv. are environmental reactions vs. plans. ▪ Almost all decisions & actions in an org. are “out of control” vs. planned. ▪ Almost all social innovation occurs in economic markets vs. by govt policy. Los Angeles New York Palo Alto ▪ Almost all new IT prods & services empower network nodes vs. hierarchies. (personal computers, email, web, smartphones, wearables)

3 P’s Model: Possible, Preferable, and Probable Futures Three Types of Foresight Management Acceleration 3 P’s Model: Possible, Preferable, and Probable Futures Three Types of Foresight Management Acceleration Studies Foundation Vision, Strategy, & Planning A 501(c)(3) Nonprofit Los Angeles New York Palo Alto KM, Ideation & Innovation Forecasting, Risk Mgmt, & Prediction © 2013 Accelerating. org

ILP Model: Innovation, Learning, and Protecting: Three Basic Leadership Challenges Acceleration Studies Foundation A ILP Model: Innovation, Learning, and Protecting: Three Basic Leadership Challenges Acceleration Studies Foundation A 501(c)(3) Nonprofit Any system can be analyzed as either: 1. A Learning (“Adaptive”) System 2. A Innovating and Protecting (“Sustainable Innovation”) System 3. An Innovating, Learning and Protecting (“ILP”) System Los Angeles New York Palo Alto Evo Devo Universe? , Smart, 2008, p. 10 © 2013 Accelerating. org

IMF Model: Innovation, Management, Foresight: Three Leadership Toolsets Acceleration Studies Foundation A 501(c)(3) Nonprofit IMF Model: Innovation, Management, Foresight: Three Leadership Toolsets Acceleration Studies Foundation A 501(c)(3) Nonprofit Los Angeles New York Emerging Tech MS Curriculum Framework, U. of Advancing Technology, Smart, 2011. Palo Alto © 2013 Accelerating. org

Developmental Foresight What Can We Anticipate? Developmental Foresight What Can We Anticipate?

TINA Trends: Irreversible Social, Econ, Political, and Tech Trends Acceleration Studies Foundation A 501(c)(3) TINA Trends: Irreversible Social, Econ, Political, and Tech Trends Acceleration Studies Foundation A 501(c)(3) Nonprofit Pierre Wack, Shell Scenarios Group, 1970’s: TINA = “There Is No Alternative” (to the Trend, On Average) Ten Examples To Test: • • • Los Angeles New York Palo Alto Decreasing Avg. Violence (Incr. War Cap. , Incr. Regul. of Violence) Increasing Central Government Powers vs. Individual Powers Increasing Democratization and Global Interdependence Increasing Indiv. Rights (Women, Child, Relig, Minority, Gay) Increasing Social Justice and Sustainability (Envir. Justice) Increasing Total Energy Use/Capita, Saturating Indiv. E. Use/Capita Increasing Total Wealth, Social Safety Nets, Liesure Time Increasing Total Information, Comp. , Communication, Specialization Increasing Biological Capacities (Life-Like Abilities) of Tech Increasing Space, Time, Energy, and Matter Density & Efficiency of Tech Simon 1996 Pinker 2012 Morris 2013 Reese 2013

Ten Areas of Technological Change Acceleration Studies Foundation A 501(c)(3) Nonprofit 1. Nanoscience and Ten Areas of Technological Change Acceleration Studies Foundation A 501(c)(3) Nonprofit 1. Nanoscience and Nanotech 2. Information Tech 3. Engineering Tech 4. Resource Tech 5. Cognitive Tech 6. Social Tech 7. Health Tech 8. Economic Tech 9. Political Tech 10. Security Tech LE Drones (Phantom Eye, Scan Eagle) Disruptive Naval ISR Platforms Unmanned Surface Vehicle (Piranha) Naval ISR, Escort, Antipiracy Platform Los Angeles New York Leadership of Technological Change (and 30 Books For Further Reading), Smart, 2013 Palo Alto

