Distinctive IT Characteristics: Implications for Digital
Innovation and Value Creation
by Robert G. Fichman, 2014
Introduction
Information technology has diffused faster and farther than any other general purpose
technology in history, and along the way has produced an unprecedented stream of innovation
and resulting value creation for businesses and consumers. So what is it about IT that makes it
such a tremendous driver of innovation? There have been many prior technologies that have
transformed the economic landscape—the assembly line, electricity generation, and the
railroads to name just three. So how is IT fundamentally different from the technologies that
came before?
This Lecture Note answers this question by explaining three distinctive characteristics of IT:
(1) Moore's law, (2) digitalization and (3) network effects. If understanding what the
term digital innovation really means is the first big step towards thinking like a digital innovator,
then understanding how these characteristics make digital technologies different from other
general purpose technologies—and why this matters for innovation and value creation—is the
second big step.
Moore’s Law
In 1984, FedEx introduced a groundbreaking new service called ZapMail, which offered 2hour nationwide delivery of high quality document facsimiles for about $25 per document.
Five years before, the FedEx board had approved $400 million to create a proprietary
network of high resolution fax machines and transmission lines to support the service. At
that time, the value proposition seemed solid: the only alternative for same-day document
delivery was to use primitive 1st generation fax machines, which very few organizations
even owned. That’s because in the early 1980s, these machines cost thousands, produced
low resolution output, required special thermal paper to print on, and were agonizingly
slow—a single page took 6 minutes to fax. And back then long distance calls were 40c per
minute! Unfortunately for FedEx, the ZapMail launch bombed. The reason? In the 5 years it
took to build the infrastructure for the service, Moore's Law had caused dramatic
improvements in quality for commercial fax machines, and prices had plummeted. Because
of this improvements—and the strong positive network effects (see below) that come from
a large installed base of fax machines—ZapMail was introduced in a world where privatelyowned fax machines had become a viable substitute.
Strictly speaking, Moore’s Law refers to the doubling of the number of circuits on computer
chips every 18-24 months (see Figure 1). However, over time the meaning of the term has
been blurred, and it now means exponential improvements in the performance-per-dollar of
any computing component. Components subject to Moore’s Law include all semi-conductors
(microprocessors, RAM chips, flash drives (see diagram below)), hard disk drives, LCD
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monitors, and fiber-optic transmission equipment. All digital devices that incorporate these
components (computers, iPods, smartphones, fax machines, etc.) also benefit from this
exponential improvement process. That’s why today’s iPod Touch costs about as much as the
first digital music players introduced in the late 1990s, but holds 1000x as many songs, and also
plays videos, runs apps, surfs the net, etc. Moore’s Law has been observed for close to 50 years
now, and is expected to continue for at least 10 more.
Source: Wikipedia Commons
The most immediate result of Moore’s Law is, of course, tremendous value creation. The same
products can be produced for rapidly decreasing cost (e.g., the cost of flash drives has dropped
10-fold in just few years) and with rapidly increasing performance—and most of that benefit
goes to consumers. Also, innovative new products, services and business models are made
possible that were not cost-effective before (e.g., high quality digital cameras, free social media
sites).
Why didn’t FedEx executives foresee the threat that Moore’s Law represented to their ZapMail
business? It’s hard to know, but one likely reason is that exponential improvements aren’t that
noticeable until the process has reached a certain threshold. When a technology is going from
“awful” to “half as awful” to “one fourth as awful” that’s easy to overlook. But once a
technology has finally crossed that threshold from “bad” to “pretty good,” situation shifts
rapidly. The technology keeps right on getting twice as good every 18 months. When $300
digital music players went from 10 songs, to 20, to 40, that was nice for very early adopters, but
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was not enough to change the relationship of average people to their music. But by the time
the first iPod was launched it had become possible to put 1,000 songs on a pocket-sized
device—basically a whole music library—and that changed everything.
Digitalization
In 1999, twenty years after FedEx gave the go ahead to the ill-fated ZapMail, Shawn
Fanning, a Northeastern University undergrad, unleashed the music industry’s worst
nightmare. Tired of using clunky search engines to find digital music files on the Internet,
Fanning invented an easy-to-use peer-to-peer file sharing system called Napster. At the
time hardly anyone had heard of MP3s, the first standard for compressed digital audio. But
within a few years, free (and illegal) digital downloads had become the primary way many
people got their music, and music CDs sales began an inexorable slide. Today it’s estimated
that 16 songs are illegally traded for every legal music download at iTunes and other
legitimate sites.
