Industrial Marketing Management 57 (2016) 119–126Contents .docx

Industrial Marketing Management 57 (2016) 119–126
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Industrial Marketing Management
Defining and identifying disruptive innovations☆
Delmer Nagy a,⁎, Joseph Schuessler a, Alan Dubinsky b
a Tarleton State University, United States
b Purdue University, United States
☆ The authors gratefully acknowledge the editor and
assistance and encouragement.
⁎ Corresponding author.
E-mail addresses: [email protected] (D. Nagy), Schu
(J. Schuessler), [email protected] (A. Dubinsky).
http://dx.doi.org/10.1016/j.indmarman.2015.11.017
0019-8501/© 2016 Elsevier Inc. All rights reserved.
a b s t r a c t
a r t i c l e i n f o
Article history:
Received 19 May 2015
Received in revised form 24 November 2015
Accepted 29 November 2015
Available online 25 March 2016
Three essential questions about innovations prevent academics
from helping managers determine if a new tech-
nology is a disruptive innovation to their organization. First,
what is a disruptive innovation? Second, how can a
disruptive innovation be disruptive to some and yet sustaining
to others? Third, how can disruptive innovations

be identified before a disruption has occurred in an
organization? This paper proposes answers to these three
questions by redefining disruptive innovations through use of
innovation adoption characteristics. Through the
relative nature of innovation characteristics, a heuristic, or
Baedeker, to better determine if an innovation
could be disruptive to an organization is proposed. Illustration
of the approach is presented to show how poten-
tially disruptive innovations could be identified before an
organizational disruption has occurred.
© 2016 Elsevier Inc. All rights reserved.
Keywords:
Innovation
Technology adoption
Managerial decision making
Disruptive innovation
1. Defining and predicting disruptive innovations
How canmanagers determine if a technologywill disrupt their
orga-
nization? In the article “Disruptive Technologies: Catching the
Wave,”
the authors (Bower & Christensen, 1995) described an idea that
has
long affected business sustainability: the notion that new
technologies
can create new markets or radically change, or disrupt, the
status quo
in existingmarkets. Although they were not the first to identify
the cre-
ative destruction caused by new innovations, identification of
newmar-
ket and low-end innovations provided researchers constructs
with
which to examine effects of new innovations on marketplaces

(Bower
& Christensen, 1995). Characterizing innovation effects
onmarketplaces
spawned a movement to enhance understanding and improve
predic-
tion of such technologies on marketplaces (Adner, 2002;
Christensen,
2006; Christensen & Raynor, 2003; Danneels, 2004; Hang,
Chen, & Yu,
2011; Schmidt & Druehl, 2008). The primary goal of this stream
of re-
search appears to be prediction of marketplace disruptions
caused by
new innovations.
Predicting disruptiveness of an innovation is important for
market
incumbents so that they avoid inimical consequences from
ignoring a
disruptive innovation. These adverse outcomes include
reducedmarket
share, decreased status, or even bankruptcy or death of an
organization
(Bower & Christensen, 1995). But how is an organizational
manager to
know if a given technology will result in a marketplace
disruption or
even affect their organization? A commonly held belief is that,
if
reviewers for their invaluable
[email protected]
managers could identify disruptive innovations before these
technolo-
gies have affectedmarkets, managers could take actions to turn a
poten-

tial marketplace disruption into a new opportunity—or at the
very least,
prevent the failure of their organization. Because the ability to
predict
disruptive innovations can have far-reaching effects, researchers
have
essayed to predict disruptions caused by new innovations. These
stud-
ies, though, have at least three common problems: (1) the
definition
of a disruptive innovation is vague, as the definitions focus on
market
impacts; (2) how can disruptive innovations be disruptive to
some,
but not to all organizations; and (3) data generally are generated
only
after a disruption has taken place (Govindarajan & Kopalle,
2006;
Hang et al., 2011; Myers, Sumpter, Walsh, & Kirchhoff, 2002;
Paap &
Katz, 2004; Schmidt & Druehl, 2008). The foregoing issues
have put
pressure on researchers tomore clearly and accurately define, or
identify,
what a disruptive innovation is.
Because Christensen and Bower characterized marketplace
disrup-
tions, or the effects new technologies can have on existing
market-
places, an opportunity exists to define how new technologies
facilitate
these market changes. In other words, technology characteristics
that
can contribute to marketplace disruptions can be identified to
extend

disruptive innovation theory. Indeed, at least six articles have
sought
to identify or define disruptive innovations from an innovation
perspec-
tive as opposed to amarketplace perspective (Adner, 2002;
Christensen,
2006; Christensen & Raynor, 2003; Danneels, 2004; Hang et al.,
2011;
Schmidt & Druehl, 2008), yet the ensuing definitions fall short
of identi-
fy specific innovation characteristics that conceivably could
clarify the
concept of a disruptive innovation. Unambiguously defining a
disrup-
tive innovation is essential for both academic and practical
reasons. Ac-
ademically, unequivocally defining a disruptive innovation is
critical to
address causal theory of reference (Kripke, 1977; Putnam,
1973). As
philosophers of business, researchers assign meaning with terms
in
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2015.11.017&domain=pdf
mailto:[email protected]
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120 D. Nagy et al. / Industrial Marketing Management 57
(2016) 119–126
their fields; as experts in business, they provide references for
“disrup-
tive innovations,” as the business discipline has proposed the

term
(Bower & Christensen, 1995). This academic ownership of
terms is com-
mon. For example, the term “lion” is defined by the community
of zool-
ogists; the definition of an “elm tree” is defined by the
community of
botanists; and if academics of the business community seek
ownership
of the idea of the “disruptive innovation,” they need to proffer a
clear
definition of what a disruptive innovation is. Otherwise, the
term will
likely not have a specific definition, thus possibly leading it to
become
merely another business buzzword.
Froma pragmatic perspective, a refinement of the definition of a
dis-
ruptive innovation is essential for managers. How can a
business deci-
sion maker analyze a technology to predict whether a new
technology
has the potential to be disruptive to a marketplace or to their
organiza-
tion? After all, Christensen has identified the “disruptive to
some, but
not to all” effects of innovative technologies. Accordingly,
might an in-
novation revolutionize a marketplace or an organization, thus
having
drastic changes or even contributing to the failure of the
business?
Will business professionals operate blindly in a rapidly
changing tech-
nological environment?

Given the above-mentioned dialectic, this paper seeks to answer
the
following three essential questions surrounding disruptive
innovations
so as to provide managers a lens through which to view new
innova-
tions and answer the three longstanding questions about this
typology
of technology: (1) what is a disruptive innovation? (2) how can
disrup-
tive innovations be disruptive to some adopters and yet be
incremental
or sustaining to others? and (3) how can disruptive innovations
be pre-
dicted before an organizational disruption has occurred? These
ques-
tions will be answered by shifting the focus of the definition of
a
disruptive innovation. Existing disruptive innovation theory
focuses
on market characteristics, new market, and low end innovations.
By
using innovation adoption theory, three innovation
characteristics are
identified to ground disruptive innovations in a technology, not
a
marketplace—an innovation's (1) technical standard, (2)
functionality,
and (3) ownership (justification for undergirding the definition
with
these features will be subsequently offered). Then, through this
redefi-
nition, an examination of an innovation's characteristics, as
compared
to existing technologies used by an organization, can beused

potentially
to identify relative effects of an innovation on an organization.
Finally,
through use of the value chain, impact of a potentially
disruptive inno-
vation can be better understood vis-à-vis an organization: the
innova-
tion and its effects could be rated, going from its disrupting
primary or
secondary operations, to its sustaining primary or secondary
operations,
to its having no effect. This paper will first review germane
literature to
assist in defining what a disruptive innovation is. Second, an
explana-
tion about the relative effects of disruptive innovations is
offered.
Third, amethod for potentially identifyingdisruptive innovations
before
the disruption occurs is proposed. Fourth, case that highlights
how this
method can be usedwith emerging technologies is proffered.
The paper
concludes with a discussion about the benefits of the
redefinition, po-
tential applications for practitioners, and future research areas.
2. Literature review
What is a disruptive innovation?Although identifying effects of
a dis-
ruptive innovation on an organization or marketplace is
relatively easy,
creating a pellucid definition of a disruptive innovation has
been elusive.
Perhaps this is because Christensen identified two different

types of dis-
ruptive innovations: newmarket innovations and low-end
innovations.
The effects of these two types of disruptive innovations on
markets are
different.
Newmarket innovations act, as their name implies, by creating
new
demand for a new technology, resulting in consumers
demanding
this new product. Conversely, low-end innovations provide
similar
characteristics to existing technologies but cost substantially
less.
Compounding the effects of these two different types of
innovations,
Christensen has stated that despite some innovations' being
disruptive
to one group, the same innovations could be sustaining to
another
group (Adner, 2002; Christensen & Raynor, 2003; Christensen,
Bohmer, & Kenagy, 2000a, 2000b; Danneels, 2004; Schmidt &
Druehl,
2008). Although the literature agrees that disruptive innovations
cause a market to behave differently, what about these
disruptive inno-
vations changes to marketplace behavior? In other words, which
inno-
vation characteristics cause marketplaces to disrupt? A
definition for
disruptive innovations that is grounded in innovation
characteristics
would provide insight into what innovation characteristics result
in
marketplace changes. Without a consistent definition, grounded

