Over time, societies and economies have undergone complete transformations through the inclusion of new artifacts, namely the steam engine in the 18th century and railroads in the 19th century. Today digital technologies are having an impact on the transformation, entitled digital transformation (DT), of education, society and economy even deeper and more widespread than any other transformation that happened/occur in history. In order to better understand the impact that DT is having, data provided by the IDC study in 2017 shows that DT investment has tended to increase by 27% each year (2017–2020), and are projected to potentially reach around $
6.3 trillion in 2020 [1
]. It should be noted that, according to Westerman et al. [2
], organizations that have managed to make a proper and successful DT are 26%more profitable than their non-digital competitors.
DT can be defined as a disruptive change of organizations supported by digital technologies [3
]. As disruptive forces transform the different sectors of activity, many organizations are moving towards DT and embodying a more innovative mindset to thrive in this new era. Organizations who do not take advantage of this moment to evolve and transform themselves, are in danger of disappearing or being superseded by more agile organizations. In this sense, DT are also improving usability and accessibility in the educational context [4
]. Technology is ever-present and allows for the incorporation and strengthening of new educational strategies, currently employed in new teaching frameworks in the last two decades [5
DT supplies a plethora of competition, new business models, new organizational models and new services. For example, according to Chanias et al. [6
], there are new business models, and existing ones need to be adapted because of digital interfaces. According to Loonam et al. [7
] organizations wishing to use digital technologies to gain greater competitive advantage should also ensure that their respective business models are aligned with Information Systems (IS) which, by definition, include technologies. According to Westerman et al. [8
] there are five types of reinvention of technology-driven business models: (i) reinventing the entire industry (e.g., the way AirBnB innovated in the hotel market); (ii) the replacement of products and services (e.g., Tesla has done this within the car industry, by replacing traditional cars driven by petroleum derivatives with electric cars); (iii) by creating new digital businesses with the development of new products and services (e.g., the evolution introduced by Nike+ with iPod and iPhone connections); (iv) reconfiguring value-added models, where products and services are reinvented in the value chain (e.g., Volvo reconfigured its business model to provide more direct services to its customers), and (v) rethinking value propositions (e.g., Tokio Marine Holdings has developed an app that can provide an insurance policy on the spot for skiing-, golf- and travel-related insurance).
Burberry, as discussed in Hansen and Sai [9
], can be used as a quantifiable of DT’s positive experience. This organization digitally transformed its business in order to provide a perfect customer experience. This organization attributes its 30% growth during the 2008 sub-prime financial crisis largely to its Omni channel initiative, i.e., multi-channel integrated sales and marketing approach.
DT’s initiatives focus on leveraging greater customer engagement, delivering greater flexibility and agility to standardized and centralized operational processes, delivering new strategic opportunities to organizations, reconfiguring business models, creating new products and services, and in some cases, disrupting and reinventing value chains and industries [2
As mentioned above, for DT to take place must be supported by digital technologies, and it is in this context that Uhl and Gollenia [10
] argue that DT supports four technological pillars: (1) cloud computing, (2) mobile, (3) social and (4) big data-analytics. The most significant use of the pillars of DT has been driven by innovation accelerators, which include, among other solutions, IoT, robotics, 3D printing, artificial intelligence, augmented and virtual reality, cognitive systems and next generation (NextGen) security. To this extent, IDC expects that through 2021 innovation accelerator markets to grow by more than 18% [11
]. However, it should be noted that the role of technology in DT, as emphasized above, goes beyond automation and optimization; technology contributes to helping organizations achieve competitive differentiation by creating additional value [12
This article has as its main objective to evaluate and compare the current state of digital adoption in function of their preparation in relation to the prevailing technological categories including IoT, big data, social media, cloud computing, blockchain, augmented and virtual reality, among others, with future priorities of organizations in the implementation of DT, in Portuguese organizations. To achieve that, we have proposed a collaborative PBL exercise between different undergraduate management students, in order to assess their research skills, which are defined in their program. The exercise has a secondary objective: to assess the accessibility of the data that compose the state of digital adoption, by establishing a partnership with CIONET Portugal (https://www.cionet.com/cionet-portugal
4. Research Methodology
The purpose of this section is to describe the procedures used to collect data that are the basis of this research. The main feature of the scientific method is organized research, strict control of the use of observations and theoretical knowledge. For the present study, we used quantitative research methodology, since it is more appropriate to determine the opinions of the respondents based on structured questionnaires.
