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# Strategic Alignment and Industry 4.0: An Exploratory Study with Eleven Companies

Gilberto Francisco de Oliveira¹(✉) ID, Rodrigo Franco Gonçalves¹ ID, and Fernando José Barbin Laurindo² ID

¹ Universidade Paulista – UNIP, São Paulo, SP, Brasil
gilberto.oliveira18@aluno.unip.br

² Escola Politécnica da Universidade de São Paulo – EPUSP, São Paulo, SP, Brasil

**Abstract.** The technologies that make up the Industry 4.0 umbrella provide organizations with efficiency and flexibility, but without alignment with organizational strategies, below-average results can be achieved in comparison with the market. In order to avoid this failure, investments in I4.0 must support current or explore new business strategies. The present work aims to analyze how eleven companies located in Brazil can be typified in technological transformation alignment perspective by model of Henderson and Venkatraman. The eleven companies are large companies with consolidated initiatives to implement Industry 4.0. In the findings, it was possible to identify that the dominant adequacy to the strategic alignment model remains valid, despite the enabling technologies of Industry 4.0 to be recent. It is also highlighted the degree of concern about the type of strategic alignment chosen by these companies, which results in a temporary competitive advantage, as it allows imitation by other competing companies by not creating value in the customers' view.

**Keywords:** Industry 4.0 · Industrie 4.0 · Strategic alignment · Henderson and Venkatraman Model · Technology transformation · Competitive advantage

## 1 Introduction

There is a widespread paradigm that Industry 4.0 (I4.0) increases firm performance to the highest levels of competitiveness [1]. The technological tools that make the I4.0 possible bring advantages, such as better quality with lower production costs; customized production; process flexibility and efficient use of resources [2]. In contrast to the positive aspects, there are several risks involved in implementing I4.0 to consider when deciding to implement it. Of these, the lack of adherence to corporate strategic alignment stands out [3].

The business strategy is the result of the confrontation between the essential competencies of the organization in the face of opportunities and threats identified in the external environment. Core competencies increase the organization's competitive advantages (valuable, rare, expensive and non-replaceable) [4]. Information Technology and Digital
Communication (ITDC) plays a leading role in strategic alignment, and in the model proposed by Henderson & Venkatraman [5], it occurs in a bidirectional way [6]. However, despite the fact that I4.0 is essentially based on ITDC [1], there is no consolidated version of strategic alignment and one of the justifications lies in the fact that it is a relatively new area of study [3].

From the premise that the new technologies of I4.0 can contribute to the organizational strategy. The objective of this paper is to verify the application of Technological Transformation of the strategic alignment model between ITDC and Business developed by Henderson and Venkatrama [5] for companies that adopt I4.0 embedded technologies, for this, eleven companies located in the state of São Paulo, Brazil, were analyzed in a sample selected by convenience.

# 2 Theoretical Background

## 2.1 Industry 4.0

The I4.0 is related to the strong integration with industrial processes, aiming to improve quality, add value to activities and eliminate waste, mainly qualifying the data flow providing speed in transmission [7]. Organizations benefit from technologies covered in I4.0 in flexibility, real-time capacity monitoring, decentralization, modularity, operational and energy efficiency, interoperability, service orientation, virtualization, and sustainability [8].

The gains achieved with I4.0 have managed to break an important paradigm in production management, by making production in volume and variety more flexible without increasing cost [9]. The technologies that comprise I4.0 are broad, according to the literature, but the most used are Big Data Analytics, CPS, IoT, and Artificial Intelligence [2, 10–12].

## 2.2 Strategic Alignment Model

The literature defines “strategic alignment” as the process of transforming business strategy into actions that ensure that business objectives are supported [6]. Strategic alignment between business and ITDC means the synchronization between consolidated strategic business initiatives and the choices made in ITDC solutions and their governance, to achieve the maximum potential for results [13]. Authors have dedicated themselves to studying strategic alignment, since, in a dynamic market, efficiency in achieving business results is dependent on how ITDC is exploited by the organization [14]. The seminal model of Henderson and Venkatraman [5] is used to typify preponderant alignment [15].

The model develops four perspectives of dominant alignment by which an organization can be characterized [5]. The first two have a business strategy as a driving force: strategy execution and technology transformation, and the other two perspectives: competitive potential and service level, explore how information technology can enable new or improved business strategies with organizational implications [15].

In perspective two: technology transformation, the assessment of the implementation of the business strategy is based on the ITDC strategy and the articulation between infrastructure needs and the information system process. There is a more prominent adherence
to this perspective by companies when observing the application of I4.0 technologies [16]. This represents a tendency to apply ITDC solutions that can bring more flexibility to manufacturing operations until product delivery, without necessarily changing the business strategy [17]. Companies that adopt technology solutions embedded in I4.0 tend to give technology the ability to act preventively in their production processes, thus supporting decision making [2]. Technologies are essentially dedicated to improving to get data in operational processes and from this data, extracting information in an agile and efficient way [19]. Greater agility in data collection and processing enables decentralization and independence in decision-making in production cells [20]. The autonomy gained from digitalization enables vertical and horizontal integrations [21, 22], in addition to the ability to share operational information in real-time with different hierarchical levels of the company [9]. The technological transformation advocated with perspective two of the strategic alignment model is not just the result of the acquisition of new technologies with the adaptation of the factory layout [23], it also depends on the training of people all over the organization to obtain superior results in the attribution of their functions [24].

## 3 Research Method

The present work can be considered exploratory research [25]. Therefore, it is intended to analyze the adherence of organizations with initiatives to implement I4.0 technologies to the model of Henderson & Verkatraman [5] in its perspective Technological Transformation. The research question that motivated the study was “How are companies that apply emerging technologies from I4.0 positioned in perspective technological transformation of the strategic alignment proposed by Henderson and Venkatrama?”.

Methodological steps were followed to give consistency to the research process. Initially, it was performed a literature review to identify the theoretical basis, in which knowledge was obtained to identify the research question that guided the proposed study. With the literature review and the research question formulated, the next step was to determine the research protocol to carry out the data collection.

The data collection stage took place between May and June 2021, with eleven responding companies located in the state of São Paulo. A structured questionnaire based on a theoretical study was applied to the response of employees who occupy decision-making positions in these companies. The choice of the responding companies was based on the indication of market professionals and academics and for having already participated in research on the maturity in the implementation of emerging technologies of I4.0 [26].

The questionnaire has fourteen assertions, in which the respondent chooses between a Likert Scale ranging from 1 to 5. Where 1 means “totally disagree” and 5, he “totally agree” with the statement. The questionnaire was developed on a Web platform. The assertions were formulated from the findings in theory about characteristics of the technological transformation perspective and, thus, verify the existence and degree of strategic alignment in a company.
Table 1 addresses the assertions presented in the questionnaire, with the reference authors.

<table><caption>**Table 1. Questionnaire**</caption><thead><tr><td>At the company, I work for:</td><td>Support</td></tr></thead><tbody><tr><td>has confