10
D i g ital Tr ansformation
and C han g es in
C o nsumer B ehav ior
Introduction
Digital transformation is one of the most significant activities of the
early twenty-first century. Digital transformation is defined as “ the
changes associated with the applications of digital technology in all
aspects of human society” (Stolterman & Fors, 2004, p. 689). From a
business perspective, digital transformation enables organizations to
implement new types of innovations and to rethink business processes
that can take advantage of technology. From this perspective, digital
transformation involves a type of reengineering, but one that is not
limited to rethinking just how systems work together, but rather, that
extends to the entire business itself. Some see digital transformation
as the elimination of paper in organizations. Others see it as revamping a business to meet the demands of a digital economy. This chapter
provides a link between digital transformation and what I call “ digital
reengineering.” To explain this better, think of process reengineering
as the generation that brought together systems in the way that they
talked to one another— that is, the integration of legacy systems with
new application that used more robust software applications.
The advent of digital transformation requires the entire organization
to meet the digital demands of their consumers. For some companies, the
usiness-to-business), that is, the
consumer is another company (B2B, or b
consumer is a provider to another company that inevitably supports a consumer. For other businesses, their consumer is indeed the ultimate buyer.
I will discuss the differences in these two types of consumer concepts later
in this chapter. What is important from an IT perspective is that reengineering is no longer limited to just the needs of the internal user, but rather
the needs of the businesses consumer as well. So, systems must change,
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as necessary, with the changes in consumer behavior. The challenge with
doing this, of course, is that consumer needs are harder to obtain and
understand, and can differ significantly among groups, depending on
variables, such as ethnicity, age, and gender, to name just a few.
As a result, IT managers need to interact with the consumer more
directly and in partnership with their business colleagues. The consumer represents a new type of user for IT staff. The consumer, in
effect, is the buyer of the organization’ s products and services. The
challenge becomes how to get IT more engaged with the buyer community, which could require IT to be engaged in multiple parts of
the business that deals with the consumer. Below are six approaches,
which are not mutually exclusive of each other:
1. Sales/Marketing : These individuals sell to the company’ s buyers. Thus, they have a good sense of what customers are looking for, what things they like about the business, and what
they dislike. The power of the sales and marketing team is
their ability to drive realistic requirements that directly impact
revenue opportunities. The limitation of this resource is that
it still relies on an internal perspective of the consumer; that
is, how the sales and marketing staff perceive the consumer’ s
needs.
2. Third-party market analysis/reporting : There are outside
resources available that examine and report on market trends
within various industry sectors. Such organizations typically
have massive databases of information and, using various
search and analysis tools, can provide a better understanding of the behavior patterns of an organization’ s consumers.
These third parties can also provide reports that show how the
organization stacks up against its competition and why consumers may be choosing alternative products. Unfortunately,
if the data is inaccurate it likely will result in false generalizations about consumer behavior, so it is critical that IT digital
leaders ensure proper review of the data integrity.
3. Predictive analytics : This is a hot topic in today’ s competitive
landscape for businesses. Predictive analytics is the process
of feeding off large data sets (big data) and predicting future
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behavior patterns. Predictive analytics approaches are usually
handled internally with assistance from third-party products
or consulting services. The limitation is one of risk— the risk
that the prediction does not occur as planned.
4. Consumer support departments: Internal teams and external
vendors (outsourced managed service) have a good pulse
on consumer preferences because they interact with them.
More specifically, these department respond to questions,
hande problems and get feedback from consumers on a regular basis. These support departments typically depend on
applications to help the buyer. As a result, they are an excellent resource for providing up-to-date things that the system does not provide consumers. Unfortunately, consumer
support organizations limit their needs to what they experience as opposed to what might be future trends of their
consumers.
5. Surveys: IT and the business can design surveys (questionnaires) and send them to consumers for feedback. Using
surveys can be of significant value in that the questions can
target specific issues that the organization wants to address.
Survey design and administration can be handled by thirdparty firms, which may have an advantage in that the questions are being forwarded from an independent source and
one that does not identify the interested company. On the
other hand, this might be considered a negative— it all
depends on what the organization is seeking to obtain from
the buyer.
6. Focus groups: This approach is similar to the use of a survey.
Focus groups are commonly used to understand consumer
behavior patterns and preferences. They are often conducted
by outside firms. The differences between the focus group
and a survey are (1) surveys are very quantitative based and
use scoring mechanisms (Likert scales) to evaluate outcomes.