We have proposed an activity to the students of degree in Management of Business-Technology, and Digital Business Design and Innovation degree (both with a duration of eight semesters, four academic years). Both type of students during their formation must understand the importance of technology, and how to manage it, if they wish to pursue new opportunities. After a first course receiving generic content, in second and following academic years they move around the class, debating, helping their classmates, and, above all, applying the course content to their projects (PBL). They work in multi-disciplinary teams, side by side with organizations to overcome challenges, and knowing the necessities to be addressed, as for example in our case study. This activity was supported by a CIONET which ensured, on the one hand, the business perspective and practical application and, on the other hand, the adaptation of the questionnaire due to compliance issues. The basic concepts needed for our proposal, are explained in the subjects of Business Communication Skills I (four credits in the 1st semester), Principles of Business Management (six credits in the 1st semester), Macroeconomics (four credits in the 2nd semester), Management Information Technologies and Systems (four credits in the 3rd semester), Marketing Management (four credits in the 3rd semester), and Methods of Decision Analysis (four credits in the 4th semester). The objective was that they could propose an adaptation of the questions based on brief discussion about its topics and implications, with the possibility that other students could to improve any individual input.
The study was based on an online questionnaire with the title “Digital Transformation (DT) in Portugal”. Before being available online, the questionnaire was subjected to an evaluation of six experts in the field, academics and CIOs. CIONET, in conjunction with an institution of higher education, ensured the dissemination of this questionnaire to organizations.
The final questionnaire was online for 60 days and 77 valid responses were received. The data collected were pooled and treated by using the IBM SPSS Statistics 24.0 software and Microsoft Excel 2016.
The questionnaire consists of three parts which include: “Organization characterization” (Part 1, with four questions), “Organization characterization regarding Digital Transformation, at present” (Part 2, with nine questions), and “Organizational future regarding Digital Transformation” (Part 3, with two questions).
The statistical analyses used for the data analysis [50
] were Descriptive Analysis (frequency analysis, descriptive statistics and graphical representations), Inferential Analysis (Spearman’s ordinal correlation, Kruskall-Wallis nonparametric test and Wilcoxon nonparametric test for paired samples) and Multivariate Analysis (Categorical Principal Components Analysis (CATPCA) including Reliability Analysis (Cronbach’s Alpha) and Exploratory Factor Analysis (EFA)).
Spearman’s correlation was used to study the relationship between variables measure on an ordinal scale. Thus, given the ordinal nature of the variables and, with the objective of evaluating differences between them we applied nonparametric tests (because the condition of the normality is not verified). Kruskall-Wallis and Wilcoxon methods are examples of application of these tests.
Categorical Principal Components Analysis (CATPCA) was used to transform correlated variables in a small set of independent variables. This is the appropriate alternative technique to Principal Component Analysis (PCA) when variables are not quantitative. In order to determine the structural relationships that link factors to variables, the appropriate multivariate technique was Exploratory Factor Analysis (EFA).
According to the two most widely adopted approaches (power analysis [52
] and rules of thumb [53
]) for estimating the sample size, it can be considered that the sample size used is sufficient for this study. For example, for the Spearman correlation coefficient, with a sample size of 77, we found a power value of 0.999996. For the multivariate techniques, we use rules of thumb. For example, for EFA, the sample size used verifies the condition of being between 5 k and 10 k, where k is the number of variables.