A “Race to Inner Space” is the Engine and Steering of Accelerating Change Acceleration A “Race to Inner Space” is the Engine and Steering of Accelerating Change Acceleration Studies Foundation A 501(c)(3) Nonprofit Nanoscience/Nanotech - Physical Inner Space – “Engine” § § § § “There’s Plenty of Performance at the Bottom. ” Photonic crystal lasers 10^6 more E efficient than other microlasers Programmable synapses 10^6 faster, 10^3 less E/comp. than neurons Fission 1, 000 X more E/mass than chem. Fusion 1, 000 X more E than fission Fuel cells allow 100, 000 X more E/mass than chem. batteries (Dan Nocera) Synthetic catalysts increase reaction speeds and yields 10^3 to 10^6 Single step efficiency jumps in macro (human) space are always far less. Infotech/Simulation - Virtual Inner Space – “Steering System” § § § § “As Intelligence Rises, Thinking Becomes More Adaptive Than Acting” Adult humans no longer act in novel ways, they think in novel ways. Simulations allow “ephemeralization” (far less mass/energy per action) Rise of scientific simulations. NSF. IPCC. NASA Solar System Simulator Telepresence, telerobotics/haptics outcompetes traveling in person Google maps, sensors, geoweb, parallelized GPUs: visual cortex for the web. Machine sim data doubles every 2 years. Human sims grow far slower. Los Angeles Info: Intelligence, Fischler, 1987; Simulation, Ross, 2006; Simulation-Based Engineering Science, NSF, 2006. New York Nano: Engines of Creation, Drexler, 1987; Nanotechnology, Ratner, 2002; The Race to Inner Space, Smart, 2012. Palo Alto © 2011 Accelerating. org

Leaders Must Use the Strongest Levers, Nanotech and Infotech, and mind the Hype Acceleration Leaders Must Use the Strongest Levers, Nanotech and Infotech, and mind the Hype Acceleration Studies Foundation A 501(c)(3) Nonprofit "Give me a lever long enough, a fulcrum, and place to stand I will move the world. " - Archimedes, 250 BCE Fenn 2008 Los Angeles New York Palo Alto Gartner Hype Cycle

1. Nanoscience and Nanotech “Nano is faster, stronger, thriftier than humanspace” Acceleration Studies Foundation 1. Nanoscience and Nanotech “Nano is faster, stronger, thriftier than humanspace” Acceleration Studies Foundation A 501(c)(3) Nonprofit - Small-Scale Physics Nanoenergetics, Fission, Fusion Nanochemistry Nanocomputing Nanodevices Sloane 2012 Von Weizsacker 2009 Ratner 2002 Battery Energy Densities: Exponential Performance Curves Come from Nano Lead Acid 30 Wh/kg (8 X worse) Ni. MH 80 Wh/kg (3 X worse) Li-Ion 250 Wh/kg Zn-Air 1084 Wh/kg (4 X better) Li-Air 5200 Wh/kg (20 X better) Li-Air Theor. 12000 Wh/kg (50 X better) Leader’s Challenge § Where would an 500% (~5 X) improvement in efficiency or performance in a physical process, sensing, computation, or comm system make the most difference for your team? A 1000% (10 X) improvement? How can you get it? Los Angeles New York Advanced Energy Materials, 1(1), pp. 34 -50, 8 Dec 2010. Figure 1. Courtesy Ramez Naam. Palo Alto

2. Information Technologies “IT is Becoming Ubiquitous and Brain-Like” Acceleration Studies Foundation A 501(c)(3) 2. Information Technologies “IT is Becoming Ubiquitous and Brain-Like” Acceleration Studies Foundation A 501(c)(3) Nonprofit - Computing and Networks Internet of Things (IOT, MIOT) Shared Pictures and Simulations Conversational Interface and Agents Big Data and Predictive Analytics Siegel 2013 Mc. Afee 2012 Stibel 2009 In 2006 Watson got 13% of Jeopardy! Q’s correct. By 2011, Watson got 90% of Q’s correct. Apple’s Siri on i. Phone 4, 2011 Brain-Like Engrg (Modular, Parallel, Weighted) • 2800 processors, working in parallel • ~100 text search methods (10 M articles) • ~100 language processing methods • 550 predictor variables IBM Watson Jeopardy Challenge, 2011 • Trained on 5. 7 M Q/A pairs (to set 550 weights) • Weights continually adjust with experience. Leader’s Challenge Los Angeles New York Palo Alto § What type of computers, communication devices, platforms, networks, sensors, databases, predictive analytics, or pattern recognition would add value for your team? How can you improve your team’s IT intelligence, COTS use, R&D, procurement, and performance measurement (ROI) every week?