Consumers sometimes may misinterpret the question thus
resulting in distorted feedback, and (2) focus groups are more
qualitative and allow IT digital leaders to engage with the
consumer in two-way dialogues.
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Figure 10.1 reflects a graphic depiction of the sources for understanding consumer behaviors and needs.
Table 10.1 further articulates the methods and deliverables that IT
digital leaders should consider when developing system strategies.
Requirements without Users and without Input
Could it be possible to develop digital strategies and requirements for
a system without user input or even consumer opinions? Could this be
a reality for future design of strategic systems?
Perhaps we need to take a step back historically and think about
trends that have changed the competitive landscape. Digital transformation may indeed be the most powerful agent of change in the
history of business.
Surveys
Internal/external
targeted consumers
Consumer support
departments
Internal support
groups, third-party
call centers,
shared services
organization
Focus groups
Internal/external
consumer sessions
Sales/marketing
Product
requirements
Staff
competitive analysis
Third-party studies
and databases
Trends
Data analysts
Predictive analytics
Figure 10.1 Sources for understanding consumer behavior.
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Table 10.1
ANALYST’ S
SOURCES
Sales/
Marketing
Langer’ s Methods and Deliverables for Assessing Consumer Needs
METHODS
Interviews
Win/loss sales
reviews
Third-Party
Databases
Support
Department
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Document
reports
reviews
Data analysis
Predictive
analytics
Interviews
Data/reports
Surveys
Internal and
external
questionnaires
Focus Groups
Hold internal
and external
sessions
DELIVERABLES
Should be conducted in a similar way to typical end user
interviews. Work closely with senior sales staff. Set up
interviews with key business stakeholders.
Review the results of sales efforts. Many firms hold formal
win/loss review meetings that may convey important
limitations of current applications and system
capabilities.
Obtain summaries of the trends in consumer behavior and
pinpoint shortfalls that might exist in current applications
and systems.
Perform targeted analytics on databases to uncover trends
not readily conveyed in available reports.
Interrogate data by using analytic formulas that may
enable predictive trends in consumer behavior.
Interview key support department personnel (internal and
third party) to identify possible application deficiencies.
Review call logs and recorded calls between consumers
and support personnel to expose possible system
deficiencies.
Work with internal departments to determine application
issues when they support consumers. Use similar surveys
with select populations of customers to validate and
fine-tune internal survey results.
Use similar surveys targeted to consumers who are not
customers and compare results. Differences between
existing customer base and non-customers may expose
new trends in consumer needs.
Internal focus groups can be facilitated by marketing
personnel. Select survey results, that had unexpected
results or mixed feedback can be reviewed. Internal
attendees should come from operations management and
sales. External focus groups should be facilitated by a
third-party vendor and held at independent sites.
Discussions with customers should be compared with
internal focus group results. Consumer focus groups
should be facilitated by professional third-party firms.
We have seen large companies lose their edge. IBM’ s fall as the
leading technology firm in the 1990s is an excellent example, when
Microsoft overtook them. Yet Google was able to take the lead away
from Microsoft, particularly in relation to analytical consumer computing. And what about the comeback Apple made with its new array
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of smart phone-related products? The question is, Why and how do
these shifts in competitive advantage occur so quickly?
Technology continues to generate change and that change is
typically referred to today as a “ digital disruption.” The challenge
in disruption is the inability to predict what consumers want and
need; furthermore, the consumer may not know! The challenge,
then, is for IT digital leaders to forecast the changes that are
brought about by technology disruptions. So, digital transformation is more about predicting consumer behavior and providing
new products and services, which we hope consumers will want.
This is a significant challenge for IT leaders, of course, given that
the profession was built on the notion that good specifications
accurately depicted what users want. Langer (1997) originally
defined this as the “ Concept of the Logical Equivalent.” So, we
may have created an oxymoron— how do we develop systems that
the user cannot specify? Furthermore, requirements that depict
consumer behavior are now further complicated by the globalization of business. Which consumer behavior are we attempting to
satisfy and across what societal cultural norms? The reality is that
new software applications will need to be built with some uncertainty. That is, some business rules may be vague and risks will
need to be part of the process of system functionality. To see an
example of designing systems based on uncertainty, we need only
to analyze the evolution of the electronic spreadsheet. The first
electronic spreadsheet, called VisiCalc, was introduced by a company called VisiCorp. It was designed for the Apple II and eventually the IBM personal computer. The electronic spreadsheet was
not designed based on consumer input per se, rather on perceived
needs by visionary designers who saw a need for a generic calculator and mathematical worksheet. VisiCorp took a risk by offering a product to the market that consumers would find useful. Of
course, history shows that it was a very good risk. The electronic
spreadsheet, which is now dominated by Microsoft’ s Excel product
has gone through multiple product generations. The inventors of
the electronic spreadsheet had a vision and the market responded
favorably. Although VisiCorp’ s vision of the market need was correct, the first version was hardly 100% accurate of what consumers
would want in a spreadsheet. For example, additional features, such
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as a database interface, three-dimensional spreadsheets to support
budgeting and forward referencing, are all examples of responses
from consumers that resulted in new product enhancements.
Allen and Morton (1994) established an excellent graphic depiction of the relationship between technology advancements and market needs (Figure 10.2)
Figure 10.2 shows an interesting life cycle of how product innovations
relate to the creation of new products and services. The diagram reflects
that innovations can occur as a result of new technology capabilities or
inventions that establish new markets—like the electronic spreadsheet.
On the other hand, the market can demand more features and f unctions
the technology organizations or developers need to respond to that—like
the upgrades made over the years to spreadsheet applications. Responding
to market needs are what most organizations have practiced over the past
60 years, usually working with their end user populations (those internal
users that supported the actual consumer). The digital revolution; however, is placing more emphasis on “generic” applications that resemble the
object paradigm (one that requires applications to be able to fit into any
business application). This trend will drive new and more advanced objectdriven applications. These applications will reside in a more robust object
functioning library that can dynamically link these modules together to
form specific applications that can support mul consumer devices (what is
now being called the “Internet of Things”).
Another useful approach to dealing with consumer preferences is
Porter’ s Five Forces Framework. Porter’s framework consists of the
following five components:
1. Competitors : What is the number of competitors in the market
and what is the organization’ s position within the market?
Technology
Innovation
Market
Figure 10.2 Technology, innovation, and market needs.
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2. New entrants : What companies can come into the organization’ s space and provide competition?
3. Substitutes: What products or services can replace what you do?
4. Buyers : What alternatives do buyers have? How close and
tight is the relationship between the buyer and seller?
5. Suppliers : What is the number of suppliers that are available,
which can affect the relationship with the buyer and also
determine price levels?
Porter’ s framework is graphically depicted in Figure 10.3.
Cadle et al. (2014) provide an approach to using Porter’ s model as
part of the analysis and design process. Their approach is integrated
with Langer’ s Analysis Consumer Methods in Table 10.2.
Concepts of the S-Curve and Digital
Transformation Analysis and Design
Digital transformation will also be associated with the behavior of the
S-curve. The S-curve has been a long-standing economic graph that
depicts the life cycle of a product or service. The S-curve is shown in
Figure 10.4
New
entrants
Consumer
support dept.
Suppliers
Industry
competitors
(sales and
marketing)
Substitutes
New products
or services
Figure 10.3 Porter’ s Five Forces Framework.
Sales and
marketing
Buyers
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Table 10.2 Langer’ s Analysis Consumer Methods
PORTER’ S FIVE FORCES
Industry competitors
New entrants
Suppliers
Buyers
Substitutes
CADEL ET AL’ S APPROACH
How strong is your market
share?
New threats
Price sensitivity and closeness
of relationship.
Alternative choices and brand
equity.
Consumer alternatives
LANGER’ S SOURCES OF INPUT
Third-party market studies
Third-party market studies
Surveys and focus groups
Consumer support and end user
departments
Sales/marketing team
Surveys and focus groups
Sales and marketing team
Third‑party studies
The left and lower portion of the S-curve represents a growing
market opportunity that is likely volatile and exists where demand
exceeds supply. As a result, the market opportunity is large and prices
for the product are high. Thus, businesses should seek to capture as
much of the market share at this time before competitors catch up.
This requires the business to take more risk and assumes that the market will continue to demand the product. The shape of the S-curve
suggests the life of this opportunity (the length of the x-axis represents the lifespan of the product).
As the market approaches the middle of the center of the S-curve,
demand begins to equal supply. Prices start to drop and the market, in
general, becomes less volatile and more predictable. The drop in price
reflects the presence of more competitors. As a product or service
approaches the top of the S, supply begins to exceed demand. Prices
begin to fall and the market is said to have reached maturity. The
uniqueness of the product or service is now approaching commodity.
