Business Information Technology- Assignment
AJ-773
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Information Systems: A Manager’s Guide to Harnessing Technology V 3.0
By John Gallaugher
Chapter 5
Moore’s Law and More: Fast, Cheap Computing, Disruptive Innovation, and What This Means for the Manager
Learning objectives
Define Moore’s Law and understand the approximate rate of advancement for other technologies, including magnetic storage (disk drives) and telecommunications (fiber-optic transmission).
Understand how the price elasticity associated with faster and cheaper technologies opens new markets, creates new opportunities for firms and society, and can catalyze industry disruption.
Recognize and define various terms for measuring data capacity.
Consider the managerial implication of faster and cheaper computing on areas such as strategic planning, inventory, and accounting.
Some Definitions
MOORE’S LAW
Chip performance per dollar doubles every eighteen months.
MICROPROCESSOR
Part of the computer that executes the instructions of a computer program .
RANDOM ACCESS MEMORY (RAM)
Fast, chip-based volatile storage in a computing device.
VOLATILE MEMORY
Storage that is wiped clean when power is cut off from a device.
SOME DEFINITIONS
NONVOLATILE MEMORY
Storage that retains data even when powered down.
FLASH MEMORY
Nonvolatile, chip-based storage.
SOLID STATE ELECTRONICS
Semiconductor-based devices.
SEMICONDUCTORS
Substance such as silicon dioxide used inside most computer chips that is capable of enabling and inhibiting the flow of electricity.
OPTICAL FIBER LINE
High-speed glass or plastic-lined networking cable used in telecommunications.
Advancing rates of technology
Change in Technological Capabilities by Year
Optical Fiber (bits per second) 0 1 2 3 4 5 6 1 2.5 6.35 16 40.299999999999997 101.59 256 Data Storage (bits per square inch) 0 1 2 3 4 5 6 1 2 4 8 16 32 64 Moore's Law (number of transistors 0 1 2 3 4 5 6 1 1.68 2.82 4.76 8 13.45 22.63
Evolution of the technological landscape
Price elasticity: Rate at which the demand for a product or service fluctuates with price change.
Evolving waves of computing:
1960s - Mainframe computers
1970s - Minicomputers
1980s - PCs
1990s - Internet computing
2000s - Smartphone revolution
2010s - Pervasive computing:
Vision of embedding low-cost sensors, processors, and communication into a wide array of products and the environment.
Allow a vast network to collect data, analyze input, and automatically coordinate collective action.
Learning Objectives
Describe why Moore’s Law continues to advance and discuss the physical limitations of this advancement.
Name and describe various technologies that may extend the life of Moore’s Law.
Discuss the limitations of each of these approaches.
The Death of Moore’s Law?
Moore’s Law is possible because the distance between the pathways inside silicon chips gets smaller with each successive generation.
Fabs: Semiconductor fabrication facilities
Silicon wafer: Thin, circular slice of material used to create semiconductor device
Packing pathways tightly together creates problems associated with size, heat, and power.
Chip starts to melt when the processor gets smaller.
Need to cool modern data centers draws a lot of power and that costs a lot of money.
Quantum tunneling kicks in when chips get smaller .
Buying time
Multicore microprocessors: Contain two or more calculating processor cores on the same piece of silicon.
Multicore chips outperform a single speedy chip, while running cooler and drawing less power.
Now mainstream, most PCs and laptops sold have at least a two-core (dual-core) processor.
Can run older software written for single-brain chips by using only one core at a time.
Firms are radically boosting speed and efficiency of chips.
Taking chips from being paper-flat devices to built-up 3-D affairs.
Transistors: Super-tiny on-off switches in a chip that work collectively to calculate or store things in memory.
Learning objectives
Understand the differences between supercomputing, grid computing, cluster computing, and cloud computing.
Describe how grid computing can transform the economics of supercomputing.
Recognize that these technologies provide the backbone of remote computing resources used in cloud computing.