3. Engineering Technologies “Cities & Machines are Automating, Dematerializing” Acceleration Studies Foundation A 501(c)(3) 3. Engineering Technologies “Cities & Machines are Automating, Dematerializing” Acceleration Studies Foundation A 501(c)(3) Nonprofit - Smart Cities, Networks, Vehicles Automation and Robotics Dematerialization and Efficiency Greentech and Pollution Transportation and Logistics Glaeser 2011 Despommier 2010 Zhang 2013 (City Gardens) (Family Farms) 26 K Robot (Postharvest Automation) Walkable Cities • Hub & Spoke • Underground Pkg • Greenbelts • Bike trails (19 mph) • Vert. Farms • HS Rail • Country Dacha Google’s Robotic Cars Lit Motors C-1 (Self-Balancing) Leuven, Belgium Leader’s Challenge Los Angeles New York Palo Alto § How would you improve the “ethics” of autonomous drones and robots for urban use? What would a good “ethical architecture” for bots look like? On your team, who is responsible for safety? For speed & cost to capability?

4. Resource Technologies “Periodic Crises, Long-Term Abundance” Acceleration Studies Foundation A 501(c)(3) Nonprofit - 4. Resource Technologies “Periodic Crises, Long-Term Abundance” Acceleration Studies Foundation A 501(c)(3) Nonprofit - Energy Water Food Population Ecosystem and Other Resources CSP+Flash Desalination: Water for Africa, Energy for Europe Diamandis 2012 Amine Scrubbers for CO 2 Capture • 1930’s Technology • Piloted in Mongstad, Norway in 2012 • 20 -30% energy cost (Amine cycling, CO 2 comp. ) • 70 -90% of CO 2 is captured • Will not be implemented without govt. mandate (like almost all big safety or envir. upgrades) Eccles 2010 “Cultured” Meat Likely Late 2010’s Leader’s Challenge § Who is responsible for resource acquisition and sustainability on your team? How will you track, report, and reward more sustainable resource ROI? Los Angeles New York Promises and Pitfalls of Carbon Capture, Fellet, Ars. Technica, 11. 28. 12. Palo Alto

5. Cognitive Technologies “Conversational Interface to the Wearable Web” Acceleration Studies Foundation A 501(c)(3) 5. Cognitive Technologies “Conversational Interface to the Wearable Web” Acceleration Studies Foundation A 501(c)(3) Nonprofit - Conversational Interface & Cyber. Twins Crowdlearning (Teacherless Ed) Global English (Workforce Growth) Wearable Web (Augmented Intell) Education Reform (Finland Model) Valiant 2013 Google Glass (Augmented Intell) Wristphone concept, 2007 Leader’s Challenge Los Angeles New York Palo Alto $500 Next IT’s Virtual Agents Finland is #1 in FREE STEM and Civics Ed. (50/50 Ed. Model) § How do you improve online training processes and performance measurements on your team? Improve use of desktops, laptops, tablets, mobiles, wearables? How do you figure out the 50% core, and 50% freedom in job and IT training?

