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Myths about technological change
 

Myths about technological change

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These slides present seven myths of technology change and the reality for each of them. These seven myths are: 1) Performance improvements follow S-curve; 2) Slow down in old technology causes search ...

These slides present seven myths of technology change and the reality for each of them. These seven myths are: 1) Performance improvements follow S-curve; 2) Slow down in old technology causes search for new technology; 3)
Costs fall as cumulative production rises; 4) Demand drives improvements; 5) Media attention means a technology will diffuse; 6) We can’t analyze the timing of new technologies; 7) The market doesn’t work.

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    Myths about technological change Myths about technological change Presentation Transcript

    • Seven Myths About Technology Change A/Prof Jeffrey Funk Division of Engineering and Technology Management National University of SingaporeMore details can be found in1) What Drives Exponential Improvements? California Management Review, May 20132) Technology Change and the Rise of New Industries, book from Stanford University Press, January 20133) Presentations on slideshare: http://www.slideshare.net/Funk98/presentations
    • Seven Myths About Technology Change Performance improvements follow S-curve Slow down in old technology causes search for new technology Costs fall as cumulative production rises Demand drives improvements Media attention means a technology will diffuse We can’t analyze the timing of new technologies The market doesn’t work
    • The Myth: Performance Improvements Follow S-Curves (Jumps and Diminishing Returns)Performance Emergence of New Technology Time
    • Where’s the S-Curve (e.g., Jumps) in Moore’s Law? You have seen Moore’s Law, Haven’t You? Moore’s Law for Microprocessors
    • Where’s the S-Curve in Magnetic Recording Density of Platters for Hard Disk Drives?Source: http://www.fgarciasanchez.es/thesisfelipe/node5.html
    • Where are the Jumps? Luminosity per watt (lm/W) of lights and displays Organic Transistors
    • Figure 2.5 Improvements in Coercivity of Magnetic Materials 100Coercivity (Oersted or Amps/Meter) SmCo MaBl PtCo Ferrites Alnico Alloys Steel 10 Trend Line For Samarium Cobalt Magnets General Trend Line 1 Where are the S-Curves? 0.1 1900 1910 1920 1930 1940 1950 1960 1970 1980 Computer Processing Speed
    • Seven Myths About Technology Change Performance improvements follow S-curve Slow down in old technology causes search for new technology Costs fall as cumulative production rises Demand drives improvements Media attention means a technology will diffuse We can’t analyze the timing of new technologies The market doesn’t work
    • The Myth: Slow Down in OldCauses Search for New Technology  Technologies exhibit diminishing returns and perhaps limits  As they experience diminishing returns, new technologies are searched for, found and developed  This causes the new technology to experience improvements, perhaps even jumps in performance
    • The Reality (1) For many technologies, limits, diminishing returns, and jumps are not clearly evident in time series (see previous figures and next slide for examples) This suggests that new technologies are searched for, targeted, and developed long before old technologies exhibit limits or even diminishing returns One reason is that while physical limits do exist, apparently few have been reached
    • Where is evidence of limits leading to search for new technology? Organic Transistors
    • The Reality (2) Even if diminishing returns exist, development of new technology begins much earlier Why? There are many technologies and many potential applications for them These technologies are targeted and pursued in decentralized manner ◦ Millions of research scientists and engineers ◦ They independently pursue many technologies long before commercialization occurs  Look for new types of materials  Consider many applications
