Modular vs. Enterprise: Which One is Right for Your Business?

Introduction 

Data forms the epitome of modern-day organizational operations, acting both as a tool in supplementing decision-making and supporting corporate functions. And given rising consumer demands and desire to maintain competitiveness, investment in data centers has become a pivotal aspect for enterprises (365 Data Centers, 2016; Nazim et al., 2019). Current business environments are highly technology-driven, and given the increasing competition, some options for businesses entail building their own data centers or outsourcing (365 Data Centers, 2016). Thus, in the same manner that data is essential, management has a significant objective in deciding on data center strategies for adoption. It is paramount in assuring their organizations and realizing data-related objectives. According to Torell and Brown (2013), considering quantitative and the underlying qualitative differences is essential when deciding on appropriate data centers for adoption as part of the organization. Undertaking organizational changes and data center upgrades forms a common aspect in organizations (Torrel and Brown, 2013), as key in ensuring systems in place align with organizational needs and goals. Of the varied options, enterprises can opt towards upgrading their currently available data centers, initiate measures in building newer data centers, or as an alternative, collaborate with other entities for leasing space (365 Data Centers, 2016; Torrel & Brown, 2013). No matter the applied choice, an organization’s management must incorporate proper measures in cross-examining enterprise needs, consider the future plans and ensure the desired option supports meeting consumer needs. 

Data centers support sufficient data storage and consequent data dissemination (Cheng et al., 2018; Deloitte, 2014), and as such, decisions associated with these centers need significant considerations. With data accessible through the existing data centers, respective organizations can operate better and effectively towards determining underlying factors for their arising problems. Therefore, this process is pivotal in ensuring that enterprises can effectively visualize varied variable-related relationships for the organization's distinct systems and associated departments across building new data centers or opting for modular data centers. 

The planned research adopts a systematic review-based study approach, focusing on undertaking an in-depth examination and evaluation of past literature as a tool in supporting data center choice processes. Research evidence, primarily through desktop research, will become a vital aspect of this study, deciphering major technological concepts to deliver evidence on the proper route for undertaking data center decision processes. In accomplishing this study’s goal, there are critical questions for focusing on, data-related aims for realization as key to the research question, and critical objectives for attaining the current study. The accomplishment of these three aspects is the epitome of this research completion. 

Research Question: 

What are the quantitative and qualitative aspects for choosing between Modular and Enterprise build in selecting data center options? 

What are the (dis)advantages of Modular and Enterprise Build measures during Data Center planning for enterprises? 

Research Aim: 

This narrative review-based study aims at taking an in-depth evaluation of pre-existing literature on data centers, document the critical differences between modular and enterprise build data centers, and decipher underlying benefits associated with selecting either model. Through carrying out desktop research, while relying on existing scholarly databases, this research helps define critical technical and engineering aspects for consideration in supporting data center choice for entities. 

Research Objectives: 

To compare and contrast across Modular and Enterprise build data centers 

To assess and document the underlying cost implications for Modular and Enterprise build models in data centers 

To evaluate and describe (dis)advantages across modular and enterprise build data centers 

To determine the most appropriate data center adoption approach for existing and incoming enterprises 

To undertake a narrative review, by systematically reviewing past authors’ works, for documenting key aspects to consider for fact-based data center adoption decision phase 

Literature Review 

The main objective of this literature review segment is to provide the context for the interpretation of emerging and existing data on the pros and cons of owning data infrastructure vis-à-vis outsourcing. To effectively exhaust the discussion on these two concepts, six informational literature sources on the research topic were identified, and themes, ideas, and principles in each source were analyzed. The choice of the sources is based on their depth in addressing the costs of outsourcing data infrastructure compared to owning such infrastructure and the implications of each option on an organization. 

In Torell and Brown (2013), the authors recognize the technical and cost-related challenges experienced when arriving at the decision of upgrading current or existing data center, building or developing a novel center, or leasing office space for the purpose of erecting a data center. To effectively decide which of the available data handling options are most feasible in handling the challenge of data management, this literature source argues that quantitative and qualitative approaches towards data handling are critical (Torell & Brown, 2013). These two research approaches are essential in ensuring that all aspects or factors regarding data management are incorporated in the option deemed suitable, whether outsourcing or owning. 

According to Torell and Brown (2013), business growth is directly proportional to the entity’s information technology (IT) requirements. The IT requirements form the prerequisites of an organization’s growth; thus, its continuity is tied to the data handling and management choices an organization’s management and IT time makes. As argued by this source, the decision-making process begins with identifying the need for novel IT equipment. Upon such an event, the next brainstorming thought that often arises is the actual physical location where such novel information technology equipment would reside (Torell & Brown, 2013). An organization with already existing data centers connected to stable power supply, space capacity, and cooling is not to outsource but instead upgrade the existing data center to meet the new demand. However, in situations where the existing data center is nearing its maximum capacity or is already at its total capacity, the choice remains on where the new IT equipment would be housed. Therefore, regardless of the state of an organization’s data center, three vital options for meeting the arising IT capacity requirement: novel build-out, data center upgrade, or outsourcing. 