in in-
novation characteristics, academics and practitioners alike are
chasing
phantoms: the ontology, or the nature of disruptive innovations,
and
epistemology, or knowledge surrounding disruptive innovations,
are
difficult tomove forwardwithout agreement as towhat is being
studied
(Bryman & Bell, 2011; Guba & Lincoln, 1994).
Instead of having a stipulated definition, or a definition based
on pre-
cisely defined concepts, academics and practitioners are left
with an ex-
tracted definition, or a definition based on common usage of the
word
(Kripke, 1977; Putnam, 1973). Unfortunately, common usage of
the
word allows for contextual inference and potentially variegated
mean-
ing: in other words, a disruptive innovation may or may not be
disrup-
tive, depending on how the word is used.
A stipulated definition is a definition in which a term is given a
spe-
cific meaning for the purposes of a given argument in a context.
For a
disruptive innovation, it should be grounded in an innovation's
charac-
teristics. This foundation is needed because the topic of
discussion is the
innovation itself, and the disruptive component of that
innovation. Any
definition of a disruptive innovation that does not address

innovation
characteristics would appear to be discussing something other
than
the innovation itself. Therefore, a definition for a disruptive
innovation
that is grounded in the innovation itself is needed to move this
body
of knowledge forward. The need for a stipulated definition has
been rec-
ognized by other business scholars as a fundamental criticism
surround-
ing disruptive innovations (Markides, 2006, Schmidt & Druehl,
2008).
Accordingly, two different definitions of a disruptive
innovation have
been proposed (Adner, 2002; Danneels, 2004; Schmidt &
Druehl,
2008; Thomond & Lettice, 2002).
One definition of a disruptive innovation focuses on the
functional
quality and cost of an innovation. This definition defines
disruptive
innovations as an innovation with “good enough” functionality
that
has a low cost (Christensen, Baumann, Ruggles, & Sadtler,
2006;
Christensen, Bohmer, & Kenagy, 2000a; Christensen, Horn, &
Johnson,
2008; Paap & Katz, 2004; Thomond & Lettice, 2002).
Theoretically,
the lower quality and lower priced innovation incrementally
improves
until eventually the innovation competeswithmarket leading
products,
thus disrupting themarket status quo (Bower & Christensen,

1995). De-
fining disruptive innovations as lower quality products that
compete on
price does not appear to be an appropriate innovation
characteristic
withwhich to define a typology of technology. Indeed, price
changes re-
flect a variety of factors from organizational processes and
materials, to
marketplace conditions. “Good enough quality” is a function of
compar-
ing two ormore innovations that complete a similar task. Price
and per-
ceived quality are not innate innovation characteristics; rather,
price
and perceived quality are redolent of business strategy
decisions. Fur-
ther, competition on price and quality is a commonly accepted
business
strategy—but neither price nor perceived quality are innate
innovation
characteristics—on which to ground a definition of a typology
of tech-
nology (Besanko, Dranove, & Shanley, 2009). As such, this
definition es-
sentially focuses on business strategies regarding market entry
and
overlooks specific innovation characteristics. This is important
because
an innovation's characteristics that create changes in customer
expecta-
tions could disrupt existing, or potentially create new, markets,
not a
price point or entry strategy.
The other definition of disruptive innovations focuses not on an

innovation's cost or quality but on market characteristics.
Danneels
121D. Nagy et al. / Industrial Marketing Management 57 (2016)
119–126
(2004), Markides (2006), and Tellis (2006) advocate that
disruptive in-
novations change the performance metrics, or consumer
expectations,
of a market. This definition moves the discussion of what
constitutes a
disruptive innovation forward, as it shifts the focus from market
strategy to alignment of an innovation's characteristics with
market ex-
pectations. However, this definition does not identify
innovation char-
acteristics that could potentially disrupt marketplace
preferences.
Specifically, which innovation characteristic or characteristics
could be
disruptive to themarketplace? Additionally, this definition does
not an-
swer the relativity of disruptive innovations—or how an
innovation can
be disruptive to one group but sustaining to another group.
Therefore,
this definition of a disruptive innovation remains somewhat
vague, as
a specific innovation characteristic, or set of characteristics, is
not iden-
tified; instead, the importance of marketplace alignment is
recognized.
2.1. Identification of disruptive innovation characteristics

Neither of the foregoing existing definitions of disruptive
innova-
tions identifies a specific innovation characteristic that could be
disrup-
tive. Rather, both definitions focus on factors external to the
innovation,
specifically market factors—costs, quality, performance
metrics, and/or
customer expectations. These factors are external to an
innovation in
that they change. An innovation's characteristics are intrinsic,
or innate,
and basedwithin the innovation itself. Cost is set by an owner,
aswell as
by changes based on a variety of factors external to an
innovation. Qual-
ity is perceived by a user, as well as changes relative to peer
innovations
external to an innovation. Customer expectations change over
time rel-
ative to other innovations and are also external to an
innovation. Rather
than identifying specific innovation characteristics to extend
disruptive
innovation theory, these works extend Christensen's definition
by de-
scribing the marketplace conditions that can lead to marketplace
dis-
ruption. None of these factors is intrinsic or innate to an
innovation.
This paper, however, proposes that innovation adoption
theories, spe-
cifically those theories addressing innovation characteristics, be
can be
used to identify specific innovation characteristics intrinsic to

an inno-
vation that can cause marketplace disruptions.
Three innovation characteristics have been identified in
innovation
adoption literature as having the potential to change markets:
radical
functionality, discontinuous technical standards, and an
innovation's own-
ership (Thomond & Lettice, 2002). Radical functionality is
recognized in
innovation adoption literature through articles describing
radical inno-
vations, or innovations that provide a user the ability to
undertake a
new behavior or accomplish a new task that was impossible
before
the invention of the innovation (Abernathy & Utterback, 1978;
Anderson & Tushman, 1990; Dahlin & Behrens, 2005). Radical
innova-
tions disrupt markets in Christensen's new market fashion by
creating
new markets. Discontinuous technical standards are also
recognized
as having the potential to change markets in innovation
adoption liter-
ature (Dewar & Dutton, 1986). Discontinuous innovations, or
innova-
tions that utilize new materials or new processes in the creation
of
existing technologies, typically disrupt markets by using less
costly ma-
terials or more efficient production processes in the creation of
existing
technologies. Discontinuous innovations disrupt markets as
described

by Christensen's low end innovation. Radical functionality,
discontinu-
ous technical standards, and an innovation's ownership can be
found
in one form or another in several innovation adoption theories
(Attewell, 1992; Rogers, 1995; Swanson, 1994). Perhaps the
exemplar
innovation adoption theory is Innovation Diffusion Theory
(IDT),
which proposes that five innovation attributes affect innovation
adop-
tion (Rogers, 1995): relative advantage, compatibility,
complexity,
trialability, and observability. Relative advantage specifically
identifies
functionality of an innovation as influencing the adoption of a
technol-
ogy. The concept of relative advantage recognizes that
innovation func-
tionality is not absolute between technologies. As the name of
the
construct implies, functionality is relative between technologies
and be-
tween users.
IDT constructs of compatibility and complexity are directly tied
to
the technical standards of an innovation. Compatible
technologies have
similar technical standards, while complex technologies have
new tech-
nical standards that create a knowledge barrier for users
(Attewell,
1992). Complexity forces adopters to overcome knowledge
barriers to
maximize the effectiveness of the new technology (Attewell,
1992).

The final two IDT attributes, trialability, and observability,
have links
to marketplace awareness or distribution channels and are
dependent
on ownership of an innovation. Innovation owners determine
how the
innovation is presented within a marketplace in terms of
trialability
and observability (Rogers, 1995).
Functionality and technical standards are further refined in
exten-
sions and modifications of adoption theories in the areas of
radical
and discontinuous innovations. For example, ideas related to
radical in-
novations have been explored in conjunction with firm
organization
(O'Connor & DeMartino, 2006), organizational strategy and
structure
(Ettlie, Bridges, & O'keefe, 1984), context (Germain, 1996),
and organi-
zational adoption (Dewar & Dutton, 1986).
This work has observed that both radical and discontinuous
innovations—or innovations with new functionality or with new
mate-
rials or production processes—dramatically alter or disrupt
existing or-
ganizational structure, strategy, context, and use.
The third innovation characteristic that influences
thedisruptiveness
of an innovation is the ownership of an innovation. Ownership
of an in-
novation is an innate but abstract characteristic: it does not have

a phys-
ical manifestation. Ownership of an innovation is substantially
different
from functionality and technical standards of an innovation in
that it is
not a physical characteristic of the innovation; one cannot touch
owner-
ship. However, the ownership model of an innovation has
established
effects on business, influencing factors both inside andoutside
of organi-
zations. Inside an organization, ownership influences costs,
employee
motivation, and organizational performance (Huang, 1997).
Outside an
organization, ownershipmodels affect resource utilization and
develop-
ment, forms of sales, and services associated with innovations
(Stam,
2009). Moreover, ownership of ideas—through patents,
copyrights,
and trademarks—limit and control nearly every aspect of an
innovation
(Chon, 1993; Joyce & Patterson, 2003). From production to
distribution
to terms of use, ownership of an innovation dictates how an
innovation
is received in a marketplace (Merges & Reynolds, 2000).
Because ownership establishes market prices, innovation-related
services, and other ways in which an innovation interacts with a
mar-
ketplace, ownership has many marketplace effects on
innovations.
While prices, services offered, and other marketplace offerings
affect