Figure 10.4
The S-curve.
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Figure 10.5 Extended S-curve.
Typically, suppliers will attempt to produce new features and functions to extend the life of the curve as shown in Figure 10.5
Establishing a new S-curve, then, extends the competitive life of
the product or service. Once the top of the S-curve is reached, the
product or service has reached the commodity level, where supply is
much greater than demand. Here, the product or service has likely
reached the end of its useful competitive life and should either be
replaced with a new solution or considered for outsourcing to a thirdparty who can deliver the product at a very low price.
Langer’ s Driver/Supporter depicts the life cycle of any application
or product as shown in Figure 10.6
Organizational Learning and the S-Curve
When designing a new application or system, the status of that
product’ s S-curve should be carefully correlated to the source of the
Technology
driver
Mini loop technology enhancements
Evaluation
cycle
Driver
maturation
Support
status
Economies
of scale
Replacement or
outsource
Figure 10.6 Langer’ s drive/supporter life cycle.
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Table 10.3 S-Curve, Application Requirement Sources, and Risk
S-CURVE STATUS
Early S-curve
High S-curve
ANALYSIS INPUT
SOURCE
Consumer
Consumer
End users
Crest of the
S-curve
End users
Consumer
End of S-curve
End user
RISK FACTOR
High; market volatility and uncertainty.
Lower; market is less uncertain as product becomes
more mature.
Medium; business users have experience with
consumers and can provide reasonable requirements.
Low; business users have more experience as product
becomes mature.
High; might consider new features and functions to
keep product more competitive. Attempt to establish
new S-curve.
None; seek to replace product or consider third-party
product to replace what is now a legacy application.
Also think of outsourcing application.
requirements. Table 10.3 reflects the corresponding market sources
and associated risk factors relating to the dependability of requirements based on the state of the consumer’ s market. Leaders engaged
in this process obviously need to have an abstract perspective to support a visionary and risk-oriented strategy. Table 10.3 includes the
associated complexity of staff needed to deal with each period in the
S-curve.
Communities of Practice
As stated in Chapter 4, Communities of Practice (COP) have been
traditionally used as a method of bringing together people in organizations with similar talents, responsibilities and/or interests. Such
communities can be effectively used to obtain valuable information
about the way things work and what is required to run business operations. Getting such information strongly correlates to the challenges of
obtaining dependable information from the consumer market. I discussed the use of surveys and focus groups earlier in this chapter, but
COP is an alternative approach to bringing together similar types of
consumers grouped by their interests and needs. In digital transformation we find yet another means of obtaining requirements by engaging
in, and contributing to, the practices of specific consumer communities.
This means that working with COP offers another way of developing
relations with consumers to better understand their needs. Using this
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approach inside an organization, as we saw in Chapter 4, provides a
means of better learning about issues by using a sustained method of
remaining interconnected with specific business user groups, which can
define what the organization really knows and contributes to the business that is typically not documented. IT digital leaders need to become
engaged in learning if they are to truly understand what is needed to
develop more effective and accurate software applications.
It seems logical that COP can provide the mechanism to assist IT
digital leaders with an understanding of how business users and consumers behave and interact. Indeed, the analyst can target the behavior
of the community and its need to consider what new organizational
structures can better support emerging technologies. I have, in many
ways, already established and presented what should be called the
“community of IT digital leaders” and its need to understand how to
restructure, in order to meet the needs of the digital economy. This new
era does not lend itself to the traditional approaches to IT strategy, but
rather to a more risk-based process that can deal with the realignment
of business operations integrated with different consumer relationships.
The relationship, then, between COP and digital transformation is
significant, given that future IT applications will heavily rely on informal inputs. While there may be attempts to computerize knowledge
using predictive analytics software and big data, it will not be able
to provide all of the risk-associated behaviors of users and consumers. That is, a “ structured” approach to creating predictive behavior
reporting, is typically difficult to establish and maintain. Ultimately,
the dynamism from digital transformations creates too many uncertainties to be handled by sophisticated automated applications on how
organizations will react to digital change variables. So, COP, along
with these predictive analytics applications, provides a more thorough
umbrella of how to deal with the ongoing and unpredictable interactions established by emerging digital technologies.
The IT Leader in the Digital Transformation Era
When we discuss the digital world and its multitude of effects on how
business is conducted, one must ask how this impacts the profession
of IT Leader. This section attempts to address the perceived evolution
of the role.