    • The Reality (3) The result is that improvement curves are relatively independent of each other Each technology is pursued as opportunity, both individual and organizational opportunity Rates of improvement reflect ◦ ability to find improvements ◦ perceptions about the potential for improvements Scientists and engineers pursue these technologies in order to obtain publications, patents, and perhaps fame
    • The Reality (3) In any case, if we try to change distribution of research effort ◦ We should understand different technologies, their rates of improvements, and their potential for further improvements Independent of application, we should fund those technologies with ◦ greatest rates of improvement and ◦ greater potential for improvements than do others But in doing so we should fund many technologies and many forms of them
    • Seven Myths About Technology Change Performance improvements follow S-curve Slow down in old technology causes search for new technology Costs fall as cumulative production rises Demand drives improvements Media attention means a technology will diffuse We can’t analyze the timing of new technologies The market doesn’t work
    • Myth: Cumulative Production Drives Cost Reductions  Costs fall as cumulative production grows in learning or experience curve ◦ One suggested mechanism is that automated manufacturing equipment is introduced, modified, and organized into flow lines  But learning curve ◦ Can’t be used until production has begun ◦ Assumes all components are unique to new product ◦ Doesn’t help us understand why some technologies experience more improvements than do other technologies ◦ Ignores work done in laboratories
    • Reality: What Drives Improvements?  Creating materials (and associated processes) that better exploit physical phenomena  Geometrical scaling ◦ Reductions in scale: e.g., integrated circuits (ICs), magnetic storage, MEMS, bio-electronic ICs ◦ Increases in scale: e.g., larger production equipment, engines, oil tankers  Some technologies directly experience improvements while others indirectly experience them through improvements in “components” ◦ Computers and other electronic systems ◦ Telecommunication systems
    • Note the names of materials Luminosity per watt (lm/W) of lights and displays Organic Transistors
    • Figure 2.5 Improvements in Coercivity of Magnetic Materials 100Coercivity (Oersted or Amps/Meter) SmCo MaBl PtCo Ferrites Alnico Alloys Steel 10 Trend Line For Samarium Cobalt Magnets General Trend Line 1 Note the names of materials 0.1 1900 1910 1920 1930 1940 1950 1960 1970 1980
    • Figure 2.6 Improvements in Energy Product of Magnetic Materials Figure 2.9 Reductions in Optical Loss of Optical Fiber 1000Energy Product (Mega-Gauss Oersteds) 100 steel 100 alnico alloys General Optical Loss (db/km) Trend Line 10 fine particles 10 rare earths 1 1 0.1 Note the names of materials 0.1 0.01 1900 1920 1940 1960 1980 2000 1960 1965 1970 1975 1980 1985 Critical Temperature for Superconductors
    • New Classes of Materials Enable Improvements over Long Time ScaleTechnology Sub- Dimensions of Different Classes of MaterialsDomain Technology measureEnergy Lighting Light intensity per unit Candle wax, gas, carbon and tungsten filaments,Trans- cost semiconductor and organic materials for LEDsformation LEDs Luminosity per Watt Group III-V, IV-IV, and II-VI semiconductors Organic LEDs Small molecules, polymers, phosphorescent materials Solar Cells Power output per unit Silicon, Gallium Arsenide, Cadmium Telluride, cost Cadmium Indium Gallium Selenide, Dye-Sensitized, OrganicEnergy storage Batteries Energy stored per unit Lead acid, Nickel Cadmium, Nickel Metal Hydride, volume, mass or cost Lithium Polymer, Lithium-ion Capacitors Carbons, polymers, metal oxides, ruthenium oxide, ionic liquids Flywheels Stone, steel, glass, carbon fibersInformation Organic Mobility (cm2/ Volt- Polythiophenes, thiophene oligomers, polymers,Trans- Transistors seconds) hthalocyanines, heteroacenes, tetrathiafulvalenes,formation perylene diimides naphthalene diimides, acenes, C60Living Biological U.S. corn output per Open pollinated, double cross, single cross, biotechOrganisms transfor- area GMO mationMaterials Load Bearing Strength to weight ratio Iron, Steel, Composites, Carbon Fibers Magnetic Strength Steel/Alnico Alloys, Fine particles, Rare earths Coercivity Steel/Alnico Alloys, SmCo, PtCo, MaBi, Ferrites,