Digitalization means taking content or processes that used to be primarily (or entirely) physical
or analog and transforming them to be primarily (or entirely) digital. Let’s start by talking about
digitizing content, which simply means taking content that used to be stored in traditional
formats (e.g., LP records, cassette tapes), and instead storing it as digital data (i.e., 1’s and 0’s).
So, instead of physical documents, 35mm film, LP records, and VHS movies, we now have digital
documents (e.g., MS Word, Adobe), digital images (JPEGs), digital music (MP3s), and digital
video (DVD, MPEG, TiVo).1
While digitalization is enabled by Moore’s law, it represents a potent force for innovation and
value creation in its own right. The most obvious advantage is that digital files can be perfectly
copied any number of times. And because of Moore’s law, the cost of storing and sharing those
copies has dropped close to zero. One 3-megabyte digital song now consumes far less than one
penny’s worth of hard drive space, and can be transmitted in seconds over the Internet for free.
Today’s 16 gigabyte flash cards can hold several thousand high resolution pictures but cost
about $10.
Just as important, digitalization of content has led to digital convergence, which means we no
longer need a different device (i.e., radio, TV, record player, tape player), to play each kind of
content. Any digital device has the potential to handle any kind of digital content. All it needs is
a way to read the content, and the right software to play it back. That’s why you can use the
same smartphone to make calls, send emails, take photos, listen to music and watch videos—
instead of carrying around a phone, a computer terminal, a camera, a music player and a video
player everywhere you go.
Digitalizationalso creates value by allowing content itself to ride Moore’s Law, making it ever
cheaper to store and transmit. But digitalization does much more than this. It also allows
content to be automatically analyzed and manipulated to correct errors or to improve quality.
Even more important, digital content can be automatically searched, indexed and crossreferenced to improve availability and shareability. Napster did nothing to reduce the cost of
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storing and transmitting music: what it did was make it easy to find. By making content easy to
find and acquire, digitalization enables the economics of the Long Tail.
The image at right depicts sales volumes
(vertical axis) for set of titles (e.g.,
books) put in order from highest volume
at the left) to lowest volume (to the
right. The “Long Tail” is the yellow part
of the curve.
The Long Tail
Source: Wikipedia Commons
The Long Tail refers to the many thousands of worthy—but less popular—books, songs and
movies that aren’t carried in stores, and aren’t shown in movie theaters or broadcast over the
airwaves, because demand is too low to justify use of those channels. But digitalization (of
content itself and of information about content) unleashes the value in the Long Tail. It
becomes economical to offer content that interests only a small percentage of consumers.
There’s virtually no limit to the number of titles that can be offered through online channels.
While a Barnes & Noble store gets 100% of its sales from the 130,000 unique titles it carries,
Amazon.com gets less than half of its book sales from its top 130,000 titles. That means over
half of Amazon’s book sales come from satisfying demand that otherwise would likely go
unfilled. While Blockbuster stores used to carry about 3,000 DVD titles, NetFlix.com now offers
over 100,000.
Although when people talk about digitalization they are usually talking about digitizing content,
we can also think about digitizing processes. This means taking a process that a firm previously
did manually or with physical machines, and turning part or all of that process over to
computers or other digital devices. The main effect of digitizing processes, aside from the
obvious efficiency gains, is to make them more flexible and tailorable. For example, in the past
decade banks digitized the process of handling check images for all their internal processes.
Instead of moving paper checks around, they scan the checks and move digital check images
around. Once this is done, it’s easy to go the further step to let customers deposit checks by
simply taking a picture of the check on their smartphones. In fact, much of the move towards
self-service has been made possible by digitizing processes.
Network Effects
In 1984, Apple Computer was on top of the world. They had just introduced the
revolutionary Apple Macintosh Computer, the first personal computer to have a graphical
user interface and a computer mouse for input. Before long, the Mac had also pioneered
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the concept of “plug and play” peripherals and multimedia support. But the Mac, despite its
obvious technical superiority, never got more than a 10% market share. Apple stock went
through major gyrations in the next decade, ending up about where it started. Meanwhile,
the stalwarts of the PC world—Microsoft and Intel—saw their sales and profits go up 100fold in this same 10 years. By 1997, Apple was on the verge of bankruptcy. If not for $150
million cash infusion by none other than Bill Gates—and the return of Apple savior Steven
Jobs to become CEO—the company would have almost certainly gone under.