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1. The IT leader must become more innovative. While the
business has the problem of keeping up with changes in
their markets, IT needs to provide more solutions. Many
of these solutions will not be absolute and likely will have
short shelf lives. Risk is fundamental. As a result, IT leaders must truly become “ business” leaders by exploring new
ideas from the outside and continually considering how
to implement the needs of the company’ s consumers. As
a result, the business analyst will emerge as an idea broker (Robertson & Robertson, 2012) by constantly pursuing
external ideas and transforming them into automated and
competitive solutions. These ideas will have a failure rate,
which means that companies will need to produce more
applications than they will inevitably implement. This will
certainly require organizations to spend more on software
development.
2. Quality requirements will be even more complex. In order to
keep in equilibrium with the S-curve the balance between
quality and production will be a constant negotiation.
Because applications will have shorter life cycles and there
is pressure to provide competitive solutions, products will
need to sense market needs and respond to them quicker. As
a result, fixes and enhancements to applications will become
more inherent in the development cycle after products go
live in the market. Thus, the object paradigm will become
even more fundamental to better software development
because it provides more readily tested reusable applications
and routines.
3. Dynamic interaction among users and business teams will
require the creation of multiple layers of communities of practice. Organizations involved in this dynamic process must
have autonomy and purpose (Narayan, 2015).
4. Application analysis, design, and development must be treated
and managed as a living process; that is, it never ends until the
product is obsolete (supporter end). So, products must continually develop to maturity.
5. Organizations should never outsource a driver technology
until it reaches supporter status.
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How Technology Disrupts Firms and Industries
The world economy is transforming rapidly from an analogue to a
digital-based technology-driven society. This transformation requires
businesses to move from a transactional relationship to one that that
is “ interactional” (Ernst & Young, 2012). However, this analogue to
digital transformation, while essential for a business to survive in the
twenty-first century, is difficult to accomplish. Langer’ s (2011) theory
of responsive organizational dynamism (ROD), as discussed earlier in
this book, is modified to show that successful adaptation of new digital technologies called Digital Dynamisms requires cultural assimilation of the people that comprise the organization.
Dynamism and Digital Disruption
The effects of digital dynamism can also be defined as a form of
disruption or what is now being referred to as digital disruption .
Specifically, the big question facing many enterprises is around how
they can anticipate the unexpected threats brought on by technological advances that can devastate their business. There are typically two
disruption factors:
1. A new approach to providing products and services to the
consumer.
2. A strategy not previously feasible, now made possible using
new technological capabilities.
Indeed, disruption occurs when a new approach meets the right
conditions. Because technology shortens the time it takes to reach
consumers, the changes are occurring at an accelerated and exponential pace. As an example, the table below shows the significant acceleration of the time it takes to reach 50 million consumers:
Radio
Television
Internet
Facebook
Twitter
Instagram
Poké mon GO
38 years
13 years
4 years
3.5 years
9 months
6 months
19 days
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The speed of which we can accelerate change has an inverse effect
on the length of time the effect lasts. We use the S-curve to show how
digital disruption shortens the competitive life of new products and
services. Figure 10.7 represents how the S-curve is shrinking along
the x-axis, which measures the length or time period of the product/
service life.
Figure 10.7 essentially reflects that the life of a product or service is
shrinking, thus enterprises have less time to capture a market opportunity and far less time to enjoy the length of its competitive success. As a result, business leaders are facing a world that is changing
at an accelerating rate and trying to cope with understanding how
new waves of “ disruptive” technologies will affect their business.
Ultimately, digital disruption shifts the way competitive forces deliver
services, requires change in the way operations are managed and measured, and shortens the life of any given product or service success.
Critical Components of “ Digital” Organization
A study conducted by Westerman et al. (2014), who interviewed 157
executives in fifty large companies, found four capabilities that were
key to successful digital transformation:
1. A unified digital platform : Integration of the organization’ s
data and processes across its department silos is critical. One
reason why web-based companies gain advantage over traditional competitors is their ability to use analytics and customer
personalization from central and integrated sources. Thus,
the first step toward a successful digital transformation is for
companies to invest in establishing central repositories of data
and common applications that can access the information.
Figure 10.7 The shrinking S-curve.
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This centralization of digital data is key to competing globally
since firms must be able to move data to multiple locations
and use that data in different contexts.