5. Analysis and Discussion of the Results
The characterization of the organization (Part 1 of the questionnaire) is very succinct given the limitation imposed by the General Data Protection Regulation (GDPR). As a result of the four questions in this section relating to the characterization of the organization, we only had access to the answers to two of them’: A2 (“What role do you play in the organization?”) and A4 (“What is the general feeling of your organization when it comes to technological disruption?”).
In relation to the role that the respondents play in the organization (question A2) to highlight the high percentage of senior executive/manager (54.6%) as well as 15.6% of CIO. Question A4 (“What is the general feeling of your organization when it comes to technological disruption?”), for which they can chose one of four options, we find that the most chosen option was “Provides new opportunities to improve business” (61%), the other options being of little relevance “Helps in the conquest of new markets” (18.2%) and “Represents a threat to the survival of the organization” (6.5%). Finally, we should point out, the worrisome percentage (14.3%), for the option that states, “Eventually the organization will adapt”.
In Part 2 “Organization characterization regarding digital transformation, at present” we have nine questions (B1 to B9). The first three questions, B1 (“The organization has explored how Digital Transformation impacts suppliers, distributors and other partners”), B2 (“The organization’s leadership has considered the costs, savings and return on investment associated with Digital Transformation”) and B3 (“The organization has, a plan, or strategy, to implement Digital Transformation”) use a five-point Likert scale ranging from: “Strongly disagree” (1) to “Strongly Agree” (5). We found that the percentage of respondents who agree/strongly agree on all these issues varies between 62% and 69%, a result that is expected in some way, taking into account the leadership functions performed by the respondents in their respective organizations. It should also be pointed out that around 20% of responses are neutral.
Given the high percentage of respondents who said they agreed with questions B1 and B3, we found it of interest to assess how well those views were aligned. For this, we calculated the Spearman’s ordinal correlation, having obtained a strong positive correlation (rs = 0.631) and significant at 0.01 level, which reveals that those who most agree that the organization has explored how DT impacts suppliers’ distributors and other partners are also those who most agree that the organization has, a plan, or strategy, to implement DT.
Questions B4 (“What is the most important goal of the Digital Transformation strategy in your organization?”), B5 (“Who leads the Digital Transformation initiative in your organization?”), B6 (“What are the main factors that currently help your organization implement Digital Transformation?”) and B7 (“What are the biggest obstacles that prevent your organization from implementing Digital Transformation?”) are on a nominal scale and the respondents could choose one or more options.
In relation to question B4, according to the role that the respondent play in the organization, the main conclusions were: for CEOs and Senior managers the most important goal of DT’s strategy is “Modernize legacy IT Systems/processes and reduce costs” (60% and 47.6% respectively); for CIO’s and Senior executive, the goal most pointed out to was reach and engage with customers more effectively (50% and 64.7% respectively). Finally, the high percentage (66.7%) attributed by the General Manager to the “Achieve better visibility to the business and increasing the income” goal should be highlighted.
Although there are organizations in which the new role of CDO begins to emerge at the level of the organization’s management, in the sample of Portuguese organizations under study, no respondents with this role were found.
When questioned regarding the main factors that help (_h) implementation of DT (question B6), the “Leadership Vision” (Leadership_h) factor pointed out by 64.9% of the organizations, stands out significantly. It can also highlight the “Culture of the organization” (Culture_h) (48.1%) and the “Technological partners” (Tec_partners_h) (40.3%) as relevant indicators. The low result (27.3%), which was surprising to us, regarding the indicator “Collaborators with knowledge” (Competences_h) it should also be mentioned.
The most referenced obstacles (_o) that prevent organization from implement DT (question B7), with approximately equal percentages are the, “Culture of the organization” (Culture_o) and “Inadequate budgets” (Budget_o) with the values, 42.9% and 40.3%, respectively.