how an innovation is received, they are a result of the owners'
of an in-
novation decision. Alternative forms of ownership in
established indus-
tries have disrupted the status quo of these industries by
changing
characteristics like price, or services surrounding the
innovation.
These changes have effects on marketplace expectations
surrounding
innovations (Johnson & Greening, 1999).
This phenomenon can be illustrated with open source software.
This
type of software is widely recognized as disrupting some
segments of
the software industry and doing so without a radically different
func-
tionality or discontinuous technical standards. Indeed, many
open
source programs perform similar tasks to proprietary software,
as
open source programs can run on existing computers, needing
no new
technical standard and providing the same functionality. The
disrupting
factor associated with open source software is the ownership of
the
software—such software has no single definitive owner
(Crowston,
Wei, Howison, & Wiggins, 2012). Rather, it is collectively
owned by a
group of volunteers which create, manage, support, and
distribute the
technologies (Lakhani & Von Hippel, 2003). Such diffused
ownership

does not raise questions about the functionality or technical
standards
of the technology. It does, however, create questions about the
price,
services, and responsibilities associated with the ownership of
the soft-
ware, which in turn affect marketplace expectations (Crowston
et al.,
2012).
(2016) 119–126
Functionality, technical standards, and ownership are also
linked to
existing disruptive innovation theory. Successful innovations
with rad-
ical functionality are the “new market” innovations identified
by
Christensen. When innovations offer something radical that is
well re-
ceived in the marketplace, these innovations can create new
demand.
Existing industry incumbents do not provide the same
functionality,
and these innovations act as their namesake and create a new
market.
However, radical functionality alone is not enough to ensure
that a
new market will be created. Business history is littered with
radical in-
novations that never succeeded in the marketplace (Dewar &
Dutton,
1986; Maidique & Zirger, 1984). Low end disruptive
innovations entail

changes to technical standards or ownership. These innovations
seek
to lower costs through the use of new materials, new production
pro-
cesses, or ownership structures. Changes in technical standards,
or the
use of lower cost materials or production processes, were used
to iden-
tify and label the phenomenon of low end disruptive innovations
in the
data storage market (Bower & Christensen, 1995). For instance,
al-
though the functionality of data storage did not change,
information
was stored in a digital format, an aspect of data storage–the
overall ca-
pacity or amount stored, was substantiallymodified based on
themate-
rials and concomitant production processes, or the technical
standard,
of the innovation. Because these changes in data storage
afforded en-
hanced store data storage, the cost per unit of data stored was
drastical-
ly reduced, thereby meeting the criterion for being a low end
innovation.
Because the foregoing three characteristics are innate to an
innova-
tion, the disruptiveness of an innovation on a marketplace will
be rela-
tive to other innovations and marketplace needs. If an
innovation is
providing radical functionality, or something new to the
marketplace,
the opportunity exists for the innovation to be a newmarket

innovation.
If an innovation seeks to lower costs through new technical
standards
(materials or production processes) or through new forms of
owner-
ship, the potential for a low end innovation exists. However,
because or-
ganizations both use innovations and create innovations,
managers
need to identify technologies that could potentially disrupt
either the
markets where the organization compete or the innovations used
by
their organizations. For example, the market for automobiles
may or
may not be disrupted by the emergence of electric automobiles.
The
functionality of the two types of automobiles are nearly
identical–
consumers do not need to relearn how to drive automobiles
based on
the method of propulsion. However, technical standards that
comprise
the materials and processes to create the automobile
substantially
change. And if marketplace preferences were to shift to a high
demand
for electric automobiles, automobile manufacturers that did not
have
the technical standards, ormaterials and production capabilities,
to pro-
duce electric automobiles may well lose market share or fail.
Therefore,
business decision makers need a definition of disruptive
innovations
that identifies specific inherent innovation characteristics to

understand
both the nature of the potential marketplace disruption—
newmarket or
low end—as well as the organizational effects the innovation
may have
directly on the organization.
2.2. Refinement of the definition of a disruptive innovation
This paper proposes that these existing theoretically recognized
constructs—functionality, technical standards, and ownership—
can be
combined with existing definitions of disruptive innovations to
extend
the existing definition of disruptive innovations. By refining
Danneels,
Markides, and Tellis' definition, a disruptive innovation is
defined here
as “an innovation that changes the performance metrics, or
consumer
expectations, of a market by providing radically new
functionality, dis-
continuous technical standards, or new forms of ownership.”
This defi-
nition includes three theoretically-grounded innovation
characteristics
that can potentially disrupt existing industries or organizations.
More-
over, this definition addresses twomajor problemswith the
existing def-
inition of disruptive innovations. First, it identifies specific
innovation
characteristics that can be identified and compared. Second, it
answers
the question regarding why an innovation might be disruptive to
some,

but not to all, entities. The solution is that innovation alignment
of func-
tionality, technical standards, and ownershipmodels with
existing orga-
nizational andmarketplace technologies is afforded. Third, this
definition
allows for innovations to be categorized as either new market
innova-
tions, those innovations with new functionality, or as low end
innovations—those innovations with discontinuous technical
standards
(materials or production processes) or new forms of ownership.
Further-
more, by grounding the definition of a disruptive innovation in
function-
ality, technical standards, and ownership, the disruptive
potential for an
innovation can be estimated before a drastic marketplace or
organiza-
tional change occurs. By supplying academics and practitioners
with
these three innovation characteristics academics can now
investigate
specific innovation qualities and practitioners can now compare
new
technology characteristics with old technology characteristics.
2.3. Innovation relativity
Oneof themajor challenges to improving the definition of
disruptive
innovations has been the “disruptive to some, but sustaining to
others”
nature of innovations (Bower & Christensen, 1995). Addressing
this
query is challenging, as the statement implies that innovation

effects
are relative (i.e., innovation effects are sensitive to an
organization's
existing context and technologies an organization has used).
Innovation
adoption theories promulgate that innovation characteristics are
rela-
tive to other innovations. Constructs from Innovation Adoption
Theory
(e.g., relative advantage, complexity, compatibility) are
grounded in
the relative nature of innovations (Abernathy & Utterback,
1978;
Henderson & Clark, 1990; Rogers, 1995; Tushman & Anderson,
1986). For example, an innovation's relative advantage is an
attribute
that is superior vis-à-vis another innovation. Complexity is the
degree
of difficulty of using an innovation relative to another
technology. Com-
patibility is the extent towhich an innovation canworkwith
another in-
novation (i.e., how the technical standard or knowledge needed
to use
an innovation is associated with another innovation).
An illustration of innovation relativity comes from the work of
Nord
and Tucker (1987). They identified innovation relativity in their
book
concerning a novel financial innovation, negotiable order of
withdrawal
(NOW) accounts. NOWaccounts were identified as a radical
innovation
to some financial institutions but an incremental innovation to
other or-

ganizations. The disruptiveness of the NOW account was based
on a fi-
nancial firm's existing organizational business practices and
how these
business practices were implemented (i.e., the relative
functionality
and technical standards of the NOW account).
Because innovation adoption theories recognize relative effects
of an
innovation, disruptive innovations can use these theoretical
bases to ex-
plain the “disruptive to some, but sustaining to others”
conundrum. By
comparing a potentially disruptive innovation with an existing
innova-
tion used in an organization, researchers ideally should now be
better
able to explain why an innovation is disruptive to one group but
sustaining to another. To do so, they merely compare
functionalities,
technical standards, or ownership across innovations. Therefore,
a
“sustaining innovation” would be an innovation that has
functionality,
technical standards, or ownership with which an organization is
famil-
iar; conversely, a potentially “disruptive innovation” would
have
functionality, technical standards, or ownership with which an
organi-
zation is not familiar. The disruptiveness of an innovation—how
an in-
novation may be sustaining to one group but disruptive to
another—is
now predicated on how familiar an organization is with existing

func-
tionalities, technical standards, or forms of ownership.
2.4. Prediction of disruptions to organizations
Because the changes caused by disruptive innovations can have
ad-
verse effects on organizations, researchers have proposed
methods
119–126
(models) to use in predicting these disruptions to organizations
and the
marketplace (Paap &Katz, 2004; Sood and Tellis, 2011).
However, many
of these models have been confirmatory in nature—confirming
that a
disruption has taken place on a marketplace level, but not
providing in-
sight as to whether or not an organization was disrupted by a
specific
innovation. Theoretically, a predictive model should be able to
identify
a potentially disruptive technology before a disruption has
occurred.
Practically, theory should be able to be refined to a specific
organization
so that an organization can determinewhether or not an
innovationwill
be disruptive to that organization. Research seeking to predict
disrup-
tive innovations has focused on marketplace disruptions and has
taken two distinct paths: a focus on modeling diffusion patterns

or an
adoption of an evolutionary approach to technology.
By identifying market forces, relative market sizes, and ability
of an
innovation to create new markets, Linton (2002) developed a
model
to determine the disruptiveness of an innovation at a market
level of
analysis. He used a Bass formula contextualized around the
foregoing
three variables and was able to provide confirmatory evidence
of mar-
ketplace disruptions owing to changes in technology. Schmidt
and
Druehl (2008) took a similar approach to identify disruptive
innova-
tions. Instead of using a Bass formula, though, their models
focused on
market diffusion curves of technologies; theywere able to
confirmmar-
ketplace disruptions caused by new technologies. Although able
to con-
firm marketplace disruptions, these models were confirmatory
in
nature and did not predict the potential disruptiveness of an
innovation
for a specific organization. In other words, the above-mentioned
efforts
were useful for identifying changes to a marketplace, but
whether they
would help individual organizations predict whether or not a
given in-
novation would be disruptive to an organization is uncertain.
The second path to identify disruptive innovations has led to a

dis-
cussion of technological stages—the evolution of a technology.
Paap
and Katz (2004) proposed three different cases that can
potentially
change the dominant technology of an industry or market. The
first
case highlights how an established technology matures to
become the
dominant driver of an industry. The second case focuses on user
needs
and how a new technology may better meet user needs than an
established technology. The third case stresses how
environmental
changes may create new drivers for technologies, thus causing
technol-
ogies to evolve to meet environmental changes. Moreover,
Myers et al.
(2002) proposed similar evolutionary stages for disruptive
innovations,
as innovations go fromproof of concept towidespreadmarket
adoption.
Both sets of researchers posit that disruptive innovations evolve
relative
to other functionality, technical standards (materials or
production pro-
cesses), or customer expectations. As with the predictive
models, how-
ever, this work focused on the marketplace and did not provide
insight
for individual organizations to predict whether or not an
innovation
would be disruptive to that organization.
2.5. Prediction of disruptive innovations specific to an
organization