2. Solution delivery : Many traditional IT departments are not
geared to integrating new processes into their legacy operations. A number of firms have addressed this problem by
establishing independent “ innovation centers” designed to
initiate new digital ideas that are more customer solution oriented. These centers typically focus on how new mobile and
social media technologies can be launched without disturbing the core technology systems that support the enterprise.
Some of these initiatives include partnerships with high-tech
vendors; however, a number of executives have shown concern
that such alliances might result in dependencies because of
the lack of knowledge inside the organization.
3. Analytics capabilities : Companies need to ensure that their
data can be used for predictive analytics purposes. Predictive
analytics provide actors with a better understanding of their
consumer’ s behaviors and allow them to formulate competitive strategies over their competitors. Companies that integrate data better from their transactional systems can make
more “ informed and better decisions” and formulate strategies to take advantage of customer preferences and thus, turn
them into business opportunities. An example is an insurance
company initiative that concentrates on products that meet
customer trends determined by examining their historical
transactions across various divisions of the business. Analytics
also helps organizations to develop risk models that can assist
them to formulate accurate portfolios.
4. Business and IT integration : While the integration of the IT
department with the business has been discussed for decades,
few companies have achieved a desired outcome (Langer,
2016). The need for digital transformation has now made this
integration essential for success and to avoid becoming a victim of disruption. True IT and business integration means
more than just combining processes and decision making; but
rather, the actual movement of personnel into business units
so they can be culturally assimilated (Langer & Yorks, 2013).
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Assimilating Digital Technology Operationally and Culturally
When considering how to design an organization structure that
can implement digital technologies, firms must concentrate on how
to culturally assimilate a new architecture. The importance of the
architecture first affects the strategic integration component of
ROD. Indeed, the actor-oriented architecture must be designed to
be agile enough to react to increased changes in market demands.
The consumerization of technology, defined as changes in technology brought on by increased consumer knowledge of how digital
assets can reduce costs and increase competitive advantage, have
created a continual reduction in the length of any new competitive
products or services life. Thus, consumerization has increased what
Eisenhardt and Bourgeouse (1988) define as “ high-velocity” market
conditions.
This dilemma drives the challenge of how organizations will cope
to avoid the negative effects of digital disruption. There are four overall components that appear to be critical factors of autonomy from
disruption:
1. Companies must recognize that speed and comfort of service
can be more important than just the cost: our experience is
that enterprises who offer multiple choices that allow consumers to choose from varying levels of service options are
more competitive. The more personal the service option, the
higher the cost. Examples can be seen in the airline industry where passengers have options for better seats at a higher
price, or a new option being offered by entertainment parks
that now provide less wait time on shorter lines, for higher
paying customers. These two examples match the price with
a desired service and firms that do not offer creative pricing
options are prime for disruption.
2. Empower your workforce to try new ideas without over controls. Companies are finding that many young employees have
new service ideas but are blocked from trying them because
of the “ old guard” in their management reporting lines. Line
managers need to be educated on how to allow their staffs to
quickly enact new processes, even though some of them may
not be effective.
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3. Allow employees and customer to have choice of devices.
Traditionally IT departments desire to create environments
where employees adhere to standard hardware and software
structures. Indeed, standard structures make it easier for IT
to support internal users and provide better security across
systems. However, as technology has evolved, the relation
between hardware and software, especially in mobile devices,
has become more specialized. For example, Apple smartphones have proprietary hardware architectures that in many
cases require different versions of application software as well
as different security considerations than its major competitor, Samsung. With the consumerization of technology, these
IT departments must now support multiple devices because
both their customers and employees are free to select them.
Therefore, it is important to allow staff to freely integrate
company applications with their personal device choices.
4. Similar to (3), organizations who force staff to adhere to strict
processes and support structures are exposed to digital disruption. Organizational structures that rely on technological
innovation must be able to integrate new digital opportunities seamlessly into their current production and support processes. Specifically, this means having the ability to be agile
enough to provide services using different digital capabilities
and from different geographical locations.
Conclusion
This chapter has provided a number of different and complex aspects
of digital transformation, its effects on how organizations are structured and how they need to compete to survive in the future. The
technology executive is, by default, the key person to lead these digital transformation initiatives because of the technical requirements
that are at the center of successfully completing these projects. As
such, these executives must also focus on their own transformation as
leaders that allows them to help form the strategic goals to meet the
dynamic changes in consumer behavior.
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