Similarly, Torell and Brown’s assertions are also affirmed in a publication by 365 Data Centers. According to 365 Data Centers (2021), purposes to critically compare the aggregate ownership cost of building one’s own data center vis-à-vis acquiring third-party colocation services. Like in Torell and Brown (2013), 365 Data Centers recognizes that the business growth triggers not only the need for reliable but also scalable data center space to collocate its dynamic information technology infrastructure. As presented in the source, colocation is a solution in addressing issues such as power downtime events that often cripple business operations as they contribute to a decline in productivity, loss in revenues, and customer churns. 

As a result, 365 Data Centers (2021) seek to prove that since successful organizations often outgrow their in-house telecommunication and computer infrastructures quickly, they are continuously faced with the challenge of ensuring that they have enabling environments for software development, Quality Assurance (QA), testing, and production applications. Their studies revealed an incremental surge in the preference for colocation services than enterprise data centers in their comprehensive analysis of the risks, costs, and opportunities attached to owning an in-house data center versus acquiring colocation services. The data relates to a 2015 data survey conducted that also reported that myriad data center workloads were progressively shifting out of private, single-tenant data centers. This shift was attributed to an increasing number of entrepreneurs, and investors found it more convenient to outsource their workloads to cloud and colocation service providers (365 Data Centers, 2021). 

Like 365 Data Centers (2021), Nazim et al. (2019) build their research on the findings that data center colocation services offer organizations, more so business entities, rental space infrastructure for their network servers, power supply, equipment rack, physical security, cooling, and internet bandwidth. This trend is boosted by the colocation service providers’ 24/7 technical supervision of nearly 100% uptime promise (Nazim et al., 2019). Additionally, the preference for colocation services is attributed to the increasingly high cost of building and maintaining enterprise in-house data centers. Moreover, colocation service providers also avail managed hosting services as well as Business Process Outsourcing (BPO) that accord them leverage and competitive advantage over enterprise in-house data centers. 

In their analysis of commonly preferred cloud deployment models, Nazim et al. (2019) identify three models: public cloud, hybrid cloud, and private cloud models. Additionally, the literature source also discusses a three-layered cloud computing model, namely Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) (Nazim et al., 2019). However, Nazim and co-authors also recognize some of the common challenges faced by modern colocation service providers, limiting the maximum preference by organizations that still express their indifference between having enterprise in-house data centers and outsourcing information technology data infrastructure. 

In yet similar findings, Watkins (2018) agrees with the data presented by Nazim et al. (2019) in stating that dynamic technological enhancements pose significant challenges to developing in-house data centers. In the literature, Watkins says that the choice to buy or build a new in-house data center is dependent on the quantity and quality of data amassed by organizations. Moreover, the choice between buying and building a data center is also determined by the type and nature of workload since there are those that are cloud-suited as well as those that are not. 

As a result, Watkins responds to the question that often arises when deciding whether to opt for classic built data infrastructure vis-à-vis purchasing conundrum in response to the need for additional data capacity, increased operations, and other IT infrastructural needs ( Watkins, 2018 ). Like 365 Data Centers (2021), Watkins also postulates that most organizations that initially preferred building their own data centers no longer find such initiatives sustainable due to the significant real estate costs associated with them, thus reverting to colocation options. Notably, findings suggest that the aggregate costs of owning a physical data center significantly surpass the perceived benefits; thus, managers prefer to buy than own. 

On the other hand, Chen et al.. (2018) address the significance of photonic switches in high-performance datacenter designs. The switches are specifically developed to meet the increasing performance demands of interconnection networks. Unlike the other sources that mainly compare owning and buying data centers, this source delves into the specific elements of datacenters that inform IT managers on the appropriate IT infrastructural option for their dynamic IT and operations demands. In this literature piece, the authors provide an overview of photonic switching technologies as well as develop an assessment methodology for examining the photonic switching technologies’ potential impact on datacenter performance. 

Finally, Deloitte (2014) also provides resourceful information on the considerations by Chief Financial Officers (CFOs) during their decision-making activities in favor of outsourcing data center services over building enterprise in-house data centers. Like the other five sources, Deloitte also acknowledges the high costs associated with owning data centers that house organizations’ information technology systems. As detailed in this publication, the costs are attributed to the increasing demand for IT and data center capacities as technological demands in the market change. Deloitte identifies four critical considerations for CFOs when making informed investment choices on data center capacity and preferred services: real estate, technology and infrastructure, commercial, tax, and finance, and risk, regulation, and continuity. 

