Data-Driven Enterprise Architecture for Pharmaceutical R&D

Round 1

Reviewer 1 Report (Previous Reviewer 2)

Comments and Suggestions for Authors

The study is interesting but still lacks methodological rigor and concrete information. Also, the theoretical background should be improved.

Improvement suggestions:

1. I recommend the authors to better address the potentialities of a data-driven organization in the pharmaceutical industry.  

2. Please clarify if Figure 1 is original or not.

3. The theoretical background of this study can be improved considering up-to-date published studies. Please read:

https://www.mdpi.com/2227-9717/11/7/2096

https://www.emerald.com/insight/content/doi/10.1108/EJIM-07-2021-0327/full/html

4. The concept of Pharma 4.0 has been proposed. It is important to present and explore it in the context of this study. Please read:

https://link.springer.com/article/10.1007/s11356-023-26856-y

https://link.springer.com/referenceworkentry/10.1007/978-3-030-58675-1_4-1

https://link.springer.com/chapter/10.1007/978-3-031-28839-5_59

5. The authors explore the sustainable growth of the framework but don’t enough explore its relevance to address the sustainable development goals. It would be relevant to explore it.

6. Authors note “The existence of parallel transformational tracks beyond the Global R&D illuminates the dynamic nature of architectural transformation within the Pharma company, where diverse divisions adapt methodologies in alignment with their distinct contexts and re-quirements.” However, they don’t critically explore how this should be managed to avoid the existence of silos.

7. Authors state “During Phase I “Gain Input & Analysis,” members of the Global R&D organization were sent a short survey to respond to the question.” How many members were contacted? All employees of the companies or only members with some specific role?

8. Authors state “To complement the survey, interviews with over 30 stakeholders…” Please be more precise with numbers.

9. It is not clear how the results of the survey and the interviews were analyzed. Did you use any software?

10. What is the structure of the survey? This information was not provided.

Comments on the Quality of English Language

it is fine. 

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 2 Report (New Reviewer)

Comments and Suggestions for Authors

Resource-based theory (RBT) has been a cornerstone of strategic management, providing valuable insights into how firms can leverage their internal resources to gain competitive advantage. However, like any theoretical framework, RBT is not without its limitations. For example:

 

1. Overemphasis on internal factors: RBT focuses primarily on internal resources and capabilities, neglecting the importance of external factors.

2. Accurately identifying and assessing resources is a challenging task for pharmaceutical R&D.

3. Resource-based theory emphasizes the importance of developing unique resources and capabilities to maintain competitive advantage. Resource-based theory, with its focus on stable and enduring resources, may provide limited insight into how to effectively navigate these dynamic environments. 

 

For these reasons, the resource-based theory may not be universally applicable across all organizational contexts and industries. This is particularly true of pharmaceutical R&D. Therefore, I have the following comment:

 

 

What are the research gaps in the manuscript? In other words, it should be rewritten to effectively clarify: (1). differences and new contributions of the current research compared to previous studies; (2). Please use academic theory to explain how RBV and dynamic capabilities are combined to produce DDA; (3). The method proposed in this manuscript is only a common rule, so it can be applied to any company/organization, not only to pharmaceutical R&D; and (4). this manuscript looks like a report, and the theoretical contribution and practical contributions are missing.

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report (Previous Reviewer 2)

Comments and Suggestions for Authors

I only recommend two minor improvements:

1. Align the balance between centralization and decentralization of the data strategy considering the theory around digitalization.

2. explore better the impact of Covid-19 in the digitalization processes of the organization.

Comments on the Quality of English Language

english is ok but the organization and layout can be improved. 

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report (New Reviewer)

Comments and Suggestions for Authors

The author has revised the manuscript, and the practical contribution has been slightly strengthened. Therefore, I recommend that this manuscript be accepted.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The topic is very interesting and important in the age of digital ecomony. While the discussion of the whole article is not an academic study, but more like a case study.  The whole paper lacks academic refinement and method support, and the verifyment of the results.

Comments on the Quality of English Language

In Abstract， “integrating into overall enterprise architecture” to “integrating it into overall enterprise architecture”. In line 228, "align an organization's IT systems” to "align organization's IT systems”.  In 256, "while negatively impacting the potential global value of shared data" is wrong. In line 425, " impact digital transformation goals" to " impact on digital transformation goals". In line 612, "consistency of data engineering" to "consistency in data engineering". In line 805, "card system which consolidates essential details" to "card system that consolidates essential details".

Reviewer 2 Report

Comments and Suggestions for Authors

The study is potentially interesting but is at a very early stage. The work carried out is mainly on the technical side. The scientific component is rather weak. The methodology adopted presents a high risk of bias. The potential for replicating the preliminary results is very limited. There is an excessive amount of speculative information without proper scientific justification.

Improvement suggestions:

1. Abstract is too long with too much contextual information. Furthermore, it should be written in a single paragraph.

2. This sentence “Studies and white papers…” is just supported in one reference.

3. Authors note “We have defined three levels of data-driven capabilities that companies must progress 60 along to truly embrace data.” This vision is not supported in any published framework.

4. Authors note “From a technical point of view an "API-First Strategy". It is not clear the separation between the scientific and technical points of view. The way these visions are interconnected is not explored.

5. Authors state “In addition to digital ecosystems, generative AI models like Chat GPT also play a significant role in the "Accelerative" level of data-driven capabilities” Once again this vision is not supported in the literature.

6. Digitalization is a fundamental term in this paper but the concept of big data is not explored.

7. Introduction section is too long and doesn’t explore correctly the research gap.

8. The concept of Data-Driven Enterprise Architecture (DDA) is not properly new. Please read:

https://www.frontiersin.org/articles/10.3389/fdata.2021.644651/full

https://www.sciencedirect.com/science/article/pii/S2405844022027724

https://ieeexplore.ieee.org/document/9254863

9. The proposed architecture should be compared against other architectures (see last comment) and it must be defined criteria to assess them

10. More detailed information about the case study should be given.

11. The methods used to explore the results are too informal. Did you perform interviews? Did you perform a thematic analysis?

12. It is not clear how the analysis of this case study can be migrated to other companies. The risk of bias is very high.

13. I would expect to have more practical contributions.

14. The number of references is very weak for a scientific paper.

15. The number of references based on journals is very low when compared to articles published in webpages.

Comments on the Quality of English Language

too much breaks of paragraphs. the connection must be improved.