"And Then a Miracle Occurs …" - Engaging the challenge of operationalizing theories of success in digital transformation

Abstract

Digital transformation programs do not have an enviable track record of success. The technical potential of digital technologies is seemingly limitless but it must be grounded in a clear understanding of how the firm creates fundamental values. While there are significant differences between startup firms with no existing business infrastructure and well-established firms seeking to leverage benefits from applying digital technologies to existing operations, both rely on an underlying theory of success. In the case of a completely new business, a built-in approach to integrating digital technology with the basic theory of success is appropriate. For existing businesses with business models in place, the integration could result in a bolted-on approach. This has some unique challenges, not least in relation to employee resistance and acceptance. Digital leadership is about building a shared theory of success for digital business transformation. Developing management flight simulators (MFS) helps to surface assumptions and beliefs about current business model behavior and aims to enhance learning about the consequences of changing the logic of the business model. Systems thinking and modeling provides a powerful approach to developing dynamic business models for operationalizing and communicating the utilization of innovative digital technology.

Full text

“And Then a Miracle Occurs …” - Engaging the challenge of operationalizing
theories of success in digital transformation
Michael VON KUTZSCHENBACH
Institute for Information Systems, School of Business
University of Applied Sciences and Arts Northwestern Switzerland
CH-4002 Basel, Switzerland
ABSTRACT
Digital transformation programs do not have an enviable
track record of success. The technical potential of digital
technologies is seemingly limitless but it must be
grounded in a clear understanding of how the firm creates
fundamental values.
While there are significant differences between startup
firms with no existing business infrastructure and well-
established firms seeking to leverage benefits from
applying digital technologies to existing operations, both
rely on an underlying theory of success. In the case of a
completely new business, a built-in approach to
integrating digital technology with the basic theory of
success is appropriate. For existing businesses with
business models in place, the integration could result in a
bolted-on approach. This has some unique challenges, not
least in relation to employee resistance and acceptance.
Digital leadership is about building a shared theory of
success for digital business transformation. Developing
management flight simulators (MFS) helps to surface
assumptions and beliefs about current business model
behavior and aims to enhance learning about the
consequences of changing the logic of the business
model.
Systems thinking and modeling provides a powerful
approach to developing dynamic business models for
operationalizing and communicating the utilization of
innovative digital technology.
Keywords: Digital Transformation, Digitalization,
Wicked Problem, Business Model, Theory of Success,
Systems Thinking, Management Flight Simulator, Digital
Leadership.
1. INTRODUCTION – THEY KNOW NOT WHAT
THEY DO (OR HOW TO DO IT)
All ideas for new products, markets, innovations and
organizations arise from an idea in the mind(s) of people
who are interested in developing them. Regardless of the
origin of the ideas, if they are seen as having potential,
then the next step will be to develop the means to achieve
the desired objectives. When managers plan, they
anticipate what may happen in the future in order to
decide what to do in the present. At this stage, the idea
becomes more structured, taking the form of a business
model and plans for implementation. As the humorous
cartoon in Figure 1 illustrates, there is often a gap
between the initial ideation and enthusiastic activity and
the realization of desired results.
This gap is generally filled by the 'business plan' or
model (see [1]). Teece [2] describes business models as
being either implicit or explicit architectures that a
business enterprise employs to create value. It is the
managers' hypothesis regarding how the firm can be
organized and operated to meet customers' expectations
and demands, at a profit. Thus, business models can be
interpreted as cognitive schemas. They are the implicit
cognitive structures that emerge from the mental models
held by the managers in the organization [3].
Fig. 1: ”Then a Miracle Occurs” (modified from [4])
In digital business transformation management, a
business model is often used as the blueprint for how a
firm might conduct business by implementing digital
technologies. In this way it translates strategic issues into
goals and actions and specifies how the conceptual model
is converted into a viable operational form.
Digital transformation programs and business models
changes due to innovative information technologies are
particularly complex and uncertain. Accordingly, the
analysis and understanding of the business model is
crucial in maximizing the utilization of new technology
and understanding its consequences.
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There are a variety of approaches used to develop and
analyze business models. The most recently used one is
the business model canvas [5]. This tool provides a
business model framework by addressing nine building
blocks: key partners, key resources, key activities, value
proposition, customer relationships, channels, customer
segments, cost structure, and revenue streams.
Aside from the advantages of standardizing the
development of a business model and supporting better
communicating of the business idea and its
operationalization, the business model canvas is weak on
explaining the causal relationships between the involved
elements and their dynamics over time ([6], [7]). In
particular, when addressing the issue of how strategic
changes such as digital transformation programs will
affect an established business the business model canvas
is limited due to its static perspective.