    • Reality: What Drives Improvements?  Creating materials (and associated processes) that better exploit physical phenomena  Geometrical scaling ◦ Reductions in scale: e.g., integrated circuits (ICs), magnetic storage, MEMS, bio-electronic ICs ◦ Increases in scale: e.g., larger production equipment, engines, oil tankers  Some technologies directly experience improvements while others indirectly experience them through improvements in “components” ◦ Computers and other electronic systems ◦ Telecommunication systems
    • Figure 2. Declining Feature Size 100 Moore’s Law for 10 Microprocessors Micrometers (Microns) Feature length 1 Junction Depth 0.1 Gate Oxide Thickness 0.01 0.001 1960 1965 1970 1975 1980 1985 1990 1995 2000Source: (ONeil, 2003) Year
    • Reductions in Scale Drive Improvements in Capacity Magnetic Recording Density
    • Other Technologies Benefit fromReductions in Scale MEMS (micro-electronic mechanical systems) for many applications ◦ Gyroscopes, resonators, micro-mirrors ◦ Photonics, ink jet nozzles for printers, micro- gas analyzers Bio-electronic ICs for many applications ◦ Point-of-care diagnostics, drug delivery ◦ chips embedded in clothing, body, etc. DNA sequencing Nanotechnology
    • Reality: What Drives Improvements? Creating materials (and associated processes) that better exploit physical phenomena Geometrical scaling ◦ Reductions in scale: e.g., integrated circuits (ICs), magnetic storage, MEMS, bio-electronic ICs ◦ Increases in scale: e.g., larger production equipment, engines, oil tankers Some technologies directly experience improvements while others indirectly experience them through improvements in “components” ◦ Computers and other electronic systems ◦ Telecommunication systems
    • Scaling in Production Equipment We all know about economies of scale ◦ But some products benefit from economies of scale more than do others ◦ Why? Some products benefit from increases in scale of production equipment more than do others Largest benefits for ◦ chemicals, other continuous flow equipment ◦ furnaces and smelters Smaller benefits for discrete parts equipment But also large benefits for ◦ Semiconductor wafers, liquid crystal display (LCD), and solar cell manufacturing equipment
    • Production of Liquids or Gasesin a Continuous Flow Factory Liquids and gases are mixed, separated, heated, cooled, filtered, settled, extracted, distilled, and dried in pipes and reaction vessels Pipes ◦ Cost is function of surface area (or radius) ◦ Output is function of volume (or radius squared) Reaction vessels ◦ Cost is function of surface area (or radius squared) ◦ Output is function of volume (radius cubed)
    • Example of Benefits of Larger Scale: EnginesCost of cylinderor piston is functionof cylinder’s surfacearea (πDH) Height of cylinderOutput of engine (H)is function ofCylinder/piston’svolume (πD2H/4)Result: output risesfaster than costs asdiameter is increased Diameter of cylinder (D)
    • Relative Price Per Output Falls as Scale Increases 10000 Oil Tanker: Steam Engine (in 1000s of tons HP) Maximum scale: Smallest was 1.3 M HP 1807 tons 1000 Marine Engine Commercial aircraftPrice per Output Largest is Smallest one had 90,000 HP 12 passengers Relative 100 Aluminum Electric Power (1000s of Plants (in MW); much amps) smaller ones built 10 Chemical Plant: LCD Mfg Equip: 1000s of tons of ethylene Largest panel size is per year; much smaller plants 16 square meters built 1 0.1 1 10 100 1000 10000 Output (Scale)
    • Reality: What Drives Improvements? Creating materials (and associated processes) that better exploit physical phenomena Geometrical scaling ◦ Reductions in scale: e.g., integrated circuits (ICs), magnetic storage, MEMS, bio-electronic ICs ◦ Increases in scale: e.g., larger production equipment, engines, oil tankers Some technologies directly experience improvements while others indirectly experience them through improvements in “components” ◦ Computers and other electronic systems ◦ Telecommunication systems
    • Computer Processing Speed: Driven by Improvements in ICs
    • Bandwidth/Speeds for Wireline Telecommunication: Driven by improvements in ICs, optical fiber, lasers, and photosensorsSource: Koh H and Magee C, 20016, A function approach for studying technological progress: application toInformation technology, Technological Forecasting & Social Change 73: 1061-1983.