What happened to the original Apple Mac? Put simply, it lost out to another standard (IBM PC)
that had much stronger network effects. Network effects means the benefit of technology use
increase with the size of the community of other users. This leads to virtuous cycles of adoption
where each round of adoption makes the technology even more attractive, which encourages
more adoption in the next round, and so forth.2
When the Mac came along, the IBM PC standard already had a very large network and
dominated the PC world. As a result, there was a much greater variety of software programs to
buy, and those programs could be sold more cheaply. Also, the large network drove down the
cost of components and peripherals for IBM standard PCs. So, for most people, the total
value of joining the IBM PC network (i.e., inherent value plus network benefits), was larger than
joining the small Mac network, despite the inherent superiority of the Mac.
Network effects can come from many sources. One key source is direct interactions among
users as they communicate and share data or other assets. These are called positive network
externalities. Telephone networks provide a classic example. A telephone is of no use when
there is no one to call, but as the number of telephone users increases, the value to you
increases even though you have not paid any more for the phone. This is where the term
“externality” comes from: it’s a benefit—or cost, in the case of negative externalities—that is
external to the original transaction, i.e., your purchase of the phone. When you use MS Office,
you benefit because it's easy to exchange documents with the huge network of other MS Office
users. One way to represent value of network externalities is with Metcalfe’s Law, which states
that the total value of a network is proportional to the number of links between network nodes
(i.e., users), which grows as the square of the number of nodes.
Positive network externalities are a consumer-side benefit the comes from going along with the
crowd. There are equally important producer-side network effects, which drive down product
costs and increase quality. For example, most technologies are subject to a learning curve,
meaning that as the volume of production increases, the cost per unit falls. Products with a
large network move down the learning curve faster. Also, many types of IT products
(microprocessors, software) have very high fixed costs of development, and very low variable
costs of production and distribution, meaning there are huge scale economies. A new PC
operating system costs billions to develop. But after it’s developed, each copy costs next to
nothing to produce and distribute. All the time Apple was trying to compete with Microsoft in
the 1980s and 90s, it had the profound disadvantage of spreading its operating system
development costs over only a few million Macs, while Microsoft was spreading its costs over
100 million Windows PCs.
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Looking beyond individual producers, we often see entire ecosystems arise around dominant
technologies like Windows. (An ecosystem consists of a core innovation plus a set of
technologies, products and services that complement the core innovation.) A strong ecosystem
means there will be better training classes and aids available in the market place; it will be
easier to hire personnel that are already trained; and useful add-in products will tend to be
developed first, and maybe only, for Windows.
Strong network effects have several implications. The greater the number of people that use a
product or standard, the more valuable it becomes to any individual user, and the more likely it
is that people will choose to adopt it in the future. So, network effects tend to produce selfreinforcing virtuous cycles of adoption and “winner-take-all” outcomes, wherein one
technology or standard eventually dominates. They also have a tendency towards three
additional diffusion patterns: (1) standards wars (where two or more technologies compete for
dominance), (2) path dependent technology trajectories (where the outcome depends on small,
chance events early in the process) and (3) technology lock-in (where a standard cannot be over
turned even when a better technology comes along).
Let’s look a little closer at each of these three patterns. Standards wars abound in the IT world.
Consider Windows vs. Apple Mac OS, Apple iPhone vs. Google Android, Internet Explorer vs.
Mozilla vs. Chrome, Play-Station vs. xBox, and Blu-Ray vs. HD DVD to name just a few. A great
example of path dependency is IBM’s decision back in 1980 to have Microsoft build the
operating system (OS) for the IBM PC instead of IBM taking a few months to build the OS
themselves (OSs weren’t all that complicated back then). Imagine how Microsoft’s fortunes,
and the world of computing might have been different! Now, of course, most of the world has
become locked-in to Windows as a standard OS, due to extremely high switching costs and
other factors.
Food for thought: Interestingly, the Mac OS has gained significant market share in
recent years. To understand how is this possible requires a subtle understanding of
network effects. Here are some issues to consider: What architectural changes has
Apple taken to improve the scale economies for computers running the Mac OS? What
has happened to the cost of computers in general? Have there been any changes in the
patterns of how personal computers are used that could loosen the bonds of “lock-in,”
not just for Windows, but for any personal computer OS?
From an adopter perspective, patterns described above raise the stakes on technology
evaluation, because it becomes especially important to pick the eventual winning technology or
standard (or to at least preserve a migration path to the ultimate winner). From a supplier
perspective, this increases the opportunity for genuine first mover advantages and can justify
speculative investment to build a large adoption network fast. Witness the dominance of early
movers on the Internet, such as eBay, Paypal and Amazon. They all become more valuable the
more they are used (network effects); they all started from humble, almost accidental
beginnings (path dependency); and now they all command great loyalty, in part due to cleverly
built-in switching costs.
