Digital strategy aligning in SMEs: A dynamic capabilities perspective
Ana Isabel Canhoto*, Brunel University London, UK
Sarah Quinton, Oxford Brookes University, UK
Rebecca Pera, University of Eastern Piedmont, Italy
Sebastián Molinillo, University of Málaga, Spain
Lyndon Simkin, Coventry University, UK
* Corresponding author
Brunel University London
Uxbridge UB8 3PH
This research received funding from Oxford Brookes University, UK, internal small grants
award number 0012-15/48.
● Provides a digital strategy aligning model for SME organizations.
● Adopts a dynamic capabilities perspective to investigate digital aligning.
● Recognizes the importance of micro-behaviors in digital strategy aligning.
● Identifies reorganization by reconfiguration as critical for IS alignment in SMEs.
● Provides a holistic understanding of SMEs’ digital practices.
Digital strategy alignment is a dominant concern for today’s managers and information systems
researchers. Yet research in this area remains fragmented, particularly on the digital strategy
alignment of small and medium-sized enterprises (SMEs), which is concerning owing to their
value to European economies. Employing dynamic capabilities as an analytical lens, we
investigate how 43 British, Irish, Italian, and Spanish SMEs, across five industry sectors, enact
digital aligning. We identify a model of digital alignment comprising five phases, which we
term “passive acceptance,” “connection,” “immersion,” “fusion,” and “transformation,” as well
as the specific combinations of sensing, seizing, and reorganizing capabilities associated with
each phase. Our model provides a holistic, practice-based perspective and highlights the role
of micro-behaviors and leadership in SMEs implementing digital strategy.
Keywords: Digital strategy aligning, SMEs, Europe, Dynamic capabilities, Five-phase model.
Digital technology offers small and medium-sized firms (SMEs) significant business
and competitive opportunities (OECD, 2019). It can transform their business functions (Peltier
et al., 2012), assist in brand promotion (Kitchen, 2017), improve customer communication and
information management (Harrigan et al., 2011), level the competitive playing field (Borges et
al., 2009), and facilitate growth (Kurnia et al., 2015). Given the strategic importance of digital
technology for SMEs, extant literature has tried to identify factors that support or hinder the
successful digitalization of these organizations. Li et al. (2016) found that culture, trust, and
the attitude of the SME owner/manager are critical for the development of collective
knowledge in information systems (IS) adoption, whereas Cenamor et al. (2019) highlight the
supporting role of digital, network, and platform capabilities. Furthermore, the barriers
identified in the literature include poor planning (Gutierrez et al., 2009), lack of formal
processes (Kitsios and Kamariotou, 2015), lack of understanding of the value of digital
technologies and business performance (Cenamor et al., 2019), and dependence on external
sourcing of IT competency (Wang and Rusu, 2018).
Despite the literature identifying specific factors that may hinder or enhance the
digitalization of SMEs, research on how SMEs can leverage their potential through the
alignment of digital and business strategies is lacking (Gutierrez et al., 2009; Kamariotou et
al., 2018; Mohd Salleh et al., 2017). This is an important knowledge gap because the alignment
between IS strategy, including digital IS, and business strategy has a critical impact on firm
performance (Renaud et al., 2016), is a key managerial concern (Kappelman et al., 2014), and
remains a critical challenge for SME leaders (Li et al., 2016). It also constitutes a knowledge
gap for the IS strategy field in general, given that insights from studies conducted with large
firms may not be transferable to SMEs.
Strategic digital alignment is a dynamic process of adaptation and change (Henderson
and Venkatraman, 1993; Li et al., 2016) that, rather than being static, demands continuous
feedback between business requirements and digital technologies. Aligning digital strategy can
be viewed as progressive and intentional (Coursey and Norris, 2008), with behaviors that move
from being reactive to purposeful uses and integration of technology (El Sawy, 2003).
However, this ongoing set of dynamic changes is not necessarily linear (Iannaci et al., 2019),
and the integration of IS with business to leverage the technology’s potential remains a
To investigate this process and, in particular, the dynamic relationship between
business requirements and digital technologies, we draw on dynamic capabilities (DCs) as a
theoretical lens. The DCs lens, as epitomized by Teece (2007), focuses on strategic change in
the organization (Helfat and Peteraf, 2009) and aids in analyzing and explaining how firms
change their resources and behaviors as a result of external pressures (Arndt et al., 2018; Daniel
et al., 2014). This includes how firms become aware of the need for change and leverage
opportunities, thus leading to the enactment of change. Therefore, use of the DCs lens to probe
digital aligning in SMEs is pertinent and valuable.
Given the limited research on digital strategy alignment in SMEs, the aim of this paper
is to extend theory to identify the combination of DCs associated with different patterns of
technology adoption and use. In response to the lacuna of practice-based knowledge
(Karpovsky and Galliers, 2015) and Mohd Salleh et al.’s (2017) call, we investigate digital
strategy aligning in SMEs to identify the practices that allow them to leverage digital
technologies. Specifically, we examine the following research question: How do SMEs enact
digital strategy alignment?
We pursue this aim through the analysis of 43 case studies of SMEs in four European
countries and across five industry sectors. This analysis allows us to develop an overarching
perspective of phases of digital strategy aligning and to delineate the characteristics and
behaviors of organizations at each phase. Furthermore, we identify the conceptual relationships
between constructs, which can form the basis for future hypotheses development, testing, and
The relevance of this study goes beyond the conceptualization of digital aligning in
SMEs in two ways. First, we provide insight that enables targeted managerial action and policy
development in this economically significant organization type (OECD, 2019). Second, as
SMEs are often key partners of large firms (Woldesenbet et al., 2012), examining digital
strategy aligning in SMEs can also help IS scholars understand the balance and interactions
between small and large organizations.
Digital strategy aligning
While scholars disagree on whether IS strategy should adapt to business strategy, co-
evolve with it (Peppard and Ward, 2004), or even challenge it (Chan and Reich, 2007), they
largely agree that IS strategy alignment is desirable and has a positive impact on business
performance (Renaud et al., 2016). However, aligning fixed IT assets with ever-changing
business imperatives is a challenging endeavor (Galliers, 2004), meaning that alignment should
be considered an ongoing process requiring continuous adjustments (Hirschheim and
Sabherwal, 2001; Li et al., 2016) rather than an either-or state (Luftman, 2000).
Reflecting this fluidity, various scholars have conceptualized IS alignment as a matter
of degree and the type of use of technology. For example, Luftman (2000) proposes a model
of alignment maturity consisting of five levels, ranging from initial to optimized. Davison et
al. (2005) also consider five stages of aligning, though their model starts from rhetorical
intention and progresses to transformation. In turn, El Sawy (2003) refers to three views of IS
evolution (connection, immersion, and fusion), progressing from reactive to purposeful uses of
technology, until there is no division between the business strategy and the technologies used
to drive it. Yeow et al. (2018) also propose a digital strategy alignment model consisting of
three phases: exploratory, building, and extension. The first two phases mirror El Sawy’s
(2003) view, while the third, extension phase, goes beyond his conceptualization. While these
models vary in the nomenclature used (i.e., levels, stages, views, and phases) and the number
of gradations considered, they all treat alignment as something the organization “does” rather
than something the organization “has” (Karpovsky and Galliers, 2015). Furthermore, these
models characterize aligning as a progressive, albeit non-linear (Iannaci et al., 2019), process,
with higher levels reflecting increasingly intentional and integrated uses of technology
(Coursey and Norris, 2008).
In recent years, research has moved away from normative models of alignment to
drawing on real-world experiences (Karpovsky and Galliers, 2015) and from a focus on the
alignment itself to the practice of aligning (Wilson et al., 2013). The emphasis is on the actions
and activities performed across the organization to achieve a fit between IS and business
strategy (Orlikowski, 2010) and recognizing that aligning does not occur in a stepwise manner,
in which organizations progress sequentially through stages of increased IT sophistication
(Iannaci et al., 2019). For example, Li et al. (2016) define strategic alignment as the dynamic
adjustment between business requirements and information technologies (including digital).