6. Social Technologies “Values-Mapped Web, Groupnets, and Wikinomics” Acceleration Studies Foundation A 501(c)(3) Nonprofit 6. Social Technologies “Values-Mapped Web, Groupnets, and Wikinomics” Acceleration Studies Foundation A 501(c)(3) Nonprofit - Social Freedoms and Privacy Evidence-Based Behavior Values-Mapped Web (Valuecosm) Groupnets (Learning, Perf. , Therapy) Wikinomics & Gamification (Coll. Intell. ) Lessig 2004 Inglehart-Welzel Cultural Values Map Page 2008 Shirky 2011 Nissenbaum 2009 Why Groupnets Will Help Criminals and the Mentally Ill: There are 50 X More Normals than Those Who Need Help. Leader’s Challenge Los Angeles New York Palo Alto § How can you facilitate Knowledge Creation, Knowledge Management, Ad-hoc Teams, Ideation, Strategy, Critique, Innovation, and a DIY, Entrepreneurial ethic in your org? How do you make it more freedom oriented and evidence-based?

7. Health Technologies “Quantified, Groupnet, Digital Health & Erooms Law” Acceleration Studies Foundation A 7. Health Technologies “Quantified, Groupnet, Digital Health & Erooms Law” Acceleration Studies Foundation A 501(c)(3) Nonprofit - Quantified and Groupnet Health Digital Wellness and Longevity Public Health and Disease Control Medical Biotech, Implants, HMIs Big Pharma and Molecular Medicine Topol 2011 Angell 2004 Eroom’s Law (Moore’s Backwards): Number of new FDA-approved drugs per $US Billion of R&D has halved every 9 years since 1950. Wearable & Implantable Sensors for Addiction Medicine • Exist today (insulin pumps) • Allows State Provision of Illicit Drugs • Medically Monitored Tapering • Nausea Option for Behavior Change Dexcom Gluc. Monitor 2010 • Eliminates an 800 B Criminal Industry Leader’s Challenge § How digital, quantified and networked is your health and wellness system and education? What incentives do you provide your team for healthy outcomes? What are you doing for diseases of affluence (obesity, CHD, addiction, ADHD)? Los Angeles New York Palo Alto the decline in pharmaceutical R&D efficiency, Scannell et. al. , Nat. Revs Drug Discovery 11, 191 -200 (2012) Diagnosing

8. Economic Technologies “Tech Productivity, Wealth, Creative Destruction” Acceleration Studies Foundation A 501(c)(3) Nonprofit 8. Economic Technologies “Tech Productivity, Wealth, Creative Destruction” Acceleration Studies Foundation A 501(c)(3) Nonprofit - Accel. Technical Productivity (TP) is 70% of GDP Growth* - Labor Productiv. is 20%. Finance is 10% of GDP Growth* - US Leads in Freedom, Entrepreneurship, Innovation - US Will Keep Same Ratio (25%) of Global GWP Pie - If We Moderate Economic Inequality, Have Fair Incentives Toffler 2006 Lovins 2011 Stack 2013 GDP Per Capita Western Europe 1000 -2000 C. E. Leader’s Challenge § In Econ Downcycle, how can you grow critical product or service performance while also cutting operating costs 20% this year? How to get everyone knowing and growing your tech productivity? Labor and finance productivity? Los Angeles New York Palo Alto *Robert Solow’s Neo-Classical Economic Growth Model, 1987, Wikipedia.

9. Political Technologies “Represent. , Shrinking Knowl, Access, Wealth Gaps” Acceleration Studies Foundation A 9. Political Technologies “Represent. , Shrinking Knowl, Access, Wealth Gaps” Acceleration Studies Foundation A 501(c)(3) Nonprofit - Adequate Political Capacity & Military Power - Adequate Political Freedom and Representation - Fair Rules and Laws, Sound Fiscal Mgmt - Shrinking Disconnectedness (Barnett’s Gap) - Shrinking Rich-Poor Divide (Kuznet’s Gap) Barnett 2005 Democratic-Plutocratic Pendulum Economic Kuznets Curve Acemoglu 2012 Environmental Kuznets Curve Leader’s Challenge Los Angeles New York Palo Alto § How can you get your team more represented, invested, and empowered to make change? How meritocratic and fair are your policies? What is the size of your internal pay and benefits gap? 10 X, 50 X? 500 X?