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Putting it All Together: From Distinctive Characteristics to Transformational
Impacts
The overall effect of Moore’s Law, digitalization, and network effects—individually and in
combination—has been to continually roll back the frontier on what is technically and
economically feasible to accomplish with IT. As a result, IT has become the dominant driving
force for innovation in processes, products and business models today, and we are reaching the
point where most large organizations are well on the road to becoming so-called “digital
enterprises” (i.e., enterprises where all information produced and consumed by key business
processes are stored and made broadly available in digital form).
The table below provides a short-hand way of understanding why and how these three
characteristics of IT are transforming jobs, companies, markets and even entire industries. The
right hand column shows chains of causation that summarizes how one or more distinctive IT
characteristics produce, through a set of intervening processes or results, some important
macro-level transformation.
Table 1: Transformational Impacts of Moore’s Law, Digitalization and Network Effects for
Innovation
Summary Impact
Chain of Influences Leading to an Transformational Impact
1. Industry transformation
Moore’s Law & Digitalization => device and network convergence =>
destruction of tight couplings between service modes and underlying
technologies => industry and market convergence; radical transformation of
whole industries.
2. Distinctive diffusion
dynamics
Network effects => “critical mass” diffusion dynamics, path dependency, winner
take all, lock-in => standards wars, risk of stranding.
3. More diverse
products and services
Moore’s Law & Digitalization => widespread diffusion of cheap digital
infrastructures => increased ability to aggregate product demand through
online channels + increased ability of consumers to find niche products suited to
their tastes => greater diversity of products and services developed and
offered (“Long Tail” effect).
4. More personalized
products and services
Digitalization => programmability, memorability, associability => greater
personalization of novel processes, products and services.
5. Faster innovation
cycles and processes
Moore’s Law & Digitalization => dramatically lowered cost/increased ease of
experimentation + complementary changes to innovation processes, structures,
incentives => more rapid development and evolution of innovative processes
and products.
6. Faster/ broader
product diffusion
Moore’s Law & Digitalization => rapid price/performance improvement of
physical digital products; near zero cost of duplication and distribution of
improvements for pure information products => accelerated emergence and
faster/broader diffusion of new products and business models.
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Summary Impact
Chain of Influences Leading to an Implication or Impact
7. Product pricing and
delivery flexibility
Digitalization => near zero cost of duplication and distribution; digital rights
management => intellectual property threats; increased control over how
digital product are used, when and by whom (e.g., bundling, trials, “freemium”
models); greater pricing flexibility (e.g., how much is charged, to whom, when,
by what mechanism, and for what level of functionality)
8. New ways to market
new products
Moore’s Law & Digitalization & Network Effects => widespread diffusion of
cheap digital infrastructures => new avenues for marketing and supporting
new products (e.g., sponsored search and context-based ads, social medial
marketing/online word-of-mouth)
9. Move to smart
technologies and
servitization
Moore’s Law & Digitalization & Network Effects => increased feasibility of
embedding digital sensors and processors in a wide range of everyday items and
then connecting them up into an “Internet of things” => widespread emergence
of “smart” technologies; accelerated move to servitization (converting
products into services) and other kinds of new business models enabled by
smart technologies.
10. Move to real-time
question answering
systems
Moore’s Law & Digitalization => feasibility of understanding natural language
questions and rapidly searching and then extracting knowledge from huge
troves of structured and unstructured data => new organizational process and
business models based on generalized real-time question answering systems.
11. Creation of
analytics-driven
digital innovation
opportunities
Digitalization => informating processes as they are automated => automatic
capture of vast new stores of detailed data about processes => pervasive
opportunities for analysis of all technology-mediated processes => increased
opportunities for process and product/business model innovation.
12. Democratized
innovation
Moore’s Law & Digitalization => widespread diffusion of cheap digital
infrastructures => increased ease of distributed collaboration and peer
production => process and product innovation discovery and development
becomes more open, democratized, and user-driven.
Here’s some food for thought: Which company/technology today do you think best represents
the best example of each chain of causation?
Footnotes
1. An explanation of the nature and implications of digitalization of content is provided in
Nicholas Negroponte’s Being Digital, Alfred E. Knope, 1995. Excerpts are
available here.).
2. Shapiro and Varian’s classic book, Information Rules: A Strategic Guide to the Network
Economy gives a thorough explanation of the sources and strategic implications of
network effects.).
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