In view of these results, it is important to discover and analyze, in respect of these interrelated questions (B6 and B7) which indicators/obstacles (variables) that facilitate or disrupt DT implementation. For this and using exploratory technique EFA to determine the structural relationships that link the factors to the variables, we apply the principal components method followed by a Varimax rotation for extraction (the one that produced a more interpretable solution). This analysis produced scores that summarize the information present in the multiple indicators/obstacles in a reduced number of factors. Table 1
presents the factorial weights of each indicator/obstacle in the 3 retained factors (Kaiser’s criterion and Scree plot criteria). Factorial weights higher than 0.4 in absolute value are highlighted in bold.
The first factor has high factorial weights in “Culture_h”, “Culture_o”, and “Budgets_o”. The second factor has high factorial weights in “Tec_partners_h”, “Leadership_h”, and “Leadership_o”. Finally, the third factor has a high factorial weight in “Budget_h” and moderate in “Budgets_o”. Thus, the first factor can be designated as “Culture of the organization”, the ‘second’ as “Vision of leadership” and, finally, the third factor can be called “Budget”.
and Figure 2
together allow us to obtain in detail the conclusions that follow. In Factor 1 (“Culture of the organization”), culture of the organization is a very important indicator to implement the DT in the organization and its shortage works as one of the biggest obstacles that prevent the organization from implementing DT. In this factor, it is also worth noting, the important weight of the inadequate budget as an obstacle. In Factor 2 (“Leadership Vision”), refers to being confused about what to do is a more significant obstacle to implementing the DT in the organization than a strong vision of leadership. On the other hand, respondents who think it is more important to have a vision of leadership as an aid to the implementation of DT, are the ones that least value the existence of technological partners. Finally, Factor 3 (“Budget”) shows that for the respondents, it is very important for the organization to have an adequate budget, as support in the implementation of the DT. Interestingly, the shortage of budget, although relevant, does not have as much weight when considered as an obstacle.
For questions B8 (“Evaluate the state of the organization’s current digital adoption for the following technology categories”) and B9 (“Classify the various departments of the organization based on their ability to adapt to technological change”) the respondents must classify ten technological categories (categories 1–10) and nine departments within a specific ordinal scale. Therefore, in question B8, the scale used for each of the categories was: (1) “Nothing prepared”, (2) “Unprepared”, (3) “Prepared”, (4) “Fully prepared” and (N/A) “Not applicable”, and for question B9 the following scale was used for each department of the organization: (1) “Not agile”, (2) “Not very agile”, (3) “Agile”, (4) “Extremely agile” and (N/A) “Not applicable”.
Thus, starting with a detailed analysis of the answers obtained for question B8, it is worth noting the large number of respondents who pointed out that “Blockchain” and “IoT Technology/Sensors” are technological categories that are not yet applied in their organization (N/A) (“Not Applicable”).
It should be noted that these categories are examples of innovation accelerators (see Section 2.2
) and they should not be used without careful analysis of the organization’s needs and strategy, such constraints mean that most Portuguese organizations still do not apply them.
In relation to categories with which the organizations have a greater degree of preparation, it has been verified that the one for which the organizations are more prepared are the 4 pillars of DT (“Agile Collaboration Tools” (category 8), “Mobility” (category 1), “Cloud Solutions” (category 2), and “Big Data & Analytics” (category 3) and also the categories “Robotics/Automation” (category 7) and “Virtual reality/Augmented reality” (category 6).
In order to evaluate if the general feeling of the organization when it comes to technological disruption (question A4) had a significant influence on the opinion of the degree of preparation of the current digital adoption in relation to the ten technological categories (question B8), we used Kruskal-Wallis’s non-parametric test for each of the categories. According to the results obtained, we conclude that question A4 only has a significant influence on the opinion of the respondents regarding the degree of preparation of “Blockchain” (category 10), as shown in Table 2
-value (Sig.) = 2.3% <5%).
However, the Kruskal-Wallis test does not indicate which of the feelings (question A4) had a significant effect on the respondents’ opinion of the degree of preparation in category 10. Therefore, to perform this identification process proceeded on to multiple comparison of the order using the Dunn test statistic [46
]. Using the unadjusted asymptotic p
-value (Sig.) (Table 3
), we can conclude that the significant differences occur between the general feeling “Eventually the organization will adapt” and “Helps in the conquest of new markets” and between “Eventually the organization will adapt” and “Provides new opportunities to improve business” (p
-value = 0.3% and 1, 2%, respectively).