To help organizations identify potentially disruptive
innovations,
prediction of a disruptive innovation should examine
innovation/orga-
nization fit. The innovation side of this alignment will be
grounded in
this definition of a disruptive innovation, in other words,
understanding
the functionality, technical standards, and ownership of an
innovation.
Many differentmodels could be used to determine the
organization-
al side of this fit, as there are several different
organizationalmodels. For
example, organizations can be examined through just about any
func-
tion or activity—howhuman resources are organized, how
capital is dis-
tributed, how information is processed, how bureaucratic the
organization is, how the organization addresses customer
service
needs, etc. To ground the predictive process, an organizational
model
that captures one of the defined innovation traits (i.e.,
functionality,
technical standard, or ownership)would beuseful, as the
organizational
modelwould overlapwith the definition of a disruptive
innovation. The
value chain provides such a model, as it examines an
organization
through organizational functions. Therefore, use of the value
chain pro-
vides an overlapping area, the functionality of an innovation

and the
functional areawhere that innovation could be usedwithin that
organi-
zation. Because of this functional overlap, by combining
innovation
characteristics with the value chain, organizations should
ideally be
able to predict where inside an organization a specific
innovation
could potentially disrupt the organization (Porter & Millar,
1985). The
value chain also classifies organizational activities into two
areas, pri-
mary and secondary areas, which describe how organizational
activities
are linked. Primary activities are conceptualized as themain
activities of
what an organization does. These focus on the transformation of
raw
materials into finished goods that are sold to customers.
Secondary ac-
tivities are dimensions of support that all primary activities
draw
upon. Because the value chain provides these distinctions, use
of the
value chain in the determination of an organizational disruption
can
give an organization a general idea about the scope of the
potential dis-
ruption. If the technology is only used in secondary activities,
the scope
of the disruption may be of lesser importance and may not need
to be
addressed in the immediate future. Conversely, if the innovation
is
used in primary activities, organizations may need to take

immediate
action in response to the innovation.
This paper proposes a three-step method for predicting how an
in-
novation may disrupt an organization (Fig. 1). This method is
depen-
dent on managers' understanding both the context of their own
innovation and the context of a potentially disruptive
innovation. To deter-
mine if an innovation could be potentially disruptive to an
organization,
a manager needs to identify first a candidate technology. Then,
for this
candidate technology he/she should define the functionality,
technical
standards, and form of ownership of that technology. Second,
the man-
ager must discern where inside an organization's value chain the
inno-
vation is used. This requires that the organization understands
the
context of the organization andwherewithin the organization the
inno-
vation could be used. Knowing the context surrounding the
innovation
should ascertain which value chain segment or segments would
utilize
the technology. Finally, understanding how the characteristics
of the
new technology, or the potentially disruptive technology, align
relative
to existing technologies used by the organization should provide
some
understanding about how potentially disruptive an innovation
might

be to the organization. Notwithstanding possible assumptions
and inac-
curacy, predicting how innovation characteristics align with
market-
place needs to create a disruption, this three-step technique can
provide managers a tool to potentially identify disruptive
innovations
before a disruption has occurred.
The first step in this process could be undertaken by comparing
the
functionality, technical standards, and forms of ownership of
the inno-
vation in question with the existing technology inside an
organization's
value chain segments. Because managers will have contextual
insight
into their own organization, and the primary and secondary
activities
of the organization, managers will ideally have contextual
capacity to
determine if one or more of an innovation's characteristics are
different
from existing technology used by the organization. If an
innovation has
one or more characteristics that differ from innovations
currently used
by the organization, then that innovation has the potential to be
a dis-
ruptive innovation through that characteristic (i.e.,
functionality, tech-
nical standards, or ownership). If the disruption can be
characterized
as affecting primary or secondary activities in the value chain,
the orga-
nizational scope of the disruptiveness can be assayed. Shown in

Fig. 1 is
the three-step process.
2.6. Illustration of the 3-step method
For this example, themethodwill focus on three-dimensional
print-
ing, or 3D, printers that layer or spray plastic in three
dimensions. Most
3D printers currently focus on plastics, but future versions of
3Dprinters
will use other materials; 3D printers that produce plastics are
available
and out of the prototyping stages of technology. 3D printers
spray
Fig. 1. Three steps to determine potential disruptive
innovations.
(2016) 119–126
plastic to produce a form. Forms can take a variety of shapes
and are typ-
ically used to create first-time designs for manufacturers. Many
indus-
tries, from architecture to medicine, use these forms (Giannatsis
&
Dedoussis, 2009; Utela, Storti, Anderson, & Ganter, 2008).
Advances in
3D printing promise to move the technology beyond simple
plastic
forms, but these advanced printers are not widespread or
mainstream
as of yet (Giannatsis & Dedoussis, 2009; Utela et al., 2008).

Many trade magazines and technology leaders have identified
3D
printing as a potentially disruptive innovation (Lipson &
Kurman,
2013; Petrick & Simpson, 2013; Rayna & Striukova, 2014). This
illustra-
tion uses two fictional organizations in the same extended value
chain—one organization that produces plastics (a potential
supplier)
and another that sells plastics (a potential retailer), to
demonstrate
how these two different organizations could interpret 3D
printers as
having relative disruptive effects. Organization A is the plastics
manu-
facturer; Organization B, the plastics retailer.
2.6.1. Step 1: identify the innovation and its characteristics
To examine the potential disruptiveness of 3D printing, the
three-
step process begins by identifying the functionality, technical
standards,
and forms of ownership of 3D printers.
• Functionality: The functionality of 3D printing is the
production or
manufacture of plastic goods. This is not new functionality, as
injec-
tionmolds have traditionally been used to create plastic
products. Be-
cause the functionality is not new, 3D printing does not have
the
capacity of becoming a new market innovation for plastic
manufac-

turers.
• Technical standards: 3D printers are large printers that layer
or spray
plastic into different forms. Traditionally, plastic products are
created
through injection molding or through extrusion. Both
injectionmolds
and extrusion use a different technical standard from that of a
3D
printer. Layering or spraying plastic into forms is a new
technical
standard for an existing functionality. Because 3D printing
offers a
new technical standard, the technology has the opportunity to
be-
come a low end disruptive innovation.
• Ownership: 3D printers come in a variety of ownership
options,
though the most commonly sold printers are proprietary in
nature.
Ownership of 3D printers is complex, as there are threemajor
compo-
nents: hardware, software, and materials used by the printer.
Each of
these components may be proprietary or open source in nature.
Typ-
ically, the hardware and printing materials are proprietary.
Software
is considerably different, though, as there are both open source
and
proprietary versions of 3D software. Proprietary software tends
to
be more likely to be used for commercial needs, as
manufacturers of

3D printers produce all three components (hardware, software,
and
materials) that align or are compatible with one another.
2.6.2. Step 2: identify where in an organization's value chain
the innovation
is used
Organization A (the plastics manufacturer) and Organization B
(the
plastics retailer) will have different segments of the value chain
affected
by 3D printing, thus resulting in relative effects of the
technology. Orga-
nization A will most likely consider functionality of 3D
printers. This
functionality is the production of plastic products, the primary
opera-
tions for Organization A. Because Organization A's operations
focus on
production of plastic products, Organization A seemingly would
charac-
terize 3D printers as having “primary effects” in the value
chain. Specif-
ically, the effects of 3Dprinting for Organization Awould be the
primary
effects vis-à-vis operations.
Organization B will also likely vet the functionality of 3D
printers.
Because the functionality does not change (i.e., 3D printers are
still pro-
ducing plastic products), Organization B will have a difficult
time in
identifying value chain primary or secondary effects of 3D
printers.