Furthermore, they specify that alignment is ongoing and evolving and that it alters according
to the needs of the business. This view of aligning echoes that of Henderson and Venkatraman
(1993), who posit that strategic alignment is a process of continuous adaptation and change.
A growing body of work has examined how different social factors (e.g., organizational
actions) result in specific emergent experiences of aligning that integrate IS and business
strategy (Karpovsky and Galliers, 2015). Extant literature highlights the critical role of
individuals or small groups, rather than whole departments in large firms, such as IT, in leading
digital alignment processes. That is, the transformation of organization processes to leverage
digital opportunities is influenced by the attitudes toward the technology of those leading the
alignment (Li et al., 2016; Morgan-Thomas, 2016; Orlikowski and Scott, 2015), their
willingness to take risks (Grant et al., 2014; Jones et al., 2014), and their personal curiosity and
open-mindedness (Day, 2011). Furthermore, organizational actors shape, reshape, and
appropriate technology through their goal-oriented actions (Whittington, 2014). Yeow et al.
(2018) investigate the behaviors that support progression through the three phases of their
model. However, their study focuses on only one firm and thus cannot account for the variety
of approaches to alignment reported in the literature (see Karpovsky and Galliers, 2015). In
particular, their analysis does not reflect how the conditions faced by different organizations
may affect their strategic alignment (Street et al., 2017), which limits the application of this
model to SMEs.
Digital strategy aligning in SMEs
Given the strategic importance of digital technology for SMEs, understanding how the
alignment of IS and business occurs in this type of firm is valuable (Spinelli et al., 2013; Street
et al., 2017). Research on IS strategy alignment in SMEs is limited and usually draws on models
developed for large firms (Mohd Salleh, 2017; Wang and Rusu, 2018). While well-established
models such as Luftman’s (2000) strategic alignment maturity model may be of value to
investigate this phenomenon in SMEs, with some adaptations (Gutierrez et al., 2009), the
findings from empirical studies conducted with large firms may not be transferable to SMEs,
as the latter exhibit unique features (Kitsios and Kamariotou, 2019) that may affect the IS
aligning process. For example, predetermined factors such as environmental, technological,
and organizational aspects of the business ecosystem have been commonly used in research on
large firms but misguidedly applied to smaller firms (Kendall et al., 2001). Furthermore,
Gutierrez et al. (2009) found that while organizations of different sizes perceive alignment in
similar ways, they adopt distinctive integration strategies and rate the importance of some
factors (e.g., governance, system architecture) differently. Such observations imply that while
SMEs’ digitalization may be partly reliant on the deployment of capabilities also found in large
firms, these firms may also follow specific approaches because of their unique characteristics,
beyond size and resource constraints (Kitsios and Kamariotou, 2019).
On the one hand, SME characteristics such as the inclination to improvise or speed of
decision making (Baker and Sinkula, 2009; Libaers et al., 2016) may assist in strategic digital
alignment. Given their greater flexibility, SMEs may have an advantage over large firms in
terms of discovery and idea generation (Libaers et al., 2016). Moreover, SMEs’ agility and
opportunistic behavior may breed success in fluid and rapidly changing environments (Baker
and Sinkula, 2009). SMEs also tend to be more effective than their larger counterparts in their
use of open innovation (Spithoven et al., 2013). These characteristics highlight an ability to
implement digital alignment. On the other hand, SMEs’ financial limitations may hinder the
absorption of learning into the firm (Sirén and Kohtamäki, 2016). For example, financial
constraints may inhibit the acquisition of information, the adoption of new processes, and the
renewal of operating resources (Nieves, 2016). The instability of IT systems and the
dependence on external IT sourcing competences can also impede digital alignment in smaller
firms (Wang and Rusu, 2018). These characteristics have a negatively impact on digital
alignment in SMEs.
While the lack of planning and formal processes can negatively affect IS development
in firms (Gutierrez et al., 2009), its relationship to alignment in SMEs remains unclear
(Kamariotou et al., 2018; Kitsios and Kamariotou, 2019). One challenge is the limited research
examining how digital leadership in SMEs drives the successful alignment among business
needs, IS, and innovation (Li et al., 2016). Cenamor et al. (2019) also allude to the cognitive
inertia of SMEs and their lack of understanding of the linkages among digital technologies,
information and communication technology, and business performance, as well as of the
importance of managing information flows. They outline the lack of insight into SMEs’
implementation of digital technologies and agree with Mohd Salleh et al.’s (2017) call for
further research on SME dynamic digital aligning and performance.
DCs as a theoretical lens to examine digital strategy alignment in SMEs
Teece et al. (1997, p. 516) define DCs as “the firm’s ability to integrate, build, and
reconfigure internal and external competences to address rapidly changing environments.”
These capabilities emphasize “the development of management capabilities and difﬁcult-to-
imitate combinations of organizational, functional and technological skills” (Teece et al., 1997,
p. 510). Indeed, they constitute a planned strategic approach, beyond ad hoc solving of business
problems or the repeated execution of good practice.
DCs are a pertinent and valuable lens through which to probe digital aligning because
they account for technology in combination with organizational and functional abilities of a
firm (Teece et al., 1997) and thus allow the analysis of changes in behavior and resource
allocation (Arndt et al., 2018). In particular, DCs can facilitate an understanding of the actions
undertaken across the organization to effect change (Yeow et al., 2018), which is relevant
because digital strategy alignment is multi-functional and each function cannot be considered
in isolation (Bharadwaj et al., 2013). This aggregative approach is particularly appropriate to
evaluate digital aligning in SMEs, as in these organizations, functional areas may merge
together, and roles and people must often be flexible rather than fixed (Gao and Hafsi, 2015;
Peltier et al., 2012). In addition, DCs are an established lens in the investigation of SMEs (e.g.,
Adeniran and Johnston, 2016; Lane et al., 2006; Lindblom et al., 2008). For example, Adeniran
and Johnston (2016) found that DCs had a positive impact on IT utilization, in terms of helping
SMEs generate long-term returns on technology applications, functions, and tools.
The DCs lens also facilitates the identification of behaviors that effect change in IS
strategy aligning (Yeow et al., 2018). Core components of DCs include “sensing,” “seizing,”
and “reorganizing.” Sensing is the ability to detect changes (Teece, 2007) and to learn quickly
(Winter, 2003). Roberts et al. (2016) emphasize that sensing is related not to the volume of
ideas available to the organization but rather to the organization’s innovativeness. For example,
many companies have excelled in the digital environment by proactively identifying customer
needs (Sebastian et al., 2017). Environmental factors, including the organizational context, are
key elements in IS strategizing, as changes can present both opportunities and threats
(Marabelli and Galliers, 2017).
Seizing involves addressing the opportunities in the marketplace by mobilizing
resources, embracing prospects for innovation, and executing actions to optimize those
opportunities and capture value (Teece, 2016). It includes investing in backbone operational
components, identifying data requirements, and building support systems, as well as
developing solutions to deliver value to key stakeholders (Sebastian et al., 2017). Seizing is
pivotal within DCs as it involves demonstrable action and moves organizations forward
through the commitment to change (Yeow et al., 2018). SMEs may have an advantage in
seizing, as their shorter decision-making chains and communication flows allow them to
respond quickly (Libaers et al., 2016).