Methodology 

Overview 

The methodology defines the directional approach adopted in one’s research, acting as a critical benchmark in documenting the significant processes (Creswell and Creswell, 2018). With this research focused on data centers, the goal lies in incorporating a narrative review method to accomplish the specified research question and attain the listed objectives. Data centers encompass critical features within the technological arena and are considered pivotal in allowing enterprises to gain competitiveness (365 Data Centers, 2016). Thus, as a tool in supporting business operations, applying the proper research method that aligns with the technical aspects of data centers and meets the study aim is critical. 

Research Method 

Narrative Review is applied as the primary research approach as essential in answering pre-listed study questions and support the realization/attainment of the study objectives. Primarily, with the review, there is offering or providing an in-depth synthesis of the different pre-selected published literature that focuses on a defined topic, helpful in describing the topic’s current state-of-art (Ferrari, 2015). As opposed to adopting a systematic review, which mainly adopts strict guidelines, e.g., PRISMA Technique (Ferrari, 2015), the proposed research will adopt a narrative review, which forms an example of a non-systematic review (Ferrari, 2015). 

Of the varied research methods, reliance on narrative review as key in this research serves critical benefits, all supporting the research aims. Compared to the application of quantitative tools, which mainly rely on numerical data while following strict quantitative-based measures (Creswell and Creswell, 2018), using the narrative review allows for flexible evaluation of past studies. As opposed to the restriction of the research process and measures on specific parameters, the utilization of narrative review, as a fundamental approach in this data center study, is paramount in increasing the study scope and offer a wider informational pool in cross-examining other studies, and document broader information. Lastly, by utilizing narrative review, there is the capacity to evaluate numerous studies and aggregate information from multiple sources (Ferrari, 2015), which helps support the research area. 

Data Collection/Access 

Secondary data/information will be applied in answering the questions defined as key for this study. With the study planned on using for narrative review, there is significant reliance on the efforts done by past authors within the area of data centers and other aspects associated with the topic. Notably, with the demand to deliver quality findings, access to reliable sources is critical for the success of this narrative review, of which gathering articles from reliable databases will be essential. Of the different databases, this research will incorporate scholarly articles from EEE Xplore, ASTM Compass, Engineering Village, Compendex, and ASME Library, among other relevant defined engineering and technology-based databases. Additional databases for utilization in meeting the study aims will include EBSCOhost, ProQuest, and Google Scholar. 

Scholarly Studies Selection and Inclusion Measures 

The quality of included articles in this research will play a vital role in supporting the findings, selecting sources that align with the topic, and meets distinct selection helpful criterion. Of the planned sources, the goal is utilizing sources within five (5) years as the central aspect of the research process, encompassing at least 80% of the content. Thus, based on the desired timeline, this will contain scholarly sources from 2018 to those published in 2021. Through this close-based approach and the reliance on current sources, it will be possible to ensure the research findings are recent and aligned with modern technological changes associated with the development of data centers. The literature search will also include published books and other reliable sources offering critical engineering-based information related to data centers in improving the informational scope. Incorporating published books will help obtain broader perspectives on the subject from different authors and supplement the information with what is communicated through published articles. 

Secondly, the literature search will primarily focus on “English-based” articles. Thus, even if there is the likelihood of other non-English sources holding some valuable information associated with the chosen topic, this inclusion criteria means they will be eliminated, as there is a strict focus on only English articles 

Thirdly, quality in sampled sources will be improved through relying on articles specifically published in identified journals. This is essential, given the review process the published articles pass through, which is vital in supporting their reliability. Therefore, there will be ensuring that at least 80% of the chosen sources are scholarly and associated with renowned journals, as pivotal in supporting the information’s credibility in supporting the current research. 

Ethical Considerations 

Professional integrity ranks pivotal in developing into quality scholars and helps improve a study’s applicability and validity with evidence from engineering (Stelios and Christodoulou, 2020). As such, adhering to ethical considerations associated with narrative reviews is essential in contributing to this study’s application. Since this research is not human-based, standard ethical considerations are not examined, focusing only on issues related to literature review. 

First, honesty during the research process and integrity promotion will be critical, and this relates to proper citation and recognition of all studies applied in supporting the current research. Since narrative reviews offer a more profound synthesis of varied previously published literature, focusing on a specific topic (Ferrari, 2015), there is reliance on other authors' works. As such, proper citation and acknowledgment of these studies will be essential in supporting the stud’s ethical considerations. 

Secondly, objectivity will be essential in this data center-based research. In ensuring objectivity, there is a focus on avoiding likely bias in this research, with proper communication and documentation of the various study aspects, by following existing research guidelines. Objectivity will thus be maintained from the study’s design, the documentation of the different literature, and eventually, during the respective findings. Also, relying on past studies, objectivity in their analysis, and documenting information from other authors is vital. 