Moreover, observing Figure 3
, we can also conclude that all the respondents who expressed as a general feeling of the organization “Eventually the organization will adapt” as an option, present as to the degree of preparation of the category “Blockchain”, distribution significantly different from the others that affirmed there is another feeling. It should also be noted that in this option all organizations are unprepared. We also found, as revealed in Figure 4
, that the options in question A4 that most influenced the evaluation of the respondents regarding the degree of preparation of the “Blockchain” are “Eventually the organization will adapt” and “Helps in the conquest of new markets” (boxplot and yellow line).
Regarding the most relevant results associated with question B9—Part 2 of the questionnaire—these were: 58% of respondents indicated that this question does not apply to the “Retail” department; the departments that have a greater degree of agility in the adaptation to technological change are “IT”, followed by “Marketing”.
In order to summarize the information presented in question B9, we use the CATPCA with the Varimax rotation method (the one that produced a more interpretable solution) and Kaiser Normalization [50
]. For component retention we use the rule of eigenvalue greater than 1 and percentage of explained variance higher than 70%. The internal consistency of the two components/dimensions (Table 4
) was measured with Cronbach’s Alpha [51
] (0.813 and 0.743, which shows a good internal consistency).
shows that the most agile departments in their ability to adapt to technological change (departments that are strongly related related to Dimension 1) are “Manufacturing/Logistics”, “Customer Service” and “Human Resources”. Departments of “Marketing” and “Sales/Business” are very strongly associated with Dimension 2 (second major component). Additionally, despite the lower relevance, we can state that the “Legal” and “IT” departments are correlated with Dimension 1. Finally, it should be noted that the weights obtained for the “Product management” department in both dimensions reflect the fact that the department’s ability to adapt to technological changes is explained simultaneously by both. Thus, we can conclude that Dimension 1 is the “Product/Customer” component and Dimension 2 is the “Marketing/Sales” component.
Combining the analysis of Table 5
with observation of Figure 4
, we can also distinguish four groups within organizations according to their adaptability (greater or less agility in adaptation) to the technological changes of the various departments of the organization: Business Group (Sales/Business and Marketing), Personal Group (Human resources and Legal department), Customer Group (Manufacturing/Logistics and Customer service) and Technological Group (IT).
In order to evaluate the future of the organization in relation to DT (“Organization future regarding Digital Transformation”—Part 3), given the accelerated pace of technological change, we began by investigating the organization’s adaptability over the next three years (Question C1). With the results obtained, we conclude that the majority (66.2%) of respondents think that their organizations are capable or very capable of implementing adequate adaptation, although a significant segment of 27.3% of the respondents think that their organizations are incapable or quite incapable.
For question C2 (“Evaluate (next 12–18 months) the priorities in the implementation of DT in the organization”), for the same technology categories of question B8, the respondents must classify the ten technologies within the following scale ranging: “No priority” (1), “Low priority” (2), “Strong priority” (3), “Total priority” (4) and (N/A) “Not applicable”.
The technological category that the respondents pointed out more frequently as a response to “Not applicable (N/A)” is “3D printing”. In relation to technological categories that the respondents of organizations evaluate as high priority to the implementation of DT in their organization, we conclude that these are the 4 pillars of DT (“Agile Collaboration Tools”, “Mobility”, “Cloud Solutions” and “Big Data & Analytics”).
Finally, with the objective of evaluating and comparing the current state of digital adoption in respect of the preparation of these in relation to the prevailing technological categories, with the future priorities of the organizations in the implementation of DT in Portuguese organizations we started by comparing the importance of technological categories, both in Present and in the Future (Questions B8 and C2). For this purpose, we applied the CATPCA with Equamax rotation (Table 6
and Figure 5
) and also the graphical representation of the average degrees assigned to each of the technological categories, in the present and the future (Figure 6
), as this was the descriptive measure which was more discriminating in the comparison of categories. Table 6
and Figure 5
show that the technological categories most closely related to Dimension 1 are:
In the present (P): “IoT/Sensors”, “3D printing”, “Big Data/Analytics”, “AI”, “VR/AR” and “Agile tools”.