Systems thinking is both a philosophy and a methodology
for understanding the behavior of complex dynamic
systems, of which business organizations are an
important exemplar [8]. Furthermore, complex and
adapting systems make learning about them difficult and
consequently ordinary decision-making becomes fraught
with problems. In particular, in the case of managing
business transformations, decision-makers usually do not
have the time to wait and see if their interventions are
going to work well, and then readjust accordingly.
Systems thinking and modeling offer a set of tools that
support communications and engagement with
stakeholders as well as processes for learning and
designing actions within these complex systems.
2. PROBLEM STATEMENT - WHY DO SO MANY
WELL-INTENTIONED DIGITAL
TRANSFORMATION EFFORTS GO ASTRAY
Digital transformation challenges are far from technical
(routine) challenges. Research has shown that many
organizations have trouble in readily transforming their
activities and structures to take advantage of new
information technologies effectively [9].
Despite the proliferation of digital transformation
initiatives, most executives recognize that their
organizations are not adequately prepared. Nearly 90% of
respondents to a 2015 global survey of executives and
managers, conducted by MIT Sloan Management Review
and Deloit [10], agreed with the statement "[d]igital
technologies have the potential to fundamentally
transform the way people in their organization work.”
However, at the same time, only 44% of this group of
respondents indicated that their organizations are
adequately prepared, as they know their business and are
able “to conceptualize how digital technologies can
impact current business processes/models". 44% of this
group indicated that businesses lack the “willingness to
experiment and take risks”.
Transforming an existing business model with the help of
innovative information technologies is far from a routine
task. Some key challenges to digital transformation
management are:
- Developing digital strategies are often based on
incomplete, fuzzy, or ambiguous data;
- Because of uncertainty and time delays in the real
world, it is difficult to link investment in digital
transformation programs to real world outcomes;
- It’s difficult to create buy-in among key stakeholders
due to diverse interests and perspectives, agendas and
perspectives, and languages; and
- People do not have a shared definition (that is a
common understanding) of a digital organization.
Consequently, most digital transformation initiatives are
complex challenges. The distinction between routine and
complex challenge, can also be related to Rittel and
Webber’s [11] typology of ‘tame’ (routine) and ‘wicked’
(complex) problems. A ‘tame problem’ may be
complicated but there is a known solution/routine to
follow in order to resolve it. Thus, it is resolvable through
unilinear acts and it is likely to have occurred before.
Tame problems are akin to puzzles – for which there is
always an answer and therefore formal analysis is a
sufficient approach to problem solving – simply apply a
proven approach properly and the best solution will
naturally emerge. Various digital transformation
management frameworks have been developed to provide
appropriate processes to successfully manage digital
business transformation endeavors.
Conversely, a complex challenge is a situation without an
established set of standard process about how to solve the
problem. Horst Rittel coined the term “wicked problems”
to describe “… that class of problems which are ill-
formulated, where the information is confusing, where
there are many decision makers and clients with
conflicting values, and where the ramifications in the
whole system are confusing” ([12], p. B141) Digital
transformation initiatives that enable the organization to
enter completely new competitive environments are
‘wicked problems.’ They are more complex, rather than
just complicated – that is, they cannot be removed from
their environment, solved, and returned without affecting
the environment.
The essence of the digital transformation challenge was
well captured by Schön [13]: “In the swampy lowland,
messy, confusing problems defy technical solution. The
irony of this situation is that the problems of the high
ground tend to be relatively unimportant to individuals or
society at large, however great their technical interest
may be, while in the swamp lie the problems of greatest
human concern.” The quotation highlights a fundamental
feature of organizations. They are comprised of tightly
inter-related systems that must operate harmoniously for
proper performance. In this system, making changes to
one subsystem (the technical) will also affect the other
subsystem (the social). Digital transformations have
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significant implications for both subsystems with the
consequences of “going digital” becoming apparent only
after some time delay and in unexpected areas of the firm
or its environment [14].
Three ways an organization can react include generating
unintended consequences, demonstrating counterintuitive
behaviors, and pushback, or policy resistance, from key
stakeholders ([15], [8]). One potential explanation for
these dysfunctions can be found in the perspectives that
the people in charge have on the system and their
understanding of how it functions, that is their theory of
success [16]. The cognitive organizing structures that
decision-makers rely upon, known as mental models, are
the collection of assumptions, routines, and networks of
causal relations that describes how a system operates.
Consequently, the quality of transformation road map
planning and decision-making depends on the adequacy
of the mental models – their theory of success - in the
problem context.
