4. Data Analysis and Findings
Figure 1 provides an overview of the questionnaire findings. Likert scale numbers 1 and 2 (totally disagree and disagree) were considered negative responses, combined (totalled) and shown in red. Likert scale number 3 was considered a neutral response and indicated in amber. Lastly, Likert scale numbers 4 and 5 (agree and totally agree) were considered positive responses, combined (totalled) and depicted in green.
Overall, the respondents view all organisational capabilities as important with Statement 5, “Understand how the competitive landscape evolves” and Statement 2, “Review product and services development efforts to ensure they align with customer requirements”, receiving the most positive ratings, whereby 78% (N = 38/49) agreed with this statement. Statement 11, “Synchronize tasks and activities with functional units across different locations”, is the most negatively rated question, whereby 35% (N = 17/49) disagreed with this statement. The most neutrally rated statements are Statement 7, “Improve coordination among different functional activities”, and Statement 9, “Ensure work outputs are synchronized across functional units and business partners”, with 35% (N = 17/49) of respondents rating both statements neutrally. Further, no respondent opted to answer the open-ended question.
The descriptive statistics include the mean, median, mode and standard deviation for the dataset. Mean is the average of the data points for each statement [
58], median is the middle value of the list of responses for each statement [
58], and mode is the value that occurs most often [
58]. A deviation from the mean is given by the standard deviation shown in
Figure 2 for the dataset [
58]. A standard deviation greater and equal to 1 indicates a relatively high variation, while a standard deviation less than 1 could be considered low. A low standard deviation indicates that the data points tend to be very close to the mean; a high standard deviation indicates that the data points are spread out over a large range of values [
58].
Figure 2 shows the standard deviation for this dataset.
The standard deviation is only below 1 for Questions 24, 9 and 2, indicating that the respondents are in general agreement about these statements. For all other statements, the standard deviation is above 1, with statements 13, 14, 16, 17, 19, 20 and 21 having a standard deviation of more than 1.2, indicating that respondents’ opinions were not highly correlated.
The 26 mean values were extracted as a separate dataset to prioritize the statements, and further quantitative data analysis was performed on the distribution of these values. For this new dataset, the mean is 3.57, the median is 3.59, and the standard deviation is 0.239. Statistical analysis revealed a confidence level of 0.0917 [
58,
59,
60] using a confidence level percentage of 95%. Applying this confidence level to the mean value (3.57) of the new dataset consisting of the 26 mean values of the statements presented an upper bound of 3.66 and a lower bound of 3.48. This created three distinct regions for categorising the data. First, mean values above the upper boundary are designated as most important since these statements received the most positive ratings from the participants (denoted in green). Second, mean values between the upper and lower boundaries are designated as of medium importance as they received the most neutral responses from participants (shown in amber). Lastly, statements below the lower boundary are designated as least important since they received the most negative responses from participants (denoted in red).
Table 3 displays the prioritization of the statements.
Table 3 presents the statement number, mean value and colour-coded priority for that statement. Green indicates statements with the highest priority, yellow indicates statements with medium priority, and red indicates statements with the lowest priority. The statements can now be grouped into the three priority groups depicted in
Table 4.
Table 4 shows that statements 1, 2, 3, 5, 6, 8, 13, 15, 24 and 25 are designated as high priority. Statements 9,14, 16, 20, 23 and 26 are designated as medium priority, and statements 4, 7, 10, 11, 12, 17, 18, 19, 21 and 22 are designated as low priority.
By considering these priorities, organisations are able to create a prioritized organisational transformation path pertaining to key Industry 4.0 organisational capabilities. Furthermore, organisations can ensure that Industry 4.0 organisational capabilities are incorporated into their Industry 4.0 vision and goals in a prioritized way, informing their strategy, business model, processes, products, services and culture alignment.
5. Discussion
A prototype checklist for organisations was developed using MS Excel to operationalize the study’s findings. This operationalized checklist could empower organisations to measure how well they are performing regarding the action captured in each statement. In addition, whenever an organisation flounders when applying the checklist, the statements guide organisations on improvement actions.