119–126
After all, Organization B focuses on selling, not producing,
plastic prod-
ucts. Although 3D printingmay alter the production of plastic
products,
it putatively would not affect the retailing of these products.
Conse-
quently, 3D printing is said to have neither primary nor
secondary ef-
fects on Organization B. Management, nevertheless, of
Organization B
may identify 3D printing as an opportunity to become vertically
inte-
grated in the value chain of its organization and regard this as
an oppor-
tunity not only to sell plastic goods, but also to manufacture
plastic
components. Palpably, this is a decidedly different scenario for
Organi-
zation B, onewhere the business model of the organization is
changing.
2.6.3. Step 3: compare the potentially disruptive innovation
with technolo-
gies currently used in the organization for that value chain
segment
Organization Awill regard 3D printing differently
fromOrganization
B. After all, 3D printing has primary operations effects on
Organization
A, but has at best only a negligible effect on Organization B.
Given the

foregoing circumstances, Organization A continues the analysis
of 3D
printing by comparing the existing technologies in its primary
opera-
tions; Organization B, though, utterly stops further
investigation.
To compare 3D printing with existing technologies,
Organization A
identifies what is currently being used for plastics production.
Rather
than using 3D printing, Organization A employs injection
molding to
create plastics. Injection molding is the current technical
standard for
the plastics industry. So, because 3D printers have no new
functionality,
both technologies—3D printing and injection molding—produce
plastic
parts. 3D molding, nevertheless, has a new technical standard:
use of a
printer as opposed to the use of an injection mold. The analysis
con-
tinues as Organization A examines critical success factors for
manufacturing operations. For Organization A, ability to create
large
volumes of standardized products, as well as ability to change
produc-
tion sets to meet production agility, is imperative.
Currently, 3D printing focuses on low volume production with
the
ability to quickly change production sets. This technology will
disrupt
a segment of the plastics manufacturing industry by shifting the
techni-

cal standard of production for plastic components where low
produc-
tion runs of varying products is the critical success factor.
Because
Organization A focuses on large batches of standardized plastic
prod-
ucts, 3D printing does not appear to be a significantly
disruptive tech-
nology. However, organizations that focus on low production
volume
with rapidly changingproduction setswould appear to need to
embrace
this new technical standard or face disruptive industry forces.
3. Discussion
This paper contributes academically and practically to the
ongoing
discussion of disruptive innovations. Academically, two
contributions
are made. First, by redefining disruptive innovations with
innovation
characteristics of functionality, technical standards, and
ownership, an
extended definition for disruptive innovations is proposed: “an
innova-
tion with radical functionality, discontinuous technical
standards, and/
or new forms of ownership that redefine marketplace
expectations.”
The second academic contribution provides insight into a
longstanding question associated with disruptive innovations:
how
can an innovation be disruptive to some adopters but not to
others?

By redefining disruptive innovations to have specific
characteristics,
these characteristics can be compared with technologies
currently
used by an organization. If disruptive innovations have
characteristics
that are already used by an organization—be it functionality, a
technical
standard, or a form of ownership—then the innovation will not
likely be
disruptive to the organization. However if the functionality,
technical
standards, or form of ownership is not utilized by the
organization,
the innovation has potential to be disruptive to the organization.
Pragmatically, the redefinition of disruptive innovations leads
to po-
tential identification of disruptive technologies before a
disruption to an
organization has taken place. By using the preceding refined
proposed
definition in conjunction with their value chain, practitioners
should
be able to improve estimation of effects of potentially
disruptive innova-
tions. Simply following the three-step method outlined in this
paper
could facilitate prediction of disruptive innovations.
Although this paper moves the discussion of disruptive
innovations
forward, it also creates future research opportunities. The
currentmeth-
odology for potentially identifying disruptive innovations needs
further

refinement. After all, its assessment inside an organization's
value chain,
an innovation's characteristics, and marketplace alignment is
not quan-
titatively based. Subsequent research should be conducted to
quantify
these areas.
Work has already been done to measure radical functionality of
in-
novations (Dahlin & Behrens, 2005; Green, Gavin, and Aiman-
Smith,
1995. Given the refined definition of disruptive innovations
created
here, radical functionality of new innovations should be
measured
from twopoints. First, the overall radicalness of an innovation's
function
relative to existingmarketplace offerings needs to bemeasured.
Second,
potential disruptiveness would be the radicalness of a new
innovation's
functionality with an organization's current technical offerings.
These
two measures would need to be reconciled to assess the overall
func-
tional radicalness of a given innovation.
Similarly, measuring technical standards and ownership is
needed
to quantitatively assess disruptive innovations. Technical
standards
and ownership would also need to be measured from both an
organization's and the marketplace perspective. Measurements
from
both orientations would need to be reconciled for an assessment

to
work.
In addition to the foregoing issues surrounding innovation
charac-
teristics of functionality, technical standards, and ownership,
the meth-
odology proposed here should be further examined. Perhaps
there are
technologies and situations that confirm this three-stepmethod;
perad-
venture, however, contexts may exist where the three-step
approach
does not apply. Cases applying this methodology would
contribute to
the prediction of disruptive innovations and allow for further
refine-
ments in predictingdisruptive innovations. Investigation into
disruptive
innovations will surely continue, as new technologies emerge.
Emerg-
ing fields—nano-technology, gene therapy, new forms of
energy—will
become increasingly important to understand how these
technologies
can potentially impact organizations.
References
Abernathy, W. J., & James, M. U. (1978). Patterns of industrial
innovation. Technology
review, 64, 254–228.
Adner, R. (2002). When are technologies disruptive? A demand-
based view of the emer-
gence of competition. Strategic Management Journal, 23(8),

667–688.
Anderson, P., & Tushman, M. L. (1990). Technological
discontinuities and dominant de-
signs: A cyclical model of technological change. Administrative
Science Quarterly,
604–633.
Attewell, P. (1992). Technology diffusion and organizational
learning: The case of busi-
ness computing. Organization Science, 3(1), 1–19.
Besanko, D., Dranove, D., Shanley, M., & Schaefer, S. (2009).
Economics of Strategy. John
Wiley & Sons.
Bower, J. L., & Christensen, C. M. (1995). Disruptive
technologies: Catching the wave. Har-
vard Business Review video.
Bryman, A., & Bell, E. (2011). Business research methods 3e.
Oxford University Press.
Chon, M. (1993). Postmodern progress: Reconsidering the
copyright and patent power.
DePaul Law Review, 43, 97.
Christensen, C. M. (2006). The ongoing process of building a
theory of disruption. Journal
of Product Innovation Management, 23(1), 39–55.
Christensen, C. M., Baumann, H., Ruggles, R., & Sadtler, T. M.
(2006). Disruptive innovation
for social change. Harvard Business Review, 84(12), 94.
Christensen, C. M., Bohmer, R., & Kenagy, J. (2000a). Will
disruptive innovations cure

health care? Harvard Business Review, 78(5), 102–112
(Crowston).
Christensen, C. M., Horn, M. B., & Johnson, C. W. (2008).
Disrupting class. How disruptive
innovation will change the way the world learns. Mc Grow Hill.
Christensen, C., & Raynor, M. (2003). The innovator's solution.
Boston: Harvard Business
School Press.
Christensen, C. M., Bohmer, R., & Kenagy, J. (2000b). Will
disruptive innovations cure
health care? Harvard Business Review, 102–117 (September–
October).
Crowston, K., Wei, K., Howison, J., & Wiggins, A. (2012).
Free/libre open-source software
development: What we know and what we do not know. ACM
Computing Surveys
(CSUR), 44(2), 7.
Dahlin, K. B., & Behrens, D. M. (2005). When is an invention
really radical?: Defining and
measuring technological radicalness. Research Policy, 34(5),
717–737.
http://refhub.elsevier.com/S0019-8501(15)30011-0/rf0005

(2016) 119–126
Danneels, E. (2004). Disruptive technology reconsidered: A
critique and research agenda.
Journal of Product Innovation Management, 21(4), 246–258.
Dewar, R. D., & Dutton, J. E. (1986). The adoption of radical
and incremental innovations:
An empirical analysis. Management Science, 32(11), 1422–

1433.
Ettlie, J. E., Bridges, W. P., & O'keefe, R. D. (1984).
Organization strategy and structural dif-
ferences for radical versus incremental innovation. Management
Science, 30(6),
682–695.
Germain, R. (1996). The role of context and structure in radical
and incremental logistics
innovation adoption. Journal of Business Research, 35(2), 117–
127.
Giannatsis, J., & Dedoussis, V. (2009). Additive fabrication
technologies applied to medi-
cine and health care: A review. International Journal of
Advanced Manufacturing
Technology, 40(1–2), 116–127.
Govindarajan, V., & Kopalle, P. K. (2006). The usefulness of
measuring disruptiveness of
innovations ex post in making ex ante predictions*. Journal of
Product Innovation
Management, 23(1), 12–18.
Green, S. G., Gavin, M. B., & Aiman-Smith, L. (1995).
Assessing a multidimensional mea-
sure of radical technological innovation. Engineering
Management, IEEE Transactions
on, 42(3), 203–214.
Guba, E. G., & Lincoln, Y. S. (1994). Competing paradigms in
qualitative research.
Handbook of Qualitative Research, 2. (pp. 163–194).
Hang, C. C., Chen, J., & Yu, D. (2011). An assessment

framework for disruptive innovation.
Foresight, 13(5), 4–13.
Henderson, R. M., & Clark, K. B. (1990). Architectural
innovation: the reconfiguration of
existing product technologies and the failure of established
firms. Administrative
Science Quarterly, 9–30.
Huang, T. C. (1997). The effect of participative management on
organizational perfor-
mance: The case of Taiwan. International Journal of Human
Resource Management,
8(5), 677–689.
Johnson, R. A., & Greening, D. W. (1999). The effects of
corporate governance and institu-
tional ownership types on corporate social performance. The
Academy of Management
Journal, 42(5), 564–576.
Joyce, C., & Patterson, L. (2003). Copyright in 1791: An essay
concerning the founders'
view of the copyright power granted to Congress in Article I,
Section 8, Clause 8 of
the US Constitution. Emory Law Journal, 52(909).
Kripke, S. (1977). Speaker's reference and semantic reference1.
Midwest studies in
philosophy, 2(1), 255–276.
Lakhani, K. R., & Von Hippel, E. (2003). How open source
software works: “Free” user-to-
user assistance. Research Policy, 32(6), 923–943.
Linton, J. D. (2002). Forecasting the market diffusion of

disruptive and discontinuous in-
novation. Engineering Management, IEEE Transactions on,
49(4), 365–374.
Lipson, H., & Kurman, M. (2013). Fabricated: The new world of
3D printing. John Wiley &
Sons.
Maidique, M. A., & Zirger, B. J. (1984). A study of success and
failure in product innova-
tion: The case of the US electronics industry. Engineering
Management, IEEE Transac-
tions on(4), 192–203.
Markides, C. (2006). Disruptive innovation: In need of better
theory*. Journal of Product
Innovation Management, 23(1), 19–25.
Merges, R. P., & Reynolds, G. H. (2000). Proper scope of the
copyright and patent power.
The Harvard Journal on Legislation, 37, 45.
Myers, D. R., Sumpter, C. W., Walsh, S. T., & Kirchhoff, B. A.
(2002). Guest editorial a
practitioner's view: Evolutionary stages of disruptive
technologies. Engineering
Management, IEEE Transactions on, 49(4), 322–329.
Nord, W. R., & Tucker, S. (1987). Implementing routine and
radical innovations. Lexington,
MA: Lexington Books.
O'Connor, G. C., & DeMartino, R. (2006). Organizing for
radical innovation: an exploratory
study of the structural aspects of RI management systems in
large established firms.