    • ICs Drive Improvements in Many Systems Computers (e.g., tablet computers) networks of RFID tags, smart dust, and other sensors Cloud/utility computing Internet content (e.g., mashups, 3D content, video conferencing) Human-computer interface (touch, gesture, neural) Mobile phones and mobile phone systems (e.g., 4G, 5G, cognitive radio) Autonomous vehicles Holographic display systems
    • Seven Myths About Technology Change Performance improvements follow S-curve Slow down in old technology causes search for new technology Costs fall as cumulative production rises Demand drives improvements Media attention means a technology will diffuse We can’t analyze the timing of new technologies The market doesn’t work
    • The Myth: Demand Drives Improvements Demand drives cumulative production Cumulative production drives improvements ◦ Automated manufacturing equipment is introduced, modified, and organized into flow lines ◦ Better products and processes are introduced Implications: stimulating demand will lead to cost reductions. This is one reason why many governments subsidize the introduction of clean energy more than they subsidize R&D spending Clayton Christensen’s theory of disruptive innovation also implies that increases in demand will lead to reductions in cost and improvements in performance
    • But…… Many improvements occur without product demand ◦ Scientists and engineers create materials to exploit physical phenomena long before technology is commercialized Even with scaling, demand is indirect driver ◦ Demand does provide money for increasing scale of production equipment or reducing scale of features on ICs and magnetic storage ◦ But often complementary technologies such as new equipment are the bottleneck And for some increases in scale, they reduce rates of increase in unit cumulative production (e.g., engines)
    • Many also Argue that Increases in Demand Lead to Accelerations in Performance During First Half of S-CurvePerformance Accelerations in Rates of Improvement Time
    • But….. Few performance curves display an acceleration, i.e., jumps, during the first half of an S-curve What about the few that do? Do the accelerations reflect increases in demand? Let’s look at example of superconductors
    • Rate of improvement for maximumcritical temperature ofsuperconductors experiencedacceleration in mid-1980sBut what caused the acceleration?Was it increases in demand forsuperconducting materials?No!It was because scientists foundnew and unexpected class(ceramics) of superconductingmaterials (later, red, black, green,purple)We don’t need more demand! Weneed scientists and engineers tolook for and find new classes ofmaterials!
    • What Does “Open Innovation” Tell Us About the Role of Demand?  In the old world of closed innovation, ◦ vertically integrated firms developed components for their systems ◦ thus demand for systems and components were somewhat linked  In the new world of open innovation, ◦ different firms develop systems and components, i.e., vertical disintegration ◦ Most firms develop components for multiple systems ◦ Thus weaker link between demand for specific systems and componentsSource: Henry Chesbrough, Open Innovation: The New Imperative for Creating and Profiting from Technology
    • What Does Open Innovation Tell Us About the Role of Demand? (2)  Open innovation in R&D is extending the vertical disintegration backwards into research  R&D is now conducted in a very decentralized world, millions of research scientists and engineers now exist  Firms (and professors) do research even when final product demand doesn’t exist ◦ Government funding, wealthy entrepreneurs, venture capital, patent protection, and development prizes support this researchSource: Henry Chesbrough, Open Innovation: The New Imperative for Creating and Profiting from Technology
    • Seven Myths About Technology Change Performance improvements follow S-curve Slow down in old technology causes search for new technology Costs fall as cumulative production rises Demand drives improvements Media attention means a technology will diffuse We can’t analyze the timing of new technologies The market doesn’t work
    • The most dangerous “model” is hypeVisibility is not a signal of growthMany technologies never experience diffusion, even if they are visible
    • For Example, Lots of Hype about Energy storage for vehicles Smart grid Wind turbines Solar cells Nanotechnology And many other technologies
    • But which ones will succeed? Which technologies will become economically feasible and thus diffuse? It largely depends on the rate of improvement ◦ Fast rates of improvement increase the chances that a new technology will become economically feasible Fast rates of improvement reflect ◦ Creation of new materials ◦ Technologies that benefit from changes in scale and the implementation of these changes in scale ◦ Technologies that benefit from reductions in scale have particularly rapid rates of improvement
    • For Example, Consider MobilePhones? (1) In early 1980s, one study concluded there would be about 1 million mobile phones in use by 2000 Some would say we under estimated the need for mobile phones I say we under estimated the impact of Moore’s Law on the cost of mobile phones Lesson: pay attention to rates of improvement and not to hype (or lack of hype)
    • Mobile Phones? (2) In early 2000s, many believed that location services were a huge market Until recently no one used these services Until recently some would say we overestimated the need for such services I say we ◦ over estimated the impact of Moore’s Law on the cost of such services for short term ◦ under estimated the impact for long term Lesson: pay attention to rates of improvement and not to hype
    • Seven Myths About Technology Change Performance improvements follow S-curve Slow down in old technology causes search for new technology Costs fall as cumulative production rises Demand drives improvements Media attention means a technology will diffuse We can’t analyze the timing of new technologies The market doesn’t work
    • Myth: We can’t analyze the timingof new technologies, because…. New technologies just appear like bolts of lighting Someone finds a technology that no one noticed before Someone comes up with new concept or new business model and “wallah” Some other form of “unexpected event” occurs
    • The Reality (1) Literally thousands of new technologies are being developed right now ◦ the concepts have been understood for years ◦ champions exist for every one of them ◦ these champions believe these new technologies will become economically feasible Some of these technologies are experiencing more rapid improvements than others
    • The Reality (2) Which ones are experiencing rapid improvements? Of course, unexpected events do occur…but we want to be the ones who cause these unexpected events In the end, everything is about probability, what are the most probable scenarios?