Finally, reorganizing involves altering company processes and routines, leveraging
resources in new ways (Yeow et al., 2018), accessing new resources to fill the previously
identified gaps (Eisenhardt and Martin, 2000), and releasing resources to create optimal
combinations (Girod and Whittington, 2017). It is the most challenging DC, as it requires a
change in culture and may necessitate discarding long-standing products and practices
(Sebastian et al., 2017). Purposeful reorganizing can occur through restructuring or
reconfiguration. On the one hand, restructuring includes fundamental changes across the whole
firm, including its structures (Girod and Whittington, 2017), but can be irregular, owing to its
significance and the resources required, as well as the level of disruption involved. On the other
hand, reconfiguration refers to localized, incremental changes, which are small in scale and do
not affect the firm’s fundamental structure. Reconfiguration might be a suitable approach for
the digital alignment of SMEs, due to their limited financial and human resources. Moreover,
given that SMEs tend to have flat organizational structures, it should be easier for them to
routinize localized changes and extend them to the whole organization, thus avoiding the
limitations of reconfiguration faced by large organizations. Table 1 summarizes the key
concepts we use in this paper.
Key concepts and definitions.
Dynamic process of adaptation and change between the firm’s digital
technology strategy and its business strategy. It is an ongoing process
that requires continuous adjustments between business requirements
and digital assets and can result in different configurations of degree
and type of use of technology.
Non-subsidiary, independent firms that employ fewer than a given
number of employees and generate turnover below a certain level. The
specific number of employees and turnover level vary across countries.
This study adopts the parameters used by the European Commission:
o Micro firms: fewer than 10 employees and/or turnover below
o Small firms: fewer than 50 employees and/or turnover below
o Medium firms: fewer than 250 employees and/or turnover
“The firm’s ability to integrate, build, and reconfigure internal and
external competences to address rapidly changing environments”
(Teece et al., 1997, p. 516).
Ability to detect changes and to learn quickly.
Ability to address the opportunities in the marketplace by mobilizing
resources, embracing prospects for innovation, and executing actions to
optimize those opportunities and capture value.
Ability to alter company processes and routines, leverage resources in
new ways, access new resources to fill the previously identified gaps,
and release resources to create optimal combinations. Reorganizing can
occur through restructuring or reconfiguration. The former refers to
fundamental changes across the whole firm, including its structures,
and the latter to localized, incremental changes that do not affect the
firm’s fundamental structure.
In summary, digital strategy alignment is a process of adaptation and change in the
interrelationship between digital assets and business strategy. Organizations, including SMEs,
need to understand how to adapt and integrate technology with business functions, so that they
can leverage their competitiveness. Extant research has stressed the importance of digital
strategy aligning for business success, but how SMEs accomplish this is under-researched.
Although known characteristics of SMEs suggest the ability to enact digital strategy aligning,
the constraints these firms face create structural challenges to aligning. Furthermore, the impact
of certain behaviors on SMEs’ approaches to digital strategy aligning remains unclear. Much
of the evidence on digital strategy aligning comes from large-scale studies, with limited
empirical research on SMEs’ aligning processes. DCs offer an aggregative approach to
investigate the set of SMEs’ aligning activities, from specific core capabilities to adaptation
and change. Through the use of this lens, we can identify the sensing, seizing, and reorganizing
activities of SMEs and provide insight into their relationship to digital technology aligning.
Specifically, we focus on the micro-behaviors of SMEs, considering the subjective experiences
of the key actors in these firms and how, through the deployment of DCs, they draw on digital
assets to adapt to the dynamic, turbulent, and rapidly changing environments (Quinn et al.,
2016) in which they operate.
We treat aligning as a dynamic process that can assume different configurations of IT
assets and business imperatives. These configurations differ in the level of sophistication of
digital technology use and the level of intentional and integrated use of technology. Similar to
Yeow et al. (2018), who investigate digital alignment using a DCs lens, we refer to each type
of configuration as a “phase.” Here, we do not suggest that one configuration is inherently
superior to another or that organizations should strive to move between configurations in one
particular direction to follow a specific path; rather, we aim to understand the social, material,
and embodied ways of aligning (Jarzabkowski and Spee, 2009) that characterize the different
degrees of the intentional and integrated use of technology.
As phenomenon-driven research, our goal was to create a holistic, practice-based
understanding of digital strategy aligning in SMEs. We adopted an interpretive approach, based
on an a priori framework (Patton, 1990). This framework provided “seed categories” (Miles
and Huberman, 1994) to structure our questions and initial deductive analysis but were
complemented with additional categories emerging inductively from the coding of the data.
As our study involved an area in which theory is nascent and, as such, we did not know
what issues might emerge from the data, we deemed an exploratory case study appropriate
(Edmondson and McManus, 2007; Eisenhardt and Martin, 2000) to develop emergent insight
(Flick, 2013) within the context (LeCompte and Schensul, 1999). Specifically, we investigated
the digital strategy alignment processes of North European (Britain and Ireland) and South
European (Italy and Spain) SMEs. The international data provided robustness for the
consistency of the findings across different contexts (Merriam and Tisdell, 2015).
The semi-structured interviews allowed the informants to share their experiences
(Denzin and Lincoln, 2008; Edmondson and McManus, 2007) and enabled us to capture their
knowledge and experiences to refine our emergent model (Benbasat et al., 1987; Eisenhardt,
1989). As we wanted to understand the “how” and “why” of SME digital strategy aligning, we
interviewed SME managers who had oversight of digital strategy in their organizations. In
many of the SMEs, only one interviewee met this criterion. Thus, to be consistent across the
various organizations studied, in terms of the profile of interviewees, we conducted only one
interview in each organization, with the understanding that the interviewees are influenced by
their environment and that the information they provide is colored by this framing (Philips and
Although the value of interviews is well-established in social science studies (Kvale
and Brinkmann, 2009), we also incorporated key information about the organization’s digital
presence by conducting desk research (Beverland and Lindgreen, 2010). For example, we
collected available data on external-facing digital technologies, such as the functionality of
websites and the type and extent of social media presence. Furthermore, when external drivers
were mentioned, such as the presence of legislation or government financial incentives, we
investigated the content of those drivers (e.g., what the law required, how much funding was
available). We found no significant discrepancies between the interview accounts and our
independent observations. Our triangulation approach emulates Pattinson et al.’s (2018)
investigation of sensemaking in SMEs. Complementarity is a valuable goal of triangulation in
studies that follow a constructive stance, such as ours, because it offers additional perspectives
on the phenomenon being studied (Farquhar et al., 2020).
The sample (Table 2) comprised 43 SME firms in five industries identified by the
European Commission as core and investigated in previous studies (see Eggers et al., 2013);
agriculture, manufacturing, retail, professional services, and tourism. We adopted the European
Commission’s definition of SMEs in this study (see Table 1). Appendix 1 lists the
characteristics of the sample as supplementary information on the case organizations. When
empirical saturation was achieved (Tracy, 2010), data collection ceased. The number of sample
cases recommended for case study research is contentious (see Dyer and Wilkins, 1991; Lillis
and Mundy, 2005). Challenges are acknowledged in reporting results from a large number of
cases and the trade-off in terms of data depth, but Piekkari et al. (2009) argue for greater
methodological pluralism and a greater appreciation for context and purpose. Thus, although
our number of cases was high (43), this number is appropriate in relation to the context and
purpose of our study, as it enables us to capture diverse experiences from practitioners in
multiple industry sectors and provides the base for building a holistic view of SME digital
Data collection and analysis
A native researcher of each country conducted the interviews, to capture nuances in
language. Eleven questions (Appendix 2) took account of multiple influences, as called for by
Morgan-Thomas (2016) and Amit and Han (2017). Following Yeow et al. (2018), who
investigate the role of DCs in strategy alignment, we sought to identify the sensing, seizing,
and reorganizing behaviors supporting digital alignment. In addition, we asked about the
external environmental drivers of digital alignment (Marabelli and Galliers, 2017) and the
influence of key individuals (Day, 2011; Gao and Hafsi, 2015; Orlikowski and Scott, 2015;
Vaccaro et al., 2012) within the three components of DCs.