Paap, J., & Katz, R. (2004). Anticipating disruptive innovation.
Research-Technology Man-
agement, 47(5), 13–22.
Petrick, I. J., & Simpson, T. W. (2013). 3D printing disrupts
manufacturing. Research-
Technology Management, 56(6), 12–16.
Porter, M. E., & Millar, V. E. (1985). How information gives
you competitive advantage.
Putnam, H. (1973). Explanation and reference. Conceptual
change (pp. 199–221).
Netherlands: Springer.
Rayna, T., & Striukova, L. (2014). The impact of 3D printing
technologies on business
model innovation. Digital Enterprise Design & Management
(pp. 119–132). Springer
International Publishing.
Rogers, E. M. (1995). Diffusion of innovations. New York: The
Free Press.
Schmidt, G. M., & Druehl, C. T. (2008). When is a disruptive
innovation disruptive?*.
Sood, A., & Tellis, G. J. (2011). Demystifying disruption: A
new model for understanding
and predicting disruptive technologies. Marketing Science,
30(2), 339–354.
Stam, W. (2009). When does community participation enhance
the performance of open

source software companies? Research Policy, 38(8), 1288–1299.
Swanson, E. B. (1994). Information systems innovation among
organizations.
Management Science, 40(9), 1069–1092.
Tellis, G. J. (2006). Disruptive technology or visionary
leadership?*. Journal of Product
Innovation Management, 23(1), 34–38.
Thomond, P., & Lettice, F. (2002, July). Disruptive innovation
explored. Cranfield Universi-
ty, Cranfield, England. Presented at: 9th IPSE International
Conference on Concurrent En-
gineering: Research and Applications (CE2002).
Tushman, M. L., & Anderson, P. (1986). Technological
discontinuities and organizational
environments. Administrative science quarterly, 439–465.
Utela, B., Storti, D., Anderson, R., & Ganter, M. (2008). A
review of process development
steps for new material systems in three dimensional printing
(3DP). Journal of
Manufacturing Processes, 10(2), 96–104.

http://refhub.elsevier.com/S0019-8501(15)30011-
0/rf0260Defining and identifying disruptive innovations1.
Defining and predicting disruptive innovations2. Literature
review2.1. Identification of disruptive innovation
characteristics2.2. Refinement of the definition of a disruptive
innovation2.3. Innovation relativity2.4. Prediction of
disruptions to organizations2.5. Prediction of disruptive
innovations specific to an organization2.6. Illustration of the 3-
step method2.6.1. Step 1: identify the innovation and its
characteristics2.6.2. Step 2: identify where in an organization's
value chain the innovation is used2.6.3. Step 3: compare the
potentially disruptive innovation with technologies currently
used in the organization for that ...3. DiscussionReferences
THE BIG IDEA
WHAT IS
44 Harvard Business Review December 2015
Twenty years after the
introduction of the
theory, we revisit
what it does—and
doesn’t—explain.
BY CLAYTON M.
CHRISTENSEN,
MICHAEL RAYNOR,

AND RORY MCDONALD
Clayton M. Christensen is
the Kim B. Clark Professor
of Business Administration
at Harvard Business
School. Michael Raynor
is a director at Deloitte
Consulting LLP. Rory
McDonald is an assistant
professor at Harvard
Business School.
HBR.ORG
December 2015 Harvard Business Review 45
The problem with conflating a disruptive in-
novation with any breakthrough that changes an
industry’s competitive patterns is that different
types of innovation require different strategic ap-
proaches. To put it another way, the lessons we’ve
learned about succeeding as a disruptive innovator
(or defending against a disruptive challenger) will
not apply to every company in a shifting market.
If we get sloppy with our labels or fail to integrate
insights from subsequent research and experience
into the original theory, then managers may end
up using the wrong tools for their context, reduc-
ing their chances of success. Over time, the theory’s
usefulness will be undermined.
This article is part of an effort to capture the state

of the art. We begin by exploring the basic tenets of
disruptive innovation and examining whether they
apply to Uber. Then we point out some common
pitfalls in the theory’s application, how these arise,
and why correctly using the theory matters. We go
on to trace major turning points in the evolution of
our thinking and make the case that what we have
learned allows us to more accurately predict which
businesses will grow.
First, a quick recap of the idea: “Disruption” de-
scribes a process whereby a smaller company with
fewer resources is able to successfully challenge
established incumbent businesses. Specifically, as
incumbents focus on improving their products
and services for their most demanding (and usually
most profitable) customers, they exceed the needs
of some segments and ignore the needs of others.
Entrants that prove disruptive begin by success-
fully targeting those overlooked segments, gaining a
foothold by delivering more-suitable functionality—
frequently at a lower price. Incumbents, chasing
higher profitability in more-demanding segments,
tend not to respond vigorously. Entrants then move
upmarket, delivering the performance that incum-
bents’ mainstream customers require, while pre-
serving the advantages that drove their early success.
When mainstream customers start adopting the en-
trants’ offerings in volume, disruption has occurred.
(See the exhibit “The Disruptive Innovation Model.”)
Is Uber a Disruptive Innovation?
Let’s consider Uber, the much-feted transportation
company whose mobile application connects con-
sumers who need rides with drivers who are willing
to provide them. Founded in 2009, the company has

Unfortunately, disruption theory is in danger of
becoming a victim of its own success. Despite broad
dissemination, the theory’s core concepts have
been widely misunderstood and its basic tenets fre-
quently misapplied. Furthermore, essential refine-
ments in the theory over the past 20 years appear to
have been overshadowed by the popularity of the
initial formulation. As a result, the theory is some-
times criticized for shortcomings that have already
been addressed.
There’s another troubling concern: In our expe-
rience, too many people who speak of “disruption”
have not read a serious book or article on the subject.
Too frequently, they use the term loosely to invoke
the concept of innovation in support of whatever it is
they wish to do. Many researchers, writers, and con-
sultants use “disruptive innovation” to describe any
situation in which an industry is shaken up and pre-
viously successful incumbents stumble. But that’s
much too broad a usage.
he theory of disruptive
innovation, introduced
in these pages in 1995,
has proved to be a
powerful way of thinking about
innovation-driven growth.
Many leaders of small,
entrepreneurial companies
praise it as their guiding star;
so do many executives at
large, well-established
organizations, including Intel,

Southern New Hampshire
University, and Salesforce.com.
THE BIG IDEA WHAT IS DISRUPTIVE INNOVATION?
46 Harvard Business Review December 201546 Harvard
Business Review December 2015
enjoyed fantastic growth (it operates in hundreds of
cities in 60 countries and is still expanding). It has
reported tremendous financial success (the most
recent funding round implies an enterprise value in
the vicinity of $50 billion). And it has spawned a slew
of imitators (other start-ups are trying to emulate its
“market-making” business model). Uber is clearly
transforming the taxi business in the United States.
But is it disrupting the taxi business?
According to the theory, the answer is no. Uber’s
financial and strategic achievements do not qualify
the company as genuinely disruptive—although the
company is almost always described that way. Here
are two reasons why the label doesn’t fit.
Disruptive innovations originate in low-end
or new-market footholds. Disruptive innovations
are made possible because they get started in two
types of markets that incumbents overlook. Low-
end footholds exist because incumbents typically
try to provide their most profitable and demanding
customers with ever-improving products and ser-
vices, and they pay less attention to less-demanding
customers. In fact, incumbents’ offerings often over-

shoot the performance requirements of the latter.
This opens the door to a disrupter focused (at first)
on providing those low-end customers with a “good
enough” product.
In the case of new-market footholds, disrupt-
ers create a market where none existed. Put simply,
they find a way to turn nonconsumers into consum-
ers. For example, in the early days of photocopying
technology, Xerox targeted large corporations and
charged high prices in order to provide the perfor-
mance that those customers required. School librar-
ians, bowling-league operators, and other small
customers, priced out of the market, made do with
carbon paper or mimeograph machines. Then in
the late 1970s, new challengers introduced personal
Idea in Brief
THE ISSUE
The ideas summed up in the
phrase “disruptive innovation”
have become a powerful part
of business thinking—but
they’re in danger of losing
their usefulness because
they’ve been misunderstood
and misapplied.
THE RESPONSE
The leading authorities
on disruptive innovation
revisit the central tenets
of disruption theory, its
development over the past
20 years, and its limitations.