While there is no foolproof method for avoiding the
undesirable reactions to change, one effective antidote to
relying on a linear routine framework (which is what
most digital transformation frameworks are based on) is
to adopt a feedback systems [17] view of the digital
transformation initiative. This is an effective alternative
perspective that enables managers to recognize the
importance of relationships between and among
organizational stakeholders and to identify the interaction
dynamics of actions, results, and reactions in a closed
loop system.
3. MODELING FOR LEARNING - MAKING
THEORIES OF SUCCESS EXPLICIT
Embarking on a strategy that involves digital
transformation introduces significant uncertainties for
many organizations. The degree of digital transformation
has a broad range of consequences. At one level, digital
transformation can result in incremental initiatives that
affect organizational efficiency (digitization, according to
[18]), but which requires no significant changes to the
core business model. At the other end of the spectrum,
digital transformation (digitalization, according to [19])
can enable the organization to enter completely new
competitive environments. In this case, efficacy is a key
organizational attribute and the business model must be
resistant to a wide range of influences. These new
competitive conditions present the organization with a
strategic wicked problem [20]. Therefore, the strategic
focus of the firm's business model must emphasize
learning, rather than optimization. It is under these
conditions that business models serve as powerful
learning tools.
When the business model is operationalized using system
dynamics tools, it becomes the basis for a type of
simulation model called a management flight simulator
(MFS). Flight simulators are employed in a wide range of
complex training situations, the best known being pilot
training and plant operations. Flight simulators provide
training in routine operations, but are perhaps most
effective in supporting decision making in 'real-time'
emergency situations. MFS simulations of complex
operational and strategic issues in businesses and other
organizations have a long history in systems thinking and
modeling [21].
A management flight simulator (MFS) is a virtual world
[22], or a learning laboratory, that is ideal in applications
where real-life experimentation is unethical or otherwise
impractical. A flight simulator permits the exploration of
both short- and long-term consequences of strategic plans
under controlled conditions. Through applying the system
dynamics methodology, MFS promote understanding of
the underlying feedback structures that generate complex
dynamic organizational behavior. When experimentation
is too costly, unethical or just plain impossible, when the
(un-)intended consequences of the decisions are difficult
to track over time or place, when multiple stakeholders
have different perceptions about the issue, which is the
case for almost all digital business transformation
initiatives, simulation becomes the main - perhaps the
only - way decision-makers can discover how complex
systems work and where high leverage points may lie.
At the core of the virtual world is the firm's theory of
success in the strategic environment. The process of
developing the MFS is also an explication of the firm's
operational business model. This is the missing step in
Figure 1. The learning component is strengthened
through the group effort needed to construct the
simulator. Key in this process is surfacing assumptions
and beliefs that underpin the theory of success, specifying
the positive feedback loops that generate growth and,
crucially, identifying the negative feedback loops. The
latter are important in identifying the situations where
insufficient strategic resources (financial, human, service
infrastructure, and knowledge, for example) can place
limits on the growth engine (see [23]). These simulators
make it possible to identify and test leverage points in the
business model, support high quality managerial dialogue
about strategic initiatives, and introduces a structured,
experimental and evidence-based approach to strategy
development and implementation.
4. DISCUSSION – LEADING DIGITAL
TRANSFORMATIONS IS ABOUT BUILDING
SHARED THEORIES OF SUCCESS
Implementing business models based on systems thinking
principles and methods has two important advantages
over traditional implementation.
The first is that the business model explicitly represents
the organization's managerial understanding of how
things are done, in essence their theory of success as to
how value is created in a digital environment. Digital
technology-driven transformation can increase the firm’s
potential for organizational growth and development. At
the same time, it presents managers with significant
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organizational risks. Externally, it affects the
organization’s strategic position in its industry; internally,
it influences the nature of the relationships both between
individuals as well as between organizational units.
The second benefit is that the business model explicitly
incorporates the dynamic relationships among the
primary value-creating components. The causal loop
methodology captures the overall feedback relationships
and identifies the nature of the growth engine (see [8],
chapter 10 for a comprehensive discussion of various
growth engines). Growth is generated by reinforcing
feedback loops. Balancing, or negative, feedback loops
define constraints on the system that may limit the
growth potential. Taken together, a systems-based model
identifies both opportunities and limitations for growth,
as well as providing a means to study how to overcome
them.
Business transformation management in complex
dynamic organizational systems that are undergoing
digitalization is a difficult environment in which to
learning about decision-makers reactions to introduced
changes (like new digital service offerings). They usually
do not have the time to wait and see if their interventions
are going to work well, and then readjust accordingly.