10. Security Technologies “Transparency, Simulations, and Immunity” Acceleration Studies Foundation A 501(c)(3) Nonprofit - 10. Security Technologies “Transparency, Simulations, and Immunity” Acceleration Studies Foundation A 501(c)(3) Nonprofit - ISR, Reciprocal Transparency (Anti-Corruption) Physical Security and Cybersecurity (Anti-Crime) Machine Ethics and Autonomy Simulations and Red Teams Redundancy, Resilience, & Immunity (Antifragility) Brin 1998 “Top Down” vs “Bottom Up” Transparency Simulations & Red Teams Herman 2008 Schwartz 2012 Leader’s Challenge Los Angeles New York Palo Alto § How can you empower and increase the bottom up (95%) monitoring and transparency (sousveillance) by your team and stakeholders? How can you simulate disruptions, problems, and opportunities ahead? Have strategies ready to go in case of crisis (danger/opportunity)?

Leadership Strategies Innovation, Management, Foresight Leadership Strategies Innovation, Management, Foresight

Good Self-Management Allows Great People Management Acceleration Studies Foundation - Self-Diagnosis comes before Self-Management Good Self-Management Allows Great People Management Acceleration Studies Foundation - Self-Diagnosis comes before Self-Management A 501(c)(3) Nonprofit - Self-Management improves People Management Los Angeles New York Palo Alto © 2013 Accelerating. org

Cognitive Diversity: Combat Bias with Multibiasing, and Open Communication Acceleration Studies Foundation A 501(c)(3) Cognitive Diversity: Combat Bias with Multibiasing, and Open Communication Acceleration Studies Foundation A 501(c)(3) Nonprofit “You can’t get an unbiased education, so the next best thing is a multibiased one. ” – Buckminster Fuller Build cognitively diverse, strengths diverse teams. Measure for strengths diversity. Page is Prof. of Complex Systems, U. Michigan Los Angeles New York Palo Alto Rath is at Gallup “Don’t expect what you don’t inspect. ” – Lou Gerstner

Knowledge Mgmt, Ideation, and Innovation Platforms Now Critical Solvers Problems Acceleration Studies Foundation Problem-Solving Knowledge Mgmt, Ideation, and Innovation Platforms Now Critical Solvers Problems Acceleration Studies Foundation Problem-Solving Marketplaces A 501(c)(3) Nonprofit http: //usnwc. libguides. com Popular Guides: RMA, Cyberwarfare, LOAC Benefit-Cost Analysis to Relatively Rank Ideas Started in 2005. 3 clearance levels. Los Angeles New York Palo Alto Those submitting ideas need: 1. Leadership by Example 2. Manager Support and Incentive (Institutional support can be nonexistent!) 3. Facilitated Exercises, “Innovation Games, ” equivalent of Wargames. 4. Benefit-Cost Analysis at the end. Innovation is 95% bottom up.

We are Good at Prediction, and Will Get Even Better Leaders Need to Do We are Good at Prediction, and Will Get Even Better Leaders Need to Do It More Acceleration Studies Foundation A 501(c)(3) Nonprofit After convincing ourselves that developmental futures are predictable, our next prediction problems are deception, bias and understanding probability. Quantitative models help, but numeracy is no guarantee of accuracy. We are biased to value confidence over uncertainty. We need less confidence and more uncertainty for greater accuracy. National Intell. Council, 2012 “We do not seek to predict the future – which would be an impossible feat. ” Los Angeles Wrong! New York Palo Alto Kahneman & Tversky, 2010 Forecasting Bias Silver, 2012 Forecasting Uncertainty Thompson, 2012 Prediction Platforms

Prediction Teams: Good Judgment Project Acceleration Studies Foundation A 501(c)(3) Nonprofit Los Angeles New Prediction Teams: Good Judgment Project Acceleration Studies Foundation A 501(c)(3) Nonprofit Los Angeles New York Palo Alto Philip Tetlock, UC Berkeley, U Penn, IARPA. Started with 3, 000 forecasters Year 1 (2011). Second year, took top 60 performers and randomly assigned them into five teams of 12 each. These “super forecasters” also delivered a farabove-average performance in Year 2. Apparently, forecasting skill cannot only be taught, it can be replicated Tetlock, 2006 http: //www. nytimes. com/2013/03/22/opinion/brooks-forecasting-fox. html