    • Analyzing the Timing of NewTechnologies If components drive the improvements in performance or cost of new technology, ◦ We must understand the components and their rates of improvement If we had understood the importance of ICs, even in the 1970s and 1980s, ◦ We would not have been surprised by success of personal computers, mobile phones, and similar technologies
    • Analyzing the Timing of NewTechnologies (2) For technologies that benefit from finding materials that better exploit physical phenomena, ◦ we can use the rates of improvement to better understand the expected changes in performance, cost, and thus economic feasibility over time ◦ if many new classes of materials have been found, this increases the chances that some form of this technology will become economically feasible
    • Analyzing the Timing of NewTechnologies (3) For technologies that benefit from changes in scale ◦ we can use actual rates of improvement and role of supporting components in these changes in scale to better understand expected changes in performance, cost, and thus economic feasibility over time ◦ For new technologies for which little data is available, we can use data from similar systems to analyze the expected benefits from changes in scale
    • Analyzing the Timing of NewTechnologies (4) Finally, demand does impact on costs and prices. Increases in demand can ◦ reduce the development costs per unit ◦ enable larger volumes and thus larger production equipment But, manual assembly and some production “equipment” benefit little from increases in scale ◦ e.g., assemblers of iPhones! And increases in demand are the last factor and often the least important
    • Seven Myths About Technology Change Performance improvements follow S-curve Slow down in old technology causes search for new technology Costs fall as cumulative production rises Demand drives improvements Media attention means a technology will diffuse We can’t analyze the timing of new technologies The market doesn’t work
    • The Myth: The Market Doesn’tWork Markets are very short-sighted New technologies will not be developed unless there is strong government intervention Governments must target new technologies in response to specific problems ◦ State the problems ◦ List potential solutions ◦ Fund and develop the potential solutions
    • The Reality Markets work reasonably well Markets have replaced hierarchies (i.e., vertical disintegration) to a large extent even in R&D (i.e., open innovation) Firms develop systems, components, and materials for those components even when ◦ the system for the components and materials are not clear ◦ and thus potential applications and demand for them are not clear
    • The Weakness of Markets They under invest in R&D, particularly research They under invest because ◦ there are large uncertainties ◦ in addition to uncertainties, information slips out and thus firms can’t appropriate all the benefits from research
    • What should governments do? Government policies should support research, perhaps much stronger than they currently do These policies should reflect how technology change occurs and not fall victim to the many “myths” The worst policies involve targeting new technologies in response to specific problems as if one is the “emperor of the universe” ◦ State the problems ◦ List potential solutions ◦ Fund and develop them
    • What should governments do? (2) Government policies should support technologies that ◦ are experiencing rapid improvements or ◦ have the potential for rapid improvements Our research helps identify these technologies ◦ Ones that benefit from creating materials to…..  if many new classes of materials are being found, improvements will probably follow ◦ Ones that benefit from reductions in scale  these technologies experience rapid rates of improvement
    • Final Words Myths about technology change reduce our ability to develop new technology Overcoming these myths can help us ◦ implement better strategies and policies ◦ more effectively find technologies that are or will become economically feasible