THE BOTTOM LINE
Does it matter whether Uber,
say, is a disruptive innovation
or something else entirely?
It does: We can’t manage
innovation effectively if we
don’t grasp its true nature.
copiers, offering an affordable solution to individu-
als and small organizations—and a new market was
created. From this relatively modest beginning, per-
sonal photocopier makers gradually built a major
position in the mainstream photocopier market that
Xerox valued.
A disruptive innovation, by definition, starts
from one of those two footholds. But Uber did not
originate in either one. It is difficult to claim that the
company found a low-end opportunity: That would
have meant taxi service providers had overshot the
needs of a material number of customers by mak-
ing cabs too plentiful, too easy to use, and too clean.
Neither did Uber primarily target nonconsumers—
people who found the existing alternatives so expen-
sive or inconvenient that they took public transit or
drove themselves instead: Uber was launched in San
Francisco (a well-served taxi market), and Uber’s
customers were generally people already in the habit
of hiring rides.
Uber has quite arguably been increasing total
demand—that’s what happens when you develop
a better, less-expensive solution to a widespread
customer need. But disrupters start by appealing to
low-end or unserved consumers and then migrate to
the mainstream market. Uber has gone in exactly the

opposite direction: building a position in the main-
stream market first and subsequently appealing to
historically overlooked segments.
Disruptive innovations don’t catch on with
mainstream customers until quality catches
up to their standards. Disruption theory differ-
entiates disruptive innovations from what are called
“sustaining innovations.” The latter make good prod-
ucts better in the eyes of an incumbent’s existing
customers: the fifth blade in a razor, the clearer TV
picture, better mobile phone reception. These im-
provements can be incremental advances or major
HBR.ORG
breakthroughs, but they all enable firms to sell more
products to their most profitable customers.
Disruptive innovations, on the other hand, are
initially considered inferior by most of an incum-
bent’s customers. Typically, customers are not will
ing to switch to the new offering merely because it
is less expensive. Instead, they wait until its quality
rises enough to satisfy them. Once that’s happened,
they adopt the new product and happily accept its
lower price. (This is how disruption drives prices
down in a market.)
Most of the elements of Uber’s strategy seem to
be sustaining innovations. Uber’s service has rarely

been described as inferior to existing taxis; in fact,
many would say it is better. Booking a ride requires
just a few taps on a smartphone; payment is cash-
less and convenient; and passengers can rate their
rides afterward, which helps ensure high standards.
Furthermore, Uber delivers service reliably and
punctually, and its pricing is usually competitive
with (or lower than) that of established taxi services.
And as is typical when incumbents face threats from
sustaining innovations, many of the taxi compa-
nies are motivated to respond. They are deploying
competitive technologies, such as hailing apps, and
contesting the legality of some of Uber’s services.
Why Getting It Right Matters
Readers may still be wondering, Why does it matter
what words we use to describe Uber? The company
has certainly thrown the taxi industry into disarray:
Isn’t that “disruptive” enough? No. Applying the
theory correctly is essential to realizing its benefits.
For example, small competitors that nibble away at
the periphery of your business very likely should be
ignored—unless they are on a disruptive trajectory,
in which case they are a potentially mortal threat.
And both of these challenges are fundamentally
different from efforts by competitors to woo your
bread-and-butter customers.
As the example of Uber shows, identifying true
disruptive innovation is tricky. Yet even executives
with a good understanding of disruption theory tend
to forget some of its subtler aspects when making
strategic decisions. We’ve observed four important
points that get overlooked or misunderstood:

1. Disruption is a process. The term “disrup
tive innovation” is misleading when it is used to refer
to a product or service at one fixed point, rather than
to the evolution of that product or service over time.
The first minicomputers were disruptive not merely
because they were low-end upstarts when they ap-
peared on the scene, nor because they were later
heralded as superior to mainframes in many mar-
kets; they were disruptive by virtue of the path they
followed from the fringe to the mainstream.
Most every innovation—disruptive or not—
begins life as a small-scale experiment. Disrupters
tend to focus on getting the business model, rather
than merely the product, just right. When they suc-
ceed, their movement from the fringe (the low end
of the market or a new market) to the mainstream
erodes first the incumbents’ market share and then
their profitability. This process can take time, and
incumbents can get quite creative in the defense
of their established franchises. For example, more
than 50 years after the first discount department
store was opened, mainstream retail companies still
operate their traditional department-store formats.
Complete substitution, if it comes at all, may take
decades, because the incremental profit from stay-
ing with the old model for one more year trumps
proposals to write off the assets in one stroke.
The fact that disruption can take time helps to
explain why incumbents frequently overlook dis-
rupters. For example, when Netflix launched, in
1997, its initial service wasn’t appealing to most
of Blockbuster’s customers, who rented movies
(typically new releases) on impulse. Netflix had an

exclusively online interface and a large inventory of
isrupters first appeal to
low-end or unserved
customers and then
migrate to the mainstream
market. Uber has gone in the
opposite direction: building
a position in the mainstream
market first and then appealing
to historically overlooked segments.
movies, but delivery through the U.S. mail meant
selections took several days to arrive. The service ap-
pealed to only a few customer groups—movie buffs
who didn’t care about new releases, early adopters of
DVD players, and online shoppers. If Netflix had not
eventually begun to serve a broader segment of the
market, Blockbuster’s decision to ignore this com-
petitor would not have been a strategic blunder: The
two companies filled very different needs for their
(different) customers.
However, as new technologies allowed Netflix
to shift to streaming video over the internet, the
company did eventually become appealing to
Blockbuster’s core customers, offering a wider se-
lection of content with an all-you-can-watch, on-
demand, low-price, high-quality, highly convenient

approach. And it got there via a classically disruptive
path. If Netflix (like Uber) had begun by launching a
service targeted at a larger competitor’s core market,
Blockbuster’s response would very likely have been
a vigorous and perhaps successful counterattack.
But failing to respond effectively to the trajectory
that Netflix was on led Blockbuster to collapse.
2. Disrupters often build business models
that are very different from those of incum-
bents. Consider the health care industry. General
practitioners operating out of their offices often rely
on their years of experience and on test results to
interpret patients’ symptoms, make diagnoses, and
prescribe treatment. We call this a “solution shop”
business model. In contrast, a number of conve-
nient care clinics are taking a disruptive path by us-
ing what we call a “process” business model: They
follow standardized protocols to diagnose and treat
a small but increasing number of disorders.
One high-profile example of using an innova-
tive business model to effect a disruption is Apple’s
iPhone. The product that Apple debuted in 2007 was
a sustaining innovation in the smartphone market: It
targeted the same customers coveted by incumbents,
and its initial success is likely explained by product
superiority. The iPhone’s subsequent growth is bet-
ter explained by disruption—not of other smart-
phones but of the laptop as the primary access
point to the internet. This was achieved not merely
through product improvements but also through the
THE DISRUPTIVE
INNOVATION MODEL
This diagram contrasts product

performance trajectories (the red
lines showing how products or
services improve over time) with
customer demand trajectories
(the blue lines showing customers’
willingness to pay for performance).
As incumbent companies introduce
higher-quality products or services
(upper red line) to satisfy the
high end of the market (where
profitability is highest), they
overshoot the needs of low-end
customers and many mainstream
customers. This leaves an opening
for entrants to find footholds in
the less-profitable segments that
incumbents are neglecting. Entrants
on a disruptive trajectory (lower red
line) improve the performance of
their offerings and move upmarket
(where profitability is highest
for them, too) and challenge the
dominance of the incumbents.
HIGHER
LOWER
PR
O
D
U
C
T

PE
R
FO
R
M
A
N
C
E
TIME
INC
UM
BE
NT
’S S
US
TA
INI
NG
TR
AJ
EC
TO

RY
EN
TR
AN
T’S
DI
SR
UP
TIV
E T
RA
JEC
TO
RY
MAINST
REAM
LOW EN
D
OF THE
MARKE
T
LEAST P
ROFITA

BLE
PERFOR
MANCE
CUSTO
MERS W
ILL PAY
FOR
HIGH E
ND
OF THE
MARKE
T
MOST P
ROFITA
BLE
HBR.ORG
introduction of a new business model. By building a
facilitated network connecting application develop-
ers with phone users, Apple changed the game. The
iPhone created a new market for internet access and
eventually was able to challenge laptops as main-
stream users’ device of choice for going online.