Dator’s “Four Futures”: Four Classic Growth Scenarios Acceleration Studies Foundation A 501(c)(3) Nonprofit Exponential Dator’s “Four Futures”: Four Classic Growth Scenarios Acceleration Studies Foundation A 501(c)(3) Nonprofit Exponential (Biz As Usual) Four Basic Stories/Components of Change Los Angeles New York Perspectives in Cross-Cultural Psychology, Jim Dator, Academic Press, 1979 Palo Alto © 2010 Accelerating. org

Innovation: Procurement Strategies Acceleration Studies Foundation A 501(c)(3) Nonprofit Unpopular Truths: • Small firms Innovation: Procurement Strategies Acceleration Studies Foundation A 501(c)(3) Nonprofit Unpopular Truths: • Small firms are much more Innovative than large firms. • Do. D Acquisitions Programs have been going backwards in Speed to Capability since 1950’s. • Tech companies and asymmetric actors have made exponential gains in Speed to Capability at same time. Small firms innovate best. Lessons: • “Speed to Capability” is the critical performance measure for all Do. D procurement programs. Lower must die. • Procurement must include diversity (small firms). • Diversity needs periodic culling or it gets wasteful. • DARPA, ONR, SPAWAR, NAVAIR, NAVSEA, etc. need their own competitions and innovation platforms. Just as true in the Example: Predator MQ-1. First prototype developed on DARPA defense industry. contract (1984) by Leading Systems Inc. , Abraham Karen, Israeli Air Force chief designer and US immigrant. LSI went bankrupt 1990, bought by Gen. Atomics. LSI did all primary innov. Common story. Los Angeles New York We Won’t Get What We Don’t Measure, Marv Langston, Former US Deputy Asst. Sec. of Defense, Dec 2012. Palo Alto

How Do You Build Your Best Small, Expert Teams? How Do You Keep Your How Do You Build Your Best Small, Expert Teams? How Do You Keep Your Suppliers Competitive? Acceleration Studies Foundation A 501(c)(3) Nonprofit Small Teams can: -- Rapidly innovate and adapt -- Operate below the radar (stealth) -- Have superior urgency and purpose -- Ignore convention and pursue vision -- Get hand-picked excellence and resources -- Be expendable, experimental, exploratory Supply Management Excellence: -- Learn from Industry Benchmarks -- Large and Small Suppliers -- Suppliers Deliver Overlapping Functions -- Performance-Based Budgets -- End-Client Feedback Drives Metrics Los Angeles -- Balance Supplier Pruning and Redundancy New York Palo Alto

DARPA and Google: Client-Centric, Network-Centric Models for Tech Innovation and Technical Intelligence Acceleration Studies DARPA and Google: Client-Centric, Network-Centric Models for Tech Innovation and Technical Intelligence Acceleration Studies Foundation A 501(c)(3) Nonprofit DARPA • Orientation to Radical Innovation • Decent Technical Intelligence • Autonomy and Freedom • Acceptance and Review of Failure • Small and Flexible Units • Flat (3 level) Organization • Constant Talent Rotation (4 -6 yr terms) Belfiore 2009 Google adds. . • Measurement Culture • Feedback/Learning Culture • Analysis/Intelligence Culture • Client (End-User) Orientation • Automation Orientation • Network/Platform-Centric (Tools first) Girard 2009 Los Angeles New York Palo Alto Google’s R&D budget is $6 B for 2012, DARPA’s is $3 B. Top 20 IT firms R&D budget >$30 B. “It’s a COTS World. ”

Discussion What Do You Think? accelerating. org/slides | @johnmsmart Discussion What Do You Think? accelerating. org/slides | @johnmsmart