In considering the prioritisation of the statement actions, an overall contribution of weight was associated with each of the priority areas, namely an overall weight of 50 for high priority, 30 for medium priority and 20 for low priority statement actions, totalling 100. The weight allocated to a particular priority was assigned equally across the number of statements within the priority (statement action weight for high-priority statements 50/10 = 5). As the maximum rating per statement action can be 3, the individual weighted contribution of a statement action in the high-priority statement actions is 1.67 (5/3 = 1.6666). A weight can now be associated with each statement action, taking cognisance of the priority of the statement. To create a mastery profile for an organisation, it follows that such an organisation would score 3 for each statement action. Hence, the rating assigned to each statement action on the checklist can be multiplied by a specific factor or weight to either increase or decrease the contribution accompanying the specific statement action into the final score of the organisation.
Table 5 shows the checklist containing the statement action, the maximum rating (3), the weight assigned to each statement action, and the weighted total to which each statement action would contribute.
The next step comprised evaluating the prototype checklist for organisations. The evaluation was achieved through a two-step process. First, the digital profile of the organisations that would evaluate the checklist had to be understood. As this study pertained to Industry 4.0 transformation, the JISC digital capability framework applied in Clarke-Darrington et al. [
61] and Morze et al. [
62] was used to guide the digital capability domain descriptions shown in the first column of
Table 6.
The study approached two organisations in order to create their profiles based on the digital capability domains. Organisation #1 is in the education sector and Organisation #2 is in the finance sector. Organisations #1 and #2 proceeded to evaluate themselves against the digital capability domains. A scale of 0 to 1 was used, with 0 implying no compliance in the specified domain, 0.5 some compliance and one 1 full compliance in the digital capability domain.
Table 6 lists the six digital capability domains and the self-evaluation of the two organisations.
It can be observed from the organisations’ self-evaluation depicted in
Table 6 that Organisation #2 is a highly capable digital organisation with a rating of 5.5 out of a maximum of 6 in comparison to Organisation #1’s rating of 1.5. Organisation #1 excels in the area of data literacy, which is crucial for an organisation in the education sector.
The second step of the two-step process could be executed with the acquisition of two digital capability domain profiles. Each organisation was asked to rate their organisation on the checklist prototype shown in
Table 5 using a pre-defined scale. The pre-defined scale applied a measurement scale of 0 to 3, where 0 indicates that the organisation does not focus on a particular statement action at all, and 3 indicates that the organisation is aware of and continuously focuses on the statement action, showing mastery of that particular statement action. A score of 1 indicates that the organisation is aware of a statement action although no planning or monitoring of a statement action has yet been developed. A score of 2 indicates that the organisation is aware of a statement action, has put a plan into motion and is continuously working on it but has not yet reached mastery. The evaluation of Organisations #1 and #2 against the prototype checklist and by applying the pre-defined scale was then visualized with a radar chart for high-, medium- and low-priority statement actions, as shown in
Figure 3.
By observing the profiles based on the checklist evaluation by the organisations, Organisation #1, as the less digitally capable organisation, has a radar diagram much closer to the centre of the visualization, indicating low scores. However, in some areas, Organisation #1 has progressed on its digital journey, as reflected in the high scores for Statements 13 and 15, which is related to the organisation’s ability to identify and assimilate new knowledge, a capability vital to an educational organization. Furthermore, Organisation #1 has better overall scores for the high- and medium-priority statement actions, showing that this organisation is focusing on the important statements first. Organisation #2, on the other hand, has high ratings in all three priority domains, with the high- and medium-priority domains having nearly maximum ratings. This reflects the organisation’s high level of digital capability, as well as its prioritisation of high- and medium-priority statement actions. For Organisation #2, no statement was rated nil, indicating that this organisation is aware of the importance of these statement actions and is actively working in all three domains of importance. By focusing on the statement actions in which organisations scored low, such organisations can now use the statement actions to plan and execute corrective action.
Author Contributions
Conceptualisation, S.S. and A.v.d.M.; methodology, S.S. and A.v.d.M.; software, S.S.; validation, S.S.; formal analysis, S.S.; investigation, S.S.; resources, S.S.; data curation, S.S.; writing, namely original draft preparation, S.S.; writing, namely review and editing, S.S. and A.v.d.M.; visualisation, S.S.; supervision, A.v.d.M.; project administration, S.S.; funding acquisition, S.S. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was approved by the Ethics Committee of the Faculty of Engineering, Built Environment and Information Technology, University of Pretoria (protocol code EBIT/49/2020 and date of approval 3 September 2020).
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The data presented in this study are available on request from the corresponding author. The data are not publicly available because of the ethical clearance obtained.
Conflicts of Interest
The authors declare no conflicts of interest.
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