Confidentiality and timely consideration of intellectual properties associated with the different sources will be vital. As an aspect of integrity, avoiding potential plagiarizing of other’s work is essential while preventing the duplication of other’s works without due acknowledgment. Due to the attached intellectual property on past studies, having respect and ensuring proper acknowledgment is paramount in supporting this research quality. 

Research Philosophy: Positivism Approach 

Objectivity ranks as the central aspect defining the planned research, which also is a crucial aspect evident in the positivism philosophical approach (Creswell and Creswell, 2018). There is an emphasis on developing knowledge through positivism by undertaking careful observation and in-depth measurements of existing realities objectively (Creswell and Creswell, 2018). This hence implies no bias can be incorporated through the research process, with objectivity as the epitome of the entire process. Moreover, using positivism, the goal lies in identifying and successfully assessing concepts towards the documentation of causes influencing or contributing to specific outcomes (Creswell and Creswell, 2018). Thus, of the varied philosophical approaches, this selected approach helps decipher critical concepts associated with choosing a data center model for adoption and will help explain significant factors related to the selected method. As opposed to choosing the data center approach based on single aspects, the study takes a multi-based approach, examining differences, advantages, the various similarities, and even disadvantages, towards making objective conclusions. 

Conclusion 

Research on data centers undertaken by previous authors helps depict the critical aspects in this area and document significant factors associated with how important data centers are within organizations (e.g., as seen from 365 Data Centers, 2016; Torrel & Brown, 2013). With decision-making as a primal aspect in organizations, the proposed research will examine underlying qualitative factors, accompanied by pre-existing quantitative factors vital in choosing the right data center adoption approach for enterprises. Of the options, this research targets cross-examining the Modular option, with efficiency compared to the Enterprise Build option as the leading alternatives. 

In accomplishing this data center specific study, there is reliance on narrative review, as the primary research approach, which primarily focuses on undertaking in-depth synthesis of the various chosen published literature on a specific topic (Ferrari, 2015), of which in this case, will focus on data centers, and the particular choice alternatives, i.e., Modular option, comparative to Enterprise build option. This research adopts a positivism philosophy and is critical in ensuring adherence to distinct ethical considerations, including professional integrity, which is essential to improving a study’s applicability (Stelios and Christodoulou, 2020). Confidentiality and considering the examined studies' intellectual properties are vital. This will be realized through proper source acknowledgment and objectivity throughout the research process, which is essential in the positivism philosophy (Creswell and Creswell, 2018). 

Time-Table 

	Week 1	Week 2	Week 3	Week 4	Week 5	Week 6	Week 7	Week 8	Week 9	Week 10
Proposal submission
Changes
Introduction/Literature Search
Writing of Project Literature Review
Writing of Project Methods
Writing of Project’s Discussion
Writing of Project’s Implications
Writing of Project’s Limitations, Conclusions, and Further Research Areas
Making corrections/incorporating feedback
Completion & Submission

References 

365 Data Centers., 2021, April 14. Data center Colocation - Build vs. buy. Retrieved from https://365datacenters.com/resources/white-papers/data-center-colocation-build-vs-buy/ 

Cheng, Q., Rumley, S., Bahadori, M. and Bergman, K., 2018. Photonic switching in high-performance data centers.  Optics express ,  26 (12), pp.16022-16043. https://www.tandfonline.com/doi/abs/10.1179/2047480615Z.000000000329 

Top of Form 

Creswell, J. W., & Creswell, J. D. (2019).  Research design: Qualitative, quantitative, and mixed methods approaches . Thousand Oaks, California: SAGE Publications, Inc. 

Bottom of Form 

Deloitte., 2014. Smarter Data Centre Outsourcing Considerations for CFOs. Deloitte Touche Tohmatsu https://www2.deloitte.com/content/dam/Deloitte/au/Documents/technology/deloitte-au-technology-smarter-data-centre-outsourcing-cfo-040314.PDF 

Ferrari, R., 2015. Writing narrative style literature reviews.  Medical Writing ,  24 (4), pp.230-235. 

Nazim, N.F.M., Senapi, S.N.H., Yatin, S.F.M., Hussin, N., Ngah, N.H. and Muhammad, N.A.M., 2019. Data Centre Colocation: Challenges and Opportunities in Private, Public and Hybrid Cloud for Businesses.  International journal of academic research in business and social sciences ,  9 (6). 

Torell, W. and Brown, K., 2013. Considerations for Owning versus Outsourcing Data Center Physical Infrastructure.  White Paper ,  171 , p. 20. 

Watkins, D., 2018. Data Center Build Vs. Buy. iMiller Public Relations . https://datacenterpost.com/data-center-build-vs-buy/