Subsequent to transcription and translation of the interviews, we analyzed the data
independently and, then, collectively using Yin’s (2013) three-step analytic framework. The
first step involved coding and categorization of each transcript. Drawing on the descriptions El
Sawy (2003) and Yeow et al. (2018) used for their respective frameworks (some of which
overlapped, as discussed previously), we coded each organization in one specific phase of IT
strategy alignment: the first, as per El Sawy’s Connection and Yeow et al.’s Exploratory
phases; the second, as per El Sawy’s Immersion phase; the third, as per El Sawy’s Fusion and
Yeow et al.’s Building phases; and the fourth, as per Yeow et al.’s Extension phase. Following
this stage of deductive categorization, we identified the organizations that exhibited a
configuration of IT alignment that matched neither El Sawy’s nor Yeow et al.’s typology.
Specifically, we identified a small number of organizations that adopted a narrow range of IT
tools, driven by pressures from the external environment rather than internal logic. We added
this phase, which we developed inductively from analysis of the data, to our typology, leading
to the five phases of digital strategy aligning shown in Table 3. We termed this new precursor
phase “passive acceptance” to denote the lack of progressive engagement with digital
technologies and the reluctant acknowledgment of the need to participate in digital strategic
aligning at a basic level. Pursuant to this, at the other end of aligning was the finding that, in a
few instances, SMEs were not only aligning their digital strategy but also reframing and
transitioning to a transformative state that incorporated but also moved beyond the extension
phase proposed by Yeow et al. (2018). We termed this phase “transformation.”
The second step focused on categorical aggregation and the search for patterns.
Mirroring Yeow et al.’s (2018) approach, we mapped the DC behaviors that characterized each
of the five phases—namely, how the firms in each phase learned (sensing), mobilized their
resources (seizing), and adapted their processes and routines (reorganizing) to align digital
In the third step, we revisited the data to search for relationships among the core themes
of “phase of strategic digital alignment” (i.e., passive; connection/exploratory, immersion,
fusion/building, and transformation), “context” (i.e., size of SME, region, and industry), and
“DCs” (i.e., sensing, seizing and reorganizing). Any outliers within each element were
swapped across the research team and followed the convergent interview approach (Rao and
Perry, 2003). To enhance qualitative legitimacy, we applied Guba and Lincoln’s (1994) criteria
of trustworthiness and authenticity.
Examples of coding and thematic analysis.
(“•” denotes behavior
illustrated by the
“Legislation and our clients lead us to
adopt digital practices…. Being a food
company we are obliged to provide
• Reactive behavior to
• Compliance to
o No strategic planning
“The way I invoice clients, the way we
communicate, through email or through
video or through any of those things; it’s
all got a trail online and everything is
connected with it. And that makes my
business incredibly easy because as a
consultancy the majority of my work is
the actual work that I’m doing, so how
technology helps me is that it just
streamlines all of that…. I can see where
projects are and keep on top of them….
My competitors are using similar tools
and this will only increase as digital
becomes normal in business.”
• Process efficiency
• External threat
o Shared understanding
of the digital potential
“We move with an overall strategy, and
digital helps to achieve it…. The use of
various tools aimed at reducing
difficulties and helping us use
information better, for example, the way
we manage documentation and work
flow … my team now relies on these
digital systems and couldn’t work
• Digital supports
• People, processes, and
o Digital used to
understand the market
o Digital planning is key
“The way that the digital arena will
change for us over the next 10 years is
going to blow our socks off. Digital
integration is giving us the capability to
consolidate inventories, to train people
across countries using YouTube videos
… it is helping us to achieve our overall
strategy of internationalization.”
o No distinction
between digital and
• Multi-digital channels
to support business
o Mindset of leader
• Integration of digital
“I’m developing my personal app … for
my own personal market of 100 people
or households, and I will be a grower for
them and they will be able to track,
develop and see how their fruit,
vegetables and meat are growing. Make
orders on the app at specific times of the
year through the app, and when it’s
ready for them they can come and
• Digital disrupts
o New culture across all
Data analysis led to the identification of five phases of digital aligning among our
sample (Table 4), from reluctant engagement with digital technology to the embrace of its
transformative power. We describe the phases and behaviors that support them next.
Phase 1: Passive acceptance
This phase is characterized by the limited, almost reluctant, use of digital technology,
driven solely by external pressures (see Table 4). The four firms in this phase displayed limited
use of a small number of digital tools, such as creating a basic website for their firms, using e-
mail and Internet search, or making the occasional international phone call via Internet
telephony services such as Skype. All firms were from different sectors (agriculture,
manufacturing, retail, and tourism) and of different sizes (two small and two medium). Two
were based in South Europe and two North Europe.
When probed for the rationale for adopting such tools, the firms described having to do
so, as a result of external pressure and the rules and conditions with which the business had to
comply. For example, government initiatives encouraged digital filing of taxes in Britain, EU
farming regulations required the digital recording of animals in Ireland, and health and safety
regulations and customer expectations dictated food handling activity in Spain:
Legislation and our clients lead us to adopt digital practices…. Being a food company
we are obliged to provide product traceability. (Small-Spain-Agriculture).
Government initiatives that made us file paperwork online was a factor that made us
start thinking about digital technologies. (Micro-Britain-Manufacturer)
Key characteristics and behaviors of each phase.
In terms of seizing, limited resources and the speed of technology change generated
concern: “The learning curve is too long and requires too much time which affects the return”
Technol ogy use
Pa ssive Acceptance
Limited use – e.g.,
email, search engines,
internet telephony for
Government grants if
efficiency, time and cost
No long-term view,
explicit budget or
metrics. Staff fear
change and aim to
maintain status quo.
Ad-hoc use of selected
tools to support service
delivery – e.g., ERP,
SAP, EDI and Cloud, e-
AdWords), some social
media presence, but
mostly for ‘push’
to keep-up with
Some investment in tools
which support specific
processes, and enhance
efficiency and control;
Lack of in-house expertise
leads to use of external
specialists. Staff training.
technology and human
strategy. E.g., Google
working (cloud services
for data storage, etc),
interactive channels for
two-way interaction via
social media), loyalty
Focused on the
adds value to
customer and staff
Integration with third-party
systems, testing digital
communications to assist
throughout the company
about benefits start of
of technology and
business functions, to
meet specific business
use of measurement
tools, embedded e-
strategic use of social
Focus on how real
time data offers
Integration across firm and
alignment of systems,
integration of internal and
external data, new resource
Opportunities for change
in direction for the
business. Seamless use
of multi-media linked to
digital mind-set of
Technology , p rocesses
and strategy managed
virtual reality, 3D
images and other
desire to lead and be
viewed as example
of best practice.
Quick adoption of new
requesting feedback from
customers (e.g., beta
Openness from top of
firm to innovate, fluid
use of staff expertise
Positive disruption to
(Small-Spain-Agriculture). The constrained resources led these firms to seek out external
sources of funding, such as government grants. Then, they proceeded to scrutinizing their
competitors’ actions, such as what product information was displayed on websites. They might
also explore ways of using technology to cut costs and improve efficiency, though, overall,
they perceived investments in technology as risky.
The use of digital technology did not progress beyond the localized use of tools. There
was no formalized planning, no systematic use of metrics or other tracking efforts, and no
specific budget for digital activities: “They come to me for project money every now and again”
(Medium-Britain-Retail). Furthermore, the managers reported general discomfort in using
technology, adding that staff resisted further innovation:
Staff are afraid of not knowing how to use and control [the technologies]. This makes
them feel useless and they are fearful both of losing their jobs and of being watched.
In this first phase, there was no articulation of aligning digital strategy, skills, planning,
or decision making for the benefit of the organization. No explicit relationship was articulated
between IT strategy and business needs or objectives. While sensing had occurred as a result
of external factors, the seizing of any opportunities was highly limited, and no reorganizing
had been implemented. Indeed, the limited use of digital technologies could even be perceived
as a distraction, undermining other processes in the organization: “Our competitors and
suppliers have influenced us to move to digital practices, but doing this stops us completing
other activities in the business” (Small–Spain-Agriculture).