Understand the characteristics of problems that are and are not well-suited for parallel processing found in modern supercomputing, grid computing, cluster computing, and multi-core processors.
Discuss how network latency places limits on offloading computing to the cloud.
A melding of minds
Supercomputers: Computers that are among the fastest of any in the world at the time of their introduction.
Supercomputing was once considered the domain of governments and high-end research labs.
Modern supercomputing is done by massively parallel processing: Computers designed with many microprocessors that work together, simultaneously, to solve problems.
Grid computing: Uses special software to enable several computers to work together on a common problem as if they were a massively parallel supercomputer.
Cluster computing: Connecting server computers via software and networking so that their resources can be used to collectively solve computing tasks.
A melding of minds
Multicore, massively parallel, grid, and cluster computing are all related.
Each attempts to lash together multiple computing devices so that they can work together to solve problems.
Software as a service (SaaS): Form of cloud computing where a firm subscribes to a third party software and receives a service that is delivered online.
Cloud computing: Replacing computing resources with services provided over the Internet.
Server farms: Massive network of computer servers running software to coordinate their collective use.
Latency: Delay in networking and data transfer speeds.
Low latency systems are faster systems.
Moore’s Law will likely hit its physical limit soon, but still-experimental quantum computing could make computers more powerful.
Learning objectives
Identify the two characteristics of disruptive innovations.
Understand why dominant firms often fail to capitalize on disruptive innovations.
Suggest techniques to identify potentially disruptive technologies and to effectively nurture their experimentation and development.
Characteristics of Disruptive Technologies
They come to market with a set of performance attributes that existing customers do not value.
Over time the performance attributes improve to the point where they invade established markets.
Product Performance
Time
Performance demanded at the high end of the market
Performance demanded at the low end of the market
Incumbent market leader
Disruptive innovation
Source: Adapted from C. Christensen, The Innovator’s Dilemma. Harvard Business School Press, 2013.
Why big firms fail
Failure to see disruptive innovations as a threat.
Reason: They do not dedicate resources to developing the potential technology since these markets do not look attractive.
Creates blindness by an otherwise rational focus on customer demands and financial performance.
Start-ups amass expertise quickly.
Big firms are forced to play catch-up.
Few ever close the gap with the new leaders.
Recognizing Potentially Disruptive Innovations
Remove short-sighted, customer-focused, and bottom-line-obsessed blinders.
Have conversations with those on the experimental edge of advancements.
Increase conversations across product groups and between managers and technologists.
If employees are quitting to join a technology, it might be worth considering.
When a Potential Disruptor is Spotted
Build a portfolio of options on emerging technologies, investing in firms, start-ups, or internal efforts.
Focus solely on what may or may not turn out to be the next big thing.
Options give the firm the right to continue and increase funding as a technology shows promise.
If a firm has a stake in a start-up, it may consider acquiring the firm.
If it supports a separate division, it can invest more resources if that division shows promise.
Encourage new market and technology development.
Focus while isolating the firm from a creosote bush-type of resource sapping from potentially competing cash-cow efforts.
Learning Objectives
Understand the magnitude of the environmental issues caused by rapidly obsolete, faster, and cheaper computing.
Explain the limitations of approaches attempting to tackle e-waste.
Understand the risks firms are exposed to when not fully considering the lifecycle of the products they sell or consume.
Ask questions that expose concerning ethical issues in a firm or partner’s products and processes, and that help the manager behave more responsibly.
E-waste
May be toxic since many components contain harmful materials such as lead, cadmium, and mercury.
It also contains small bits of increasingly valuable metals such as silver, platinum, and copper.
Requires recycling, which is extremely labor intensive.
Most of the waste is exported for recycling,
Discarded, often obsolete technology associated with negative externalities
E-waste
Managers must consider and plan for the waste created by their:
Products, services, and technology used by the organization.
Managers must audit disposal and recycling partners with the same vigor as their suppliers and other corporate partners.