Furthermore, disruptive information technologies impose
significant challenges both on the organizations’ internal
processes as well as on their relationships with their
customers and business partners. Consequently, the
decision to “go digital” requires managers to develop
perspectives that have the requisite variety to cope with
these challenges. The feedback systems approach is a
powerful means for managers to develop and
communicate business models that include those aspects
of digitalization that affects their firm’s theory of success.
The Uber case ([24], [16]) illustrates how a feedback
systems approach can be applied to understanding how
digital transformation affects both the business model and
the established business environment. Uber is a child of
the extreme forms of new organizations that digital
technologies can enable. Started in 2009, Uber has
become a contentious competitor in the traditional taxi
industry in cities around the world. Enabled by
smartphone technology, Uber’s radically different
business model has dramatically increased both consumer
efficiency and company revenues. The result is one of
largest point-to-point transportation networks in the
world. Technology plays the central role in providing
consumers with ‘me-here-now’ logistics services that
drives the efficiency gains.
One of Uber’s core challenges is that it must manage
satisfaction on both sides of a two-sided market (riders
and drivers). At the same time, as its business model
seeks to address future customer needs and relationships,
it is also outpacing many of the laws that regulate the taxi
industry [24]. Uber’s business model reveals that the
company relies on a set of feedback loops that reinforce
the power of the system from one side of the market to
the other, thereby creating a growth engine. The central
component of this growth engine is known as a ‘get-big-
fast’ (GBF) strategy [25]. However, regardless of how
compelling their service is, there are also a number of
limiting feedback loops in Uber’s GBF strategy.
Modeling Uber’s theory of success in applying a GBF
strategy enables decision-makers to identify and
investigate the potential side effects of digital
transformation. The model captures the interplay of
powerful reinforcing feedbacks that drive Uber’s rapid
growth and their interaction with constraints arising from
the behavioral changes of major stakeholders, potential
decline of the customer base resulting from limited
availability of capital, and delays in deploying the
capabilities and competencies needed to provide an
attractive Uber app. Thus, decision-makers understand
better the interdependencies of socio-technical changes
and how balancing feedback loops can limit growth
through, for example, service erosion.
Driving digital business transformation is a delicate
balancing act between the fundamental changes in
business due to advanced technologies and disruptive
business models on the one hand, and developing
infrastructures required to serve changing customer
demands, keeping customers attracted, as well as
managing the resulting frictions with the established
environment on the other.
5. SUMMARY AND CONCLUSION
Digital leadership is about building shared theories of
success. In moving beyond slogans about
interconnectedness and systems and overcoming
organizational dysfunction, however, we need to develop
specific approaches and tools to foster our systems
thinking and modelling capabilities. Building a shared
theory of success is effective when the decision-makers
are able to engage people in what Schön ([26] in [22])
called “reflective conversation with the situation.”
Management flight simulators aim to enhance learning
about the intended and unintended consequences of a
digital strategy. The purpose of developing and running
MFS is to gain a deeper understanding and insights into
why the business model behave the way it does, and how
changing the logic of the business affects its internal and
external environments and vice versa. Building a MFS
should help the participants make their theory of success
explicit, test their mental models and assumptions about
the behavior of the new business model, and discover
inconsistencies and blind spots in the digital strategy and
the resulting transformation roadmap.
This article has presented the challenges we face in
moving to the next level of digital transformation
management – meeting complex challenges requires
learning “new ways of thinking.” This demands an
increased capacity to build and apply a systemic
understanding of the nature of the systems we are trying
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to improve. Systems thinking provides a process, a set of
thinking skills and technologies that can improve our
ability to develop that systemic understanding.
Systems thinking and modeling is a powerful tool for
supporting the explication of mental models and
understanding the consequences of these models in the
real world. However, simply having a powerful and
flexible language is in itself not sufficient to assure that
the process will have a successful outcome. Framing the
digital business transformation challenge as a wicked
problem shifts our focus from being solution-oriented to
becoming learning and process-oriented. Wicked
problems have no ‘solutions’ in the sense of a result
being right or wrong. Instead, we are more concerned
with the process of working together with others to craft a
business model that enables working effectively towards
a vision of the future that incorporates an improvement
over the current situation.
Ultimately, an organization’s ability to succeed in an
increasingly complex environment will depend on its
ability to learn - about itself, the market, its competitors,
the utilization of new technologies, and its place in the
larger natural and social environment. Systems thinking
and modeling provide a powerful approach for
representing and operationalizing the mental models that
strategic decision-makers bring to the table.
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