In the future (F): “VR/AR”, “3D printing”, “IoT/Sensors”, “AI”, “Robotics/Automation” and “Blockchain”.
For Dimension 2 they are:
In the present (P): “Mobility”, “Robotics/Automation” and “Cloud Solutions”.
In the future (F): “Agile tools”, “Cloud Solutions”, “Big Data/Analytics” and “Mobility”.
It should also be noted that in Dimension 2, the “Blockchain” technological category in the Present, although with a moderate weight in this dimension and negative, is in contrast to the “Mobility”, “Robotics/Automation” and “Cloud Solutions” categories with positive weights.
shows the evolution of the results for the ten technological categories in present and future.
Associating the information from Table 6
with Figure 5
and Figure 6
, we can state that, in Dimension 1, the technological categories identified as preponderant in the Present are those that the respondents consider to be less prepared in their organizations. On the other hand, the technological categories identified as predominant in the Future, in this dimension, are those considered by them as less important than for the implementation of DT. Regarding Dimension 2, we verified that the technological categories with the greatest weight in the dimension were those that the respondents pointed out as being the best prepared categories in their organization regarding digital adoption in the Present. In the opinion of the respondents regarding the degree of priority of implementation in the Future, it was verified that the technological categories with greater weight, in this dimension, are those evaluated by them as being of priority.
More explicitly, we can conclude that, in relation to the technological categories that constitute the four pillars of DT (categories 1, 2, 3 and 8), the respondents evaluated their organizations as:
well prepared in relation to digital adoption in the Present for all categories, except for the “Agile tools” category (only with moderate preparation—category 8);
the categories are all priorities in relation to the implementation of DT in the Future, with particular relevance in the “Agile tools” category where the largest increase occurred.
Finally, there was a significant decrease in the degree of priority in the future implementation of “Robotics”, “VR/AR” and “3D printing” categories.
Summarizing, Dimension 1 can be designated by the technological categories with “Less preparation (P)/priority (F)” and Dimension 2 by “Greater preparation (P)/priority (F)”.
In order to verify if there are significant differences in the organizations’ evaluations, before and after (P/F), for each of the technological categories, we used Wilcoxon nonparametric tests (suitable for paired samples). We found that, in the “Mobility”, “3D printing” and “Blockchain” categories (categories 1, 5 and 10), there were no significant differences (p-values > 0.5) in the evaluations of organizations in Present and Future, conclusions which confirm the previous exploratory analysis.
6. Research Limitations
In the present research, a comparative evaluation of the current adoption and future priorities was carried out, in relation to the technological pillars and the accelerators of transformation and digital innovation in Portuguese organizations using an approach of a pre-designed collaborative PBL exercise to select the main indicators to evaluate, with the with the eventual collaboration of 15 undergraduate management students. The present research work is relevant since there are no significant inputs of this nature and scope in the existing literature.
As the area we are exploring is relatively unexplored territory, this research has encountered some limitations. The first concerns the number of responses obtained: although the study was released in a large number of organizations (CIONET’s online survey), the number of responses obtained was relatively low. Even though this limitation conditions, in a certain way, the generalization of our results, the data gathered is sufficient (see Section 4
) to reach the objectives proposed in this work. Furthermore, the need to define research avenues has been identified, to define future research lines that can use the results already obtained and continue the research in DT in its various aspects.
Second, given the legal constrictions imposed by the GPRD, it was not possible to define and analyze the results by business domain or by size of the organization. These two limitations may generate some bias in the analysis and in the overall discussion of the results obtained.