Phase 2: Connection
This phase is characterized by the ad hoc, but voluntary, use of some tools for both
internal and external activities, illustrating a progression from the previous phase in which the
use of digital tools was minimal (Table 4). The 13 firms in this phase used digital technology
on an ad hoc basis, including tools to engage with customers, such as having a limited social
media presence or experimenting with search engine marketing. They also had back-office
systems (e.g., Yammer) to facilitate internal communication.
These organizations justified adoption of digital technology as a means to deal with
perceived threats in the environment and also as a result of changes in consumer behavior.
They also reported monitoring their competitors’ actions and feeling pressured to keep up with
their competitors, particularly direct ones:
Competition and the environment push us to be digitized, competition is important and
we follow its movement to be at the same level and use the same tools. (Micro-Spain-
The firms had made some investments in digital tools to support productivity and/or
improve process efficiency. For example, cloud services allowed staff to access key documents
remotely, at any time and from anywhere, while enterprise resource planning (ERP) systems
helped reduce mistakes:
Use of software and digital tools have been wonderful in terms of control improvement
and error reduction. (Small-Spain-Manufacturer).
These firms are experimenting with new channels to communicate with customers, such
as social media, online advertising, and even e-commerce. However, they deem these as
complementary to traditional media and use them only when they are likely to improve
The way I invoice clients, the way that we communicate, through email or through
video or through any of those things; it’s all got a trail online and everything is
connected with it. And that makes my business incredibly easy because as a
consultancy…. So how technology helps me is that it just streamlines all of that … to
allow me to have the time and freedom to just get on. (Micro-Ireland-Services)
While staff were using various tools, overall, they were resistant to broader changes.
There was no formal plan or budget in place for further investment in digital technology. In
addition, while there was some measurement of results, this did not happen systematically:
“We are implementing some specific digital tools but are not sure how much benefit they
Within the connection phase of digital strategy, we noticed certain developments from
the passive acceptance phase. The sensing capability now requires a need to engage in digital
IT tools to gain process efficiencies from limited investment. The progression of seizing is
evident in the linking of content across social media platforms or the connecting of e-commerce
with internal systems, to achieve a determined purpose, such as better, up-to-date supply
information. For example, one Italian firm had created an online space for customers to ask
questions, and it linked this information to the product database and the communication team’s
group information. In this case, the firm was prepared to invest in expertise, as it did not have
the internal skills required to align various technologies but appreciated the potential value.
However, the relationship between business objectives and strategic implementation of IT
technologies remains unrecognized in this phase. Finally, reorganizing is minimal and limited
to the short-term.
Phase 3: Immersion
This phase is characterized by a somewhat sophisticated use of digital technology and
a growing interdependence between business and technology (Table 4). The immersion phase
is a “watershed” point, as the relationship between business and technology is acknowledged
and some steps toward integration are taken. More sophisticated sensing emphasizes that
positive potential is apparent, firms are seizing opportunities to integrate systems, and a certain
systematic evaluation of the integration now occurs as part of reorganizing, including cultural
Nineteen firms displayed competent use of digital technology, such as the creation of
online communities or the mining of data from Google analytics and customer relationship
management systems, in contrast with the previous (connection) phase, in which firms
deployed tools without integration. Moreover, we found evidence of interdependence between
IT and people, as in the case of smart working solutions. Digital technology is deemed
supportive of the business’s overall strategy: “We move with an overall strategy and digital
helps to achieve it” (Micro-Italy-Services).
The firms adopted digital technologies when they believed they would offer
opportunities. Moreover, rather than focusing on how automation could reduce time, money,
or errors, as in the previous connection phase, the firms noticed how technology could add
value—be it in the form of enhancing the customer experience, enabling flexible working, or
freeing up employees to explore new projects and activities:
People in the business can work remotely and at different hours, across the same
virtual cabinets…. Technology allows us to think in a broader [way]. (Micro-Britain-
To tap into the perceived opportunities, firms invested in third-party solutions to
improve service delivery: “[The third-party solution] advises [our clients] of liabilities and
deadlines, sends appreciative texts for paying on time” (Micro-Britain-Services). They also
tested the deployment of solutions across functions:
I’d like us to embrace anything that's available in terms of intelligent systems, which
are capable of substituting for human time and attention. In this way, we can focus on
the three, in my view irreplaceable, human practices which are social influence, social
intelligence and social creativity. (Small-Italy-Services)
We found evidence of some systematic monitoring of digital use, as well as the use of
metrics to inform further investment. Occasionally, firms used these to rethink previous
business strategy: “Digital has been the driver to disintermediation and to a new unique brand
building. We were suppliers, now we are competitors” (Small-Italy-Manufacturer).
In this phase, firms believe in the benefits of digital technology and the possibilities it
may provide for business. Digital strategy aligning was enacted by drawing staff and the
integration of processes closer. For example, the development of digital skills by specific
employees was supported by some of the SMEs in Britain and Italy, so that current market data
could be better exploited to inform forward planning. Designated staff were made responsible
for certain digital activities in the firms, such as cloud systems, to assist in implementing
alignment. Firms engaged in internal communication initiatives to support the adoption and
use of digital tools. As a result, staff regarded digital technology as a positive force for the
Phase 4: Fusion
This phase is characterized by the extensive use of digital tools, deployed to meet
business objectives. Here, digital strategy aligning is visible. Unlike in the previous phase, in
which firms used technology to support business strategy, there is now a sense of interaction
between business and IT strategy (Table 4). The four firms in this phase fuse digital technology
with the business:
Our business strategy does not differ from our digital one. The second does not depend
on the first one. They are completely blended, it’s not separated. (Medium-Italy-
Firms deliberately seek ways to use technology to improve their position and increase
flexibility. For example, they explore ways to obtain real-time data, accelerate the process of
analyzing existing datasets, and make any insights available for decision making:
When you work with … real-time data, all our business practices have changed, which
is positive. (Medium-Italy-Services)
In this phase, management perceives technology as a means to go beyond the firm’s
defined and well-established environment. Although this vision may not yet be implemented,
it is a progression from the immersion phase. A deep sense of curiosity and a focus beyond the
The bit I love is thinking about what you can use technology for going forwards; that
is huge, absolutely massive. (Medium-Britain-Manufacturer)
Resources (financial and human) are deployed to support this investment, for example,
by reassigning budgets or recruiting staff with specific technical skills. Moreover, firms seek
to integrate internal and external data (e.g., social media insight is integrated with internal
customer data), to maximize the benefits from operating in a digital environment. They look
beyond the current use of technology to also consider how it might shape the future business
environment, such as what new geographic markets can be made viable because of digital
We are changing how we operate at a core level…. It is costing a lot of money but I
believe it will transform us, our structures, the interactions we have … and all our
experimentation will make us the leader. (Small-Britain-Manufacturer)
The fusion phase of digital strategy alignment relies, in part, on the mindset and
characteristics of the organization’s leader, which is more apparent than in the previous phases
and encourages a sense of curiosity about digital technology. Multiple digital channels and
technologies are embedded within the organization, which supports innovation through the trial
and measurement of new technologies and then, accordingly, the adjustment of business
activities. For example, one firm achieves a broader business strategy of internationalization,
having been created by the leader, by combining the use of digital communication technologies
to reach international business audiences, the improved manufacturing accomplished through
digitally controlled laser cutting of materials, and social media to train local installers. Thus,
in the fusion phase, sensing is often led by enthusiasm from the top, which encourages the
seizing and implementation of new resource configurations, which then facilitates the potential
for reorganizing in the firm.
Phase 5: Transformation
This phase is characterized by the intentional use of digital technology to transform the
business (Table 4). While firms in the fusion phase were open to the possibility of reorganizing,
those in the transformation phase pursue the realization of such reorganizing. This marks a
substantial progression from the previous phases of aligning.
We classified three firms in this most advanced phase. Two were middle-sized
enterprises based in South Europe, and the other was micro-sized and based in North Europe.
The firms had partially, rather than fully, achieved this phase but were aspirational in
progressing toward full transformation.
The firms have a culture that promotes discovery, vigilance, and implementation of
opportunities. Technology has become second nature, with no difference between non-digital
and digital activities. These firms proactively adapt to market shifts through the use of digital
technologies. For example, they engage customers in the development and beta-testing of new
products and seek feedback from them. The openness to change is evident not just in the
manager championing the digital agenda but across functions and roles as well, and there is a
noticeable development from the fusion and immersion phases:
A lot is changing [more competition, less resources, surveillance, privacy and data
complexity are the most important]; we need to be prepared and to listen to these
changes. We need to cope with these changes. (Medium-Italy-Services)
In this phase, firms have managed to overcome organizational silos, particularly in
relation to social media practices. Respondents discussed the development of a new culture of
digitalization, in which the mindset, tools, and capabilities added to the firm’s creativity and
All social media from Instagram to Twitter are connected and everybody, even those
who work in production, use our Facebook account…. The Internet rewards content
more than the amount of money you invest…. Creativity rewards the digital. Our portal
is more innovative than…, we are dimensionally superior compared to the size of our
Digital strategy aligning, when achieved, may disrupt established business models,
anticipating fast-changing market signals and offering creative opportunities for small firms.
For example, developing a customized mobile app allowed disintermediation by engaging
directly with end consumers, who became highly involved in the new form of interaction:
I’m developing my personal app … for my own personal market of 100 people or
households, and I will be a grower for them and they will be able to track, develop and
see how their fruit, vegetables and meat are growing. Make orders on the app at specific
times of the year through the app, and when it’s ready for them they can come and
In the transformation phase, the concept of “how” to align technology and business
subtly changes to extend beyond how to bring strands together to how the firm might use a
different lens to anticipate the future of the business. An example of how alignment can lead
to positive disruption comes from an Italian organization:
The success of our YouTube video and social media activity on the handmaking of
shoes made us rethink our whole business, and now we are going to open a training
school for handmade shoes. This will be totally new for us as a manufacturer.
The sensing, seizing, and reorganizing capabilities are all cohesive and interwoven, such that
digital strategic aligning has moved an organization beyond aligning to new territories,
progressing the business into experimentation.
State of digital strategy aligning among the SMEs in our sample
The findings from SMEs in two European regions reveal a concentration of firms in the
connection and immersion phases of aligning, with digital technologies being used mostly on
an ad hoc basis or as support to the business strategy. The bulk of firms in the early phases of
DCs indicates that while the SMEs in our sample are engaging with digital technology,
benefiting from the transformative potential of digital technologies remains aspirational for
most (Peltier et al., 2012). As in Sebastian et al.’s (2017) study of large firms’ digitalization,
in our SME sample, firms found articulating the need for a digital strategy easier than actually
The lack of homogeneity of firm characteristics within each phase, and particularly in
the least and most advanced ones (see Appendix 1), suggests that the difference in engagement
with digital technologies among SMEs and also between SMEs and their larger counterparts
cannot be explained by size and sectorial factors alone. Instead, technology adoption and
strategy alignment are closely tied to the attitudes and behaviors of the people within the firms
(Morgan-Thomas, 2016; Orlikowski and Scott, 2015), with personal curiosity and open-
mindedness being key individual capabilities driving them:
I am not afraid of learning new technologies and this is really important. First, I
evaluate whether or not it is worth introducing into the company and then I teach my
colleagues…. It is important not to reject changes. On the contrary, I am always
looking for new technologies or tools to integrate them into the company. I select
them and prioritize based on the level of interest for the company. (Medium-Spain-
I think there’s an openness from the top, from the board, to say we understand we’re
in a digital age and we do want to embrace it. (Small-Britain-Manufacturer)
Our findings also show that, similar to large organizations, SMEs do not adopt one
approach to digital aligning, and the phase of alignment cannot be measured in terms of
whether particular digital technologies (e.g., social media, cloud services) have been adopted.
Rather, it is the effective integration of technology with the business’s strategy, following a
localized, incremental, reconfiguration approach, that leads to alignment (Tanriverdi et al.,
2010). For some firms, this integration leads to adopting a small number of technologies, while
for others, a large number.
Our conceptualization of digital alignment and subsequent fieldwork resulted in the
identification of five phases, each exhibiting different types of technology use (ad hoc vs.
integrated) and different approaches to technology adoption (reactive vs. purposeful), as
illustrated in Fig. 1. Consistent with previous conceptualizations of IS alignment (e.g., Yeow
et al., 2018), our model depicts intentional and integrated uses of digital technology as higher
levels of digital strategy alignment. However, this representation does not mean that some
phases are superior to others or that SMEs should or do progress linearly from one phase to the
next (see Iannaci et al., 2019). For an SME competing on price rather than innovation or
customer service, for example, it may not make sense to move from “fusion” to
“transformation”; conversely, a new venture whose business model is based on disrupting the
market may move quickly to the “transformation” phase, skipping some or all of the others.
Within each phase, there are moments of technology exploitation and exploration, in response
to perceived changes in the firm’s environment (Marabelli and Galliers, 2017), and use of
different combinations of the sensing, seizing, and reorganizing capabilities.
Fig. 1. A five-phase model of digital strategy aligning in SMEs.
As mentioned previously, our five-phase model builds on the work of Yeow et al.
(2018) and El Sawy (2003). Although Yeow et al. commence with the “exploratory” phase,
when managers articulate and acknowledge the potentiality of digital technologies, our model
identifies an important prequel phase—passive acceptance. In this phase, the external
environment exerts pressure on the firm such that it must adopt digital technology to continue
in business. Yeow’s et al.’s framework pays limited attention to the impact of the external
regulatory environment on the adoption of digital technologies as a trigger for digital strategy
aligning. Our results revealed a recognition of the need for change based on external regulatory
and, sometimes, customer pressure, rather than internal, firm-led drivers and resultant
activities. The detection of this prequel phase among our sample is consistent with Cenamor et
al.’s (2019) observation that many SME managers lack an understanding of the connections
between digital technologies and broader business strategy and performance.
By introducing this phase, we acknowledge that firms may deploy digital technology
even though they have little or no intention to progress toward more intense or more strategic
use of the technology (Iannaci et al., 2019). This phase can be compared with Sebastian et al.’s
(2017) “defining” phase or Davison et al.’s (2005) “rhetorical intention” phase, in which there
are some visible uses of the technology and even public statements of intent, but these are not
supported by planning or structured implementation.
Moreover, in this phase, the sensing, seizing, and reorganizing elements of DCs are
present but embryonic. They form the bases for further digital activities, though progression is
by no means guaranteed. Sensing is mostly focused on obligations and compulsory regulation,
policy, or other external forces (Kurnia et al., 2015). Seizing aims to identify shortcuts and
opportunities to reduce costs, while reorganizing is reactive and lacking in detailed planning
(Gutierrez et al., 2009; Jones et al., 2014; Kitsios and Kamariotou, 2019).
The second phase, “connection,” differs from the first phase, with more extensive use
of technology (albeit still limited) and, more important, a change in attitudes toward technology
use (Li et al., 2016). Specifically, we find an intentional, if tentative, use of various tools.
Employees use technology particularly for repetitive tasks or for collaborative work, though
the lack of internal expertise in digital technologies presents a challenge (Wang and Rusu,
2018). Both Gebhardt et al. (2006) and Libaers et al. (2016) observe similar localized responses
to the sensing of an external threat to the business, with seizing activities focused on process
efficiencies. This phase shows investment in some of the core components of the organization’s
backbone (Sebastian et al., 2017), but it is short-term, not strategic. This phase echoes Yeow
et al.’s (2018) exploratory phase and El Sawy’s (2003) connection view, in which
environmental scanning occurs and employees commence cross-functional communication to
identify and acquire specific resources.