3. Some disruptive innovations succeed;
some don’t. A third common mistake is to focus
on the results achieved—to claim that a company
is disruptive by virtue of its success. But success is
not built into the definition of disruption: Not every
disruptive path leads to a triumph, and not every tri-
umphant newcomer follows a disruptive path.
For example, any number of internet-based re-
tailers pursued disruptive paths in the late 1990s, but
only a small number prospered. The failures are not
evidence of the deficiencies of disruption theory;
they are simply boundary markers for the theory’s
application. The theory says very little about how
to win in the foothold market, other than to play
the odds and avoid head-on competition with
better-resourced incumbents.
If we call every business success a “disruption,”
then companies that rise to the top in very differ-
ent ways will be seen as sources of insight into a
common strategy for succeeding. This creates a dan-
ger: Managers may mix and match behaviors that are
very likely inconsistent with one another and thus
unlikely to yield the hoped-for result. For example,
both Uber and Apple’s iPhone owe their success to
a platform-based model: Uber digitally connects
riders with drivers; the iPhone connects app devel-
opers with phone users. But Uber, true to its nature
as a sustaining innovation, has focused on expand-
ing its network and functionality in ways that make
it better than traditional taxis. Apple, on the other
hand, has followed a disruptive path by building
its ecosystem of app developers so as to make the

iPhone more like a personal computer.
4. The mantra “Disrupt or be disrupted”
can misguide us. Incumbent companies do
need to respond to disruption if it’s occurring, but
they should not overreact by dismantling a still-
profitable business. Instead, they should continue
to strengthen relationships with core customers
by investing in sustaining innovations. In addition,
they can create a new division focused solely on the
growth opportunities that arise from the disrup-
tion. Our research suggests that the success of this
new enterprise depends in large part on keeping
THE UBIQUITOUS
“DISRUPTIVE
INNOVATION”
“Disruptive innovation”
and “disruptive
technology” are now
part of the popular
business lexicon, as
suggested by the
dramatic growth in
the number of articles
using those phrases
in recent years.
SOURCE FACTIVA ANALYSIS OF A WIDE VARIETY OF
ENGLISH-LANGUAGE PUBLICATIONS
2,500
2,000

1,500
1,000
500
0
1998 2000 2002 2004 2006 2008 2010 2012 2014
ARTICLES
it separate from the core business. That means that
for some time, incumbents will find themselves
managing two very different operations.
Of course, as the disruptive stand-alone business
grows, it may eventually steal customers from the
core. But corporate leaders should not try to solve
this problem before it is a problem.
What a Disruptive Innovation
Lens Can Reveal
It is rare that a technology or product is inherently
sustaining or disruptive. And when new technol-
ogy is developed, disruption theory does not dictate
what managers should do. Instead it helps them
make a strategic choice between taking a sustaining
path and taking a disruptive one.
The theory of disruption predicts that when an

entrant tackles incumbent competitors head-on, of-
fering better products or services, the incumbents
will accelerate their innovations to defend their
business. Either they will beat back the entrant by
offering even better services or products at compa-
rable prices, or one of them will acquire the entrant.
The data supports the theory’s prediction that en-
trants pursuing a sustaining strategy for a stand-
alone business will face steep odds: In Christensen’s
seminal study of the disk drive industry, only 6% of
sustaining entrants managed to succeed.
Uber’s strong performance therefore warrants ex-
planation. According to disruption theory, Uber is an
outlier, and we do not have a universal way to account
for such atypical outcomes. In Uber’s case, we believe
that the regulated nature of the taxi business is a large
part of the answer. Market entry and prices are closely
controlled in many jurisdictions. Consequently, taxi
companies have rarely innovated. Individual drivers
have few ways to innovate, except to defect to Uber.
So Uber is in a unique situation relative to taxis: It can
offer better quality and the competition will find it
hard to respond, at least in the short term.
To this point, we’ve addressed only whether or
not Uber is disruptive to the taxi business. The lim-
ousine or “black car” business is a different story,
and here Uber is far more likely to be on a disruptive
path. The company’s UberSELECT option provides
more-luxurious cars and is typically more expensive
than its standard service—but typically less expen-
sive than hiring a traditional limousine. This lower
price imposes some compromises, as UberSELECT
currently does not include one defining feature of

the leading incumbents in this market: acceptance
of advance reservations. Consequently, this offering
from Uber appeals to the low end of the limousine
service market: customers willing to sacrifice a mea-
sure of convenience for monetary savings. Should
Uber find ways to match or exceed incumbents’
performance levels without compromising its cost
and price advantage, the company appears to be
well positioned to move into the mainstream of the
limo business—and it will have done so in classically
disruptive fashion.
How Our Thinking About
Disruption Has Developed
Initially, the theory of disruptive innovation was
simply a statement about correlation. Empirical
findings showed that incumbents outperformed
entrants in a sustaining innovation context but un-
derperformed in a disruptive innovation context.
The reason for this correlation was not immediately
evident, but one by one, the elements of the theory
fell into place.
First, researchers realized that a company’s pro-
pensity for strategic change is profoundly affected
by the interests of customers who provide the re-
sources the firm needs to survive. In other words, in-
cumbents (sensibly) listen to their existing custom-
ers and concentrate on sustaining innovations as a
result. Researchers then arrived at a second insight:
ncumbent companies
should not overreact
to disruption by dismantling
a still-profitable business.

Instead they should strengthen
relationships with core
customers while also creating
a new division focused on
the growth opportunities that
arise from the disruption.
HBR.ORG
Incumbents’ focus on their existing customers be-
comes institutionalized in internal processes that
make it difficult for even senior managers to shift
investment to disruptive innovations. For example,
interviews with managers of established companies
in the disk drive industry revealed that resource allo-
cation processes prioritized sustaining innovations
(which had high margins and targeted large markets
with well-known customers) while inadvertently
starving disruptive innovations (meant for smaller
markets with poorly defined customers).
Those two insights helped explain why in-
cumbents rarely responded effectively (if at all)
to disruptive innovations, but not why entrants
eventually moved upmarket to challenge incum-
bents, over and over again. It turns out, however,
that the same forces leading incumbents to ignore
early-stage disruptions also compel disrupters
ultimately to disrupt.
What we’ve realized is that, very often, low-end
and new-market footholds are populated not by a

lone would-be disrupter, but by several comparable
entrant firms whose products are simpler, more con-
venient, or less costly than those sold by incumbents.
The incumbents provide a de facto price umbrella,
allowing many of the entrants to enjoy profitable
growth within the foothold market. But that lasts
only for a time: As incumbents (rationally, but mis-
takenly) cede the foothold market, they effectively
remove the price umbrella, and price-based com-
petition among the entrants reigns. Some entrants
will founder, but the smart ones—the true disrupt-
ers—will improve their products and drive upmar-
ket, where, once again, they can compete at the
margin against higher-cost established competitors.
The disruptive effect drives every competitor—
incumbent and entrant—upmarket.
With those explanations in hand, the theory of
disruptive innovation went beyond simple corre-
lation to a theory of causation as well. The key ele-
ments of that theory have been tested and validated
through studies of many industries, including retail,
computers, printing, motorcycles, cars, semicon-
ductors, cardiovascular surgery, management edu-
cation, financial services, management consulting,
cameras, communications, and computer-aided
design software.
Making sense of anomalies. Additional re-
finements to the theory have been made to address
certain anomalies, or unexpected scenarios, that
the theory could not explain. For example, we origi-
nally assumed that any disruptive innovation took
root in the lowest tiers of an established market—
yet sometimes new entrants seemed to be compet-

ing in entirely new markets. This led to the distinc-
tion we discussed earlier between low-end and
new-market footholds.
Low-end disrupters (think steel minimills and
discount retailers) come in at the bottom of the mar-
ket and take hold within an existing value network
before moving upmarket and attacking that stratum
(think integrated steel mills and traditional retail-
ers). By contrast, new-market disruptions take hold
in a completely new value network and appeal to
customers who have previously gone without the
product. Consider the transistor pocket radio and
the PC: They were largely ignored by manufacturers
of tabletop radios and minicomputers, respectively,
because they were aimed at nonconsumers of those
goods. By postulating that there are two flavors of
foothold markets in which disruptive innovation
can begin, the theory has become more powerful
and practicable.
Another intriguing anomaly was the identifi-
cation of industries that have resisted the forces
of disruption, at least until very recently. Higher
education in the United States is one of these. Over
the years—indeed, over more than 100 years—new
kinds of institutions with different initial charters
have been created to address the needs of various
population segments, including nonconsumers.
Land-grant universities, teachers’ colleges, two-year
colleges, and so on were initially launched to serve
those for whom a traditional four-year liberal arts
education was out of reach or unnecessary.
s there a novel technology or
business model that allows

entrants in higher education to
follow a disruptive path? The
answer seems to be yes, and the
enabling innovation is online learning.
Many of these new entrants strived to improve
over time, compelled by analogues of the pursuit of
profitability: a desire for growth, prestige, and the
capacity to do greater good. Thus they made costly
investments in research, dormitories, athletic fa-
cilities, faculty, and so on, seeking to emulate more-
elite institutions. Doing so has increased their level
of performance in some ways—they can provide
richer learning and living environments for students,
for example. Yet the relative standing of higher-
education institutions remains largely unchanged:
With few exceptions, the top 20 are still the top 20,
and the next 50 are still in that second tier, decade
after decade.
Because both incumbents and newcomers are
seemingly following the same game plan, it is per-
haps no surprise that incumbents are able to main-
tain their positions. What has been missing—until
recently—is experimentation with new models that
successfully appeal to today’s nonconsumers of
higher education.
The question now is whether there is a novel

technology or business model that allows new en-
trants to move upmarket without emulating the in-
cumbents’ high costs—that is, to follow a disruptive
path. The answer seems to be yes, and the enabling
innovation is online learning, which is becoming
broadly available. Real tuition for online courses is
falling, and accessibility and quality are improving.
Innovators are making inroads into the mainstream
market at a stunning pace.
Will online education disrupt the incumbents’
model? And if so, when? In other words, will on-
line education’s trajectory of improvement in-
tersect with the needs of the mainstream mar-
ket? We’ve come to realize that the steepness
of any disruptive trajectory is a function of how
quickly the enabling technology improves. In
the steel industry, continuous-casting technol-
ogy improved quite slowly, and it took more than
40 years before the minimill Nucor matched the
revenue of the largest integrated steelmakers. In
contrast, the digital technologies that allowed
personal computers to disrupt minicomputers
improved much more quickly; Compaq was able to
increase revenue more than tenfold and reach parity
with the industry leader, DEC, in only 12 years.
Understanding what drives the rate of disruption
is helpful for predicting outcomes, but it doesn’t al-
ter the way disruptions should be managed. Rapid
disruptions are not fundamentally different from any
others; they don’t have different causal mechanisms
and don’t require conceptually different responses.
Similarly, it is a mistake to assume that the strat-

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