Third, the literature shows that DT is a very active research area and focuses on several areas of knowledge, namely the Behavioral and Information Systems areas. This means that investigation should also be extended to those fields of scientific knowledge.
The global results obtained are good in general, but not realistic. In comparison with previous international studies, for example Kane et al. [25
], affirm that: “only the 15% of responses obtained from companies at the early stages in processes of DT, affirms that their organizations have a clear and coherent digital strategy”. Spremic [54
], suggest that IT governance should be strategically focused in the organizations for a successful DT development, and for their implementation, companies should rely on skillful employees, as for example talent management, or systematically raising people’s competences with a continuous learning. Similar findings were identified by Reis et al. [55
], who affirm that managers should adapt their business strategy to a new digital reality, something that also affects the scholars, who are also facing changes, as prior research may not have identified all the opportunities and challenges of DT.
Our paper is one-step more in a currently widely strategy for identifying and compare the critical success factors in the DT and business strategy. Holotiuk and Beimborn [56
] work with a Digital Business Strategy framework (DBS), based on a structured review of 21 industry reports. From their analysis, they yield eight generic dimensions with 40 critical success factors, also called CSFs. This approach can be complementary to our study, and in a future extended study a possible system to use and compare. Libert, Beck and Wind [57
], present seven questions to ask before a new DT. In front of the assumption that the companies have about their preparation for DT, they have estimated that DT have a failures range from 66% to 84%. In addition, their proposal can be adapted in a future study incorporating their questions in a more complex survey to identify the real state of the DT in organizations.
From an educational perspective, our approach helped the students to identify the main types of data that can support their learning and support making decision systems. Extracting information from data to ultimately turn it into knowledge can contribute to drawing a complete picture of student learning which can empower them in their professional future, as well as stakeholders and policymakers who study such contexts. The project gave the students valuable date to follow an improve different subjects and educate them on the management of tools available to gather, organize, visualize, and analyze these data as well as methods for improving its accessibility, availability, usability, and understanding.
Finally, our objective of assessing the current position and future perspectives of the Portuguese organizations regarding DT was used a broader approach rather than an in-depth approach. Meaning that the complexity of the relations that should be studied in future research target on the subject and thus the specific relationships that emerge from the analysis will be deepened, both at the national level and in the international context.
Digital Transformation is becoming, more and more a common expression, due to its relevance to the life of organizations. DT, as discussed, may be considered essential for organizations to be competitive. However, this transformation cannot be undertaken through an ad hoc process but by a strategically defined and planned process as its results an impact throughout the organization, from processes and activities to business models. Organizations that do not adopt DT may disappear from the market. In order to understand the perception of Portuguese organizations regarding the adoption of DT, our team created a questionnaire.
The results presented and discussed in Section 5
, have shown a set of important findings that contribute to the understanding of the present and future position of the Portuguese organizations with regard to DT. Regarding the general feeling of the organization when it comes to technological disruption, we found that the most chosen option was “Provides new opportunities to improve business”. The results obtained are in line with the study presented in [49
], where 29 European countries are analyzed, which show that “… the feedback effects of the process are also worth considering, since the niche markets generated, greater competition, access to new markets, etc., all motivate entrepreneurs to introduce more innovations and corresponding digital transformations.”
In addition, we found that over 60% of respondents agree/strongly agree that their organizations: (i) explore how DT impacts suppliers, distributors and other partners, (ii) considered the costs, savings and return on investment associated with DT and that (iii) the organization has a plan, or strategy, to implement DT. We also conclude that the respondents that most agree that the organization has explored how DT impacts suppliers’ distributors and other partners are those who most agree that organization has, a plan or strategy, to implement DT. These results allowed us to have a perception of DT in Portugal, similar to those presented in [35
] related to a study applied in South Africa.
Related to indicators/obstacles that help or disrupt DT implementation, “Culture of the organization” is a very important indicator to implement the DT in the organization and its shortage works as one of the biggest obstacles that prevent the organization from implementing DT. Another factor (indicator) considered fundamental for digital transformation is “Leadership vision” (64%). This finding is reinforced by [47
] indicating that “… effective governance has been considered by some researchers as a critical lever for organizations to drive successful digital transformation.”