The results of our study also identified a phase between the “exploratory” and
“building” phases of Yeow et al. (2018). Our more nuanced phase of “immersion” draws on
the work of El Sawy (2003) and includes a recognition by leadership of the potential of digital
technology as a support structure for the business (Li et al., 2016). This intermediary phase is
important because now firms explicitly consider the possibilities and benefits of digital strategy
alignment (Morgan-Thomas, 2016) and begin enacting a cultural shift. Processes, people, and
technology become interdependent (Orlikowski, 2010), which is reflected in the organization’s
activity. The characteristics of the owner/manager are influential in the decision to commit to
digital technologies (Belso-Martinez et al., 2013; Gao and Hafsi, 2015; Li et al., 2016). There
is an appreciation of the need for adaptive change across the whole firm (Girod and
Whittington, 2017), though full integration remains an aspiration. The working environment
changes with, for example, the adoption of Internet-enabled applications, customer relationship
management systems, online order management, and e-commerce. Digital technologies
support the strategy, both internally and externally. Much emphasis is put on internal
communications and the use of technology to assist in understanding the market, and actions
move beyond problem solving to leveraging knowledge. This phase is the tipping point
mentioned by El Sawy (2003) but absent in Yeow et al.’s (2018) model.
In our fourth phase, “fusion,” there is no division between business strategy and the
technologies used to drive it (Mithas et al., 2013; Sirén and Kohtamäki, 2016). This phase
manifests through “always-on” digital technologies, the use of multimedia, data mining, cloud
storage, and real-time supply chain management. Tanriverdi et al. (2010) label this phase the
“integration quest,” and Gebhardt et al. (2006) highlight the embedding of change through
formalization of activities and processes. Yeow et al. (2018) term this the “building” phase and
El Sawy (2003) the “fusion” view, in which systems are reconfigured to support strategic
initiatives. The effectiveness of implementation may depend on the experience of key
individuals (Ates et al., 2013; Li et al., 2016), their level of risk aversion in their decision
making, and the presence of core technological assets, such as an operational backbone and a
digital services platform (Sebastian et al., 2017). Learning from the changes adopted to develop
DCs (Sirén and Kohtamäki, 2016; Teece, 2007) is a feature of this phase for SMEs.
The fifth phase of alignment is the “transformation” phase. While the final phase in
Yeow et al.’s (2018) model involves growing the firm and leveraging its capabilities, our final
phase moves beyond these activities to a culture in which strategic unsettling is deliberately
created. Technologies are used to reappraise business models, enable positive disruption
(Henderson and Venkatraman, 1993), encourage innovation in the firm, and “facilitate
experimentation” (Sebastian et al., 2017, p. 203), in the form of dynamic, ongoing responses
that evolve with the needs of the business (Karpovsky and Galliers, 2015). Organizations
demonstrate openness, vigilance, and readiness to experiment, often through visionary
leadership (Li et al., 2016), which enables them to keep up with larger direct or indirect
competitors. Our evidence shows that firms in the transformation phase challenge the status
quo and then begin shaping their environment by enacting novel ideas (Libaers et al., 2016),
thus creating a new culture. Transformation also involves constant awareness and absorption
of feedback from the market to maintain this state of readiness (Calabretta and Kleinsmann,
Uniqueness of the SME context
Our new five-phase model (Fig. 1) presents a conceptualization of digital strategy
aligning in SMEs based on real-world experiences (Karpovsky and Galliers, 2015) and
provides a holistic understanding of the phenomenon and the capabilities that shape it (Spinelli
et al., 2013; Street et al., 2017). It illustrates the nuances in the digital aligning strategies of
SMEs and can help identify the current position of an SME relative to others. We propose an
indicative model that encompasses the principles of analytical theory proposed by Gregor
(2006). Analytical theory in IS is valuable when little is known about the phenomenon in
question. When relationships between factors are associative, this type of foundational theory
can help develop further theory for predicting, designing, and taking action (Gregor 2006).
Furthermore, the proposed model attempts to redress Renaud et al.’s (2016, p. 88) criticism
that “[m]odels describe sociotechnical systems through geometric representations in which
practitioners and the social dimension of the IS disappears behind theoretical abstractions.”
Accordingly, our model encompasses a sociotechnical approach that acknowledges the role of
human actors in business strategy and strategic alignment and answers Renaud et al.’s (2016)
call for a broader non-functionalist model of strategic aligning. Our model shows the processes
of connection between IS and business strategy within the context of SMEs and demonstrates
how this happens in practice, as called for by Vial (2019), Street et al. (2017), and Mohd Salleh
et al. (2017). Our model is meant not to be normative or predictive but inductive; it does not
suggest that SMEs should adopt specific behaviors or progress through each of the five steps
Building on our findings, we offer five observations with regard to SMEs and large
firms. First, as for large organizations (Sebastian et al., 2017; Yeow et al., 2018), different
phases of digital strategic alignment are associated with the deployment of specific sensing,
seizing, and reorganizing capabilities (Roberts et al., 2016; Teece, 2007). Second, this
deployment is commonly influenced by social actors’ perceptions (Li et al., 2016; Morgan-
Thomas, 2016; Orlikowski and Scott, 2015) and behaviors (Whittington, 2014). However,
unlike their larger counterparts, in SMEs this subjective assessment of the environment is
largely dependent on the cognition of the firm’s leader (Cenamor et al., 2019; Li et al., 2016),
rather than the groups or departments leading technology deployment.
Third, digital strategy aligning in SMEs has specific characteristics not generally found
in large firms—namely, that how key individuals in the organization interpret external
influences is highly consequential for organizational innovation and change, with the role of
individuals in strategizing being highly determinant (Vaccaro et al., 2012). We found that
individual digital leadership influences the level and approach to technology use in SMEs,
echoing Li et al.’s (2016) findings. Moreover, cognitive inertia (Cenamor et al., 2019) was
apparent in the earlier phases (passive acceptance and connection) of digital aligning, as firms’
leaders did not demonstrate appreciation for the linkages between digital technologies and
Fourth, the financial limitations (Sirén and Kohtamäki, 2016) and lack of technical
expertise (Wang and Rusu, 2018) in SMEs conditioned the purchase, implementation, and
support of digital assets with which to bring about digital aligning (Nieves, 2016). However,
these firms’ flexibility and agility to effect change (Libaers et al., 2016), as well as their rapid
decision making (Baker and Sinkula, 2009), enabled this enactment to occur rapidly,
particularly in later phases (immersion, fusion, and transformation). Fifth, compared with large
organizations (Girod and Whittington, 2017), SMEs may benefit from reorganization by
reconfiguring rather than restructuring, as a means to adapt to the digital environment.
When enacting strategic digital aligning, SMEs need to look beyond single initiatives
and consider how strategy can be embedded through organizational practice (Kamariotou et
al., 2018; Marabelli and Galliers, 2017) and the broader environment (Bharadwaj et al., 2013;
Orlikowski et al., 2016). Our study shows that some firms do this, particularly in the connection
and immersion phases. We uncovered the underpinning concepts of learning (Winter, 2003),
opportunistic behavior (Baker and Sinkula, 2009), and fluid IT development (El Sawy, 2003;
Hao and Song, 2016; Tanriverdi et al., 2010) in the connection, immersion, and fusion phases
and demonstrated digital aligning in the fusion phase.
This study set out to develop a holistic view of how SMEs deploy DCs to achieve digital
strategic alignment. Our conceptualization of digital alignment as a nuanced process
comprising five phases of aligning addresses many of the limitations specified in prior work
on digital alignment. In our study, we identified different combinations of sensing, seizing, and
reorganizing behaviors associated with different types of IS strategy aligning, thus addressing
Yeow et al.’s (2018) inability to account for the variety of approaches to alignment reported in
the literature (Karpovsky and Galliers, 2015). Furthermore, our research dissects the process
of IS strategizing described in Marabelli and Galliers (2017) and extends Yeow et al.’s (2018)
digital alignment model.
The contribution of our new conceptualizations—the passive acceptance and
transformation phases of digital aligning—helps extend strategic IS scholarship in several
ways. First, our conceptualizations provide nuance to previous models. Thus, we offer insight
into the shaping of attitudes and behaviors at the outset of digital alignment activity, the
recognition of the intertwining of people and digital technologies during alignment, and the
potential transformative outcomes of digital alignment when realized.
Second, these more nuanced phases shed greater light on the nature of alignment.
Unlike hierarchical models (e.g., Churchill and Lewis, 1983; Scott and Bruce, 1987), our model
is not based on a single measure (e.g., the number of digital technologies adopted) and therefore
provides a more robust indication of the characteristics of each phase and the variety of
behaviors that SMEs may exhibit. Moreover, our five-phase model identifies the behaviors
associated with different phases, including the mindset of those leading the organization.
Third, IS strategy literature is lacking in practice-based research data, with prior
research focusing on macro-level thinking rather than micro, everyday practices that enact
strategy (Marabelli and Galliers, 2017). Our study incorporates both organizational behaviors
and changes in strategizing, while accounting for how individuals practice strategy. In doing
so, it situates the individual within the behavior of the organization as it pursues strategic digital
alignment (Orlikowski et al., 2016).
Fourth, our findings, though focused on SMEs, may hold relevance for digital strategy
aligning in large organizations as well. SMEs often operate in the same markets as large firms,
so a failure to investigate how they pursue digital alignment provides an incomplete
understanding of the context in which large firms operate. In addition, while SMEs are more
flexible with less structural complexity and have fewer legacy constraints than large
organizations, sometimes large firms are either broken into smaller units (e.g., geographical
units) or internally divided in the hope of mirroring the flexibility and innovative behaviors of
their smaller, more entrepreneurial counterparts. Moreover, the enacted behaviors associated
with SME digital strategy aligning may be relevant for large organizations. For example,
detecting that a business unit is in the passive acceptance phase of aligning may inform
subsequent interventions, such as making funding available or sharing best practices from
similar units in the immersion phase to reduce risk. Conversely, if a business unit is in the
transformation phase, it can serve as an exemplar for other organizational units.
Finally, our study answers some ongoing questions in the SME literature. For example,
our findings support the view that a lack of planning hinders IS development in SMEs
(Gutierrez et al., 2009) and also explain how digital leadership drives IS strategy alignment in
SMEs (Cenamor et al., 2019; Li et al., 2016).
Our study reveals the relative importance of external drivers for organizations at the
more reactive, ad hoc phases of technology adoption versus internal drivers for firms using
digital technology in a more proactive, integrated manner. Specifically, we did not find that
SMEs of a particular size, industry, or region were more likely than others to be in the early or
late phases of digital alignment. Instead, we found that when digital alignment was driven
mostly by external factors (e.g., regulatory pressures, consumer expectations), SMEs tended to
adopt arbitrary initiatives, with technology serving as a supportive element. By contrast, when
digital alignment was driven mostly by the enthusiasm and mindset of key individuals, SMEs
embraced transformative strategies, with technology intertwined with the business.
Three insights for SMEs derived from our findings may provide directional assistance
in digital strategic alignment. First, the influence of core personnel, especially managers, as the
drivers and facilitators of alignment should not be overlooked in digital strategy alignment.
Managers in SMEs may compensate for the lack of resources in comparison with large
organizations. SME leaders should act as key environment “sensors” and “learners” for their
organizations in terms of disseminating knowledge of trends, competitor activity, and
technological possibilities, to embed DCs in their organizations. Second, the flexible and
responsive characteristics of SMEs should be fully leveraged to embed digital technologies and
practices as incremental reconfigurations of the firm. The reduced structural complexity and
fewer legacy constraints of SMEs (vs. large firms) enable reorganization by reconfiguration,
which is advantageous in the digital environment (Girod and Whittington, 2017). Third, SMEs
can use our model as a diagnostic tool to help identify the phase of alignment they are currently
in, as this may assist them in determining which components of DCs to adopt.
Future research directions
This study contributes novel insight into both SME managerial perspectives and digital
strategy aligning, but it also has several limitations. The data were cross-sectional and collected
across a range of industries, which might limit understanding of the phenomenon. As SMEs
are developing entities, a longitudinal study involving multiple interviews in each firm would
help monitor firms’ continued aligning in the digital environment. Research could also extend
our approach by focusing on emerging countries. Alternatively, studies could adopt a sector-
specific approach to investigate whether any specificities of digital adoption are dependent on
the sector (e.g., service or manufacturing industries).
We sought to complement the interviewees’ descriptions of their organization and the
state of digitalization with secondary data. However, we acknowledge the limitation of the
study in terms of the restricted triangulation of the data collection. Only additional interviews
within each organization or analysis of contemporary firm documents would have enabled us
to confirm or challenge those narratives. As interviews are the “main road to multiple realities”
(Stake 1995, p. 64), future research could endeavor to obtain richer descriptions through
within-case interviewee triangulation (Farquhar et al., 2020).
Finally, future research could provide measurable insight into the phenomena identified
herein. For example, studies could identify and measure constructs influencing SME
owner/manager behaviors or identify specific relationships between the proactive adoption and
level of integration of technologies.
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Uses of digital technology identified
Phase of digital
ERP, no social media
ERP, Electronic data interchange (EDI), software product
traceability, no social media
ERP, software product traceability, Skype and Viber, no
Social media (Facebook, Twitter, Instagram, YouTube),
ERP, CRM, cloud systems, Google AdWords, online
E-commerce, social media (Facebook, Twitter, Instagram,
E-commerce, business management software, social
media (Facebook, Twitter), software product traceability
Social media (Facebook, LinkedIn and Twitter), cloud
(Google Apps), geolocation, balanced scorecard software.
Social media (Facebook, LinkedIn), ERP geolocation
Social media (Facebook and Twitter), B2B online
platforms, business management software, CRM
E-commerce, SEO, SEM, blog, social media (Facebook,
Twitter, Instagram, Google+), ERP, CRM (mailing,
newsletters), point of sale (POS), terminal solutions
Social media (Facebook, Twitter, LinkedIn), ERP, CRM
(mailing, newsletters), content management system
(CMS), open application programming interface (Open
API), other business management software
Social media (Facebook, Twitter), ERP, EDI
Blog, social media (Facebook, Twitter, LinkedIn), CRM
(notifications, newsletter, emails), data mining
Social media (Facebook, Twitter, Instagram, YouTube,
LinkedIn), Hootsuite, business intelligence, CRM
(notifications, newsletter, emails), e-commerce, automated
ticket booking, geolocation system, revenue management
Social media presence, videos, apps
Social media presence, videos, apps, YouTube channel,
blog, online shop
Social media presence, videos, apps, YouTube channel,
blog, online shop
Social media presence, videos, apps, YouTube, blog,
Social media presence, videos, YouTube, blog
Interactive website, social media presence, videos,
Social media presence, videos, YouTube, online booking
Social media presence, videos, YouTube
Apps, software, call back, limited social media
Cloud, online payment, social media, supply management
Online supply ordering, limited social media
Supply management system, social media presence
Interactive demos, call backs
Ecommerce, social media presence
YouTube channel, limited social media presence
Videos, YouTube channel, social media
Social media, online store
Social media presence, videos, YouTube, blog
Social media presence, blog
Social media presence, videos, apps, YouTube channel,
Interactive website, online booking, social media presence
Limited social media presence
Interactive website, social media presence
Interactive website, social media presence
Appendix 1. Characteristics of sample organizations
Appendix 2. Interview questions related to the components of DCs