When organisational leadership is unsure how to proceed this presents a more significant obstacle to implementing the DT in the organization than a strong leadership vision. On the other hand, respondents who think it is more important to have a vision of leadership as an aid to the implementation of DT, are the ones that least value the existence of technological partners. For the respondents, it is very important for the organization to have an adequate budget, as support in the implementation of the DT. It can also highlight the “Technological partners” as relevant factor that help DT implementation. The results obtained are in agreement with the study presented in [35
], since the authors concluded that “The high number of factors identified by the participants suggested that organizational factors were dominant in their opinion when considering the adoption of digital transformation…”.
In respect of the departments with the highest degree of agility in the adaptation to technological change, the most chosen was “IT” followed by “Marketing”. Technological categories which the organizations point out as having a great degree of preparation were the 4 pillars of DT (“Agile Collaboration Tools” (category 8), “Mobility” (category 1), “Cloud Solutions” (category 2), and “Big Data & Analytics” (category 3)), “Robotics/Automation” (category 7) and “Virtual reality/Augmented reality” (category 6). Moreover, for these technological categories, organizations have been evaluated as well-prepared for all of them, with the exception of the “Agile tools” category. However, they are all a priority in the future with special emphasis (associated with the greatest increase) precisely in the “Agile tools” category. In the “Robotics”, “VR/AR” and “3D printing” categories there has been a decrease in the level of priority concerning future implementation. Finally, regarding technological categories, it should be noted that there are no significant differences in the present and future evaluations for the categories “Mobility”, “3D printing” and “Blockchain”. It should also be noted that the results obtained in the study are in agreement with those presented in [35
Regarding the most relevant results associated with ability, of the various departments of the organizations, to adapt to technological changes, we found that the most agile departments are Manufacturing/Logistics, Customer Service and Human Resources in the “Product/Customer” dimension (Dimension 1). For the dimension Marketing/Sales (Dimension 2), the most agile departments are Marketing and Sales/Business. A more detailed analysis of these results allowed us to identify four groups within organizations according to their adaptability to technological changes: Business, Customer, Personal and Technological.
An additional point of note is that although there are organizations in which the new role of CDO begins to emerge at the level of the organization’s management, in the sample of Portuguese organizations under study, no respondents with this function were found. Notwithstanding the result obtained for Portuguese organizations, CDO has a major role in companies, citing [46
] “CDO is both a bridge and a separator between business units and IT that ensures smooth project development and implementation.”
The completed research presented here confirms that digital transformation to succeed on the one hand must have a strategy and, on the other hand, leads to the transformation of the business model of the organization. However, the results obtained are not sufficiently enlightening to establish the implications for strategy and business models. In this context, the study confirms that an ad hoc transformation by organizations, i.e., without defining a digital transformation implementation strategy, and the behavior of actors at all hierarchical levels, namely CIOs, is counterproductive leading to failure and even endangers the organization itself.
Further studies are required by sector of activity to assess whether their business models are similar, which implies the existence of a more generic or sector-specific framework (e.g., Retail sector [58
]), while respecting the individuality of the intrinsic model of the organization [7
Although it has been found that Portuguese organizations are aware of the need to accommodate digital transformation, the study presented in [48
] found that Portugal, compared to the other 26 European Union countries, is relatively efficient in digital transformation.
This study has implications for both business and the academy. In an academic perspective, the study provides an exploratory review of the literature on digital transformation concepts, giving a conceptual structure of the main aspects of digital transformation in organizations that are still in a pre-digital phase and others already in transformation. This approach provides an initial perspective on how to manage the key factors to be addressed in order to carry out successful digital transformations. From a practical/practitioner point of view, the research gives us some valuable insights of the current situation of Portuguese organizations in the DT context, and despite the limitations already discussed in the previous section it points out potential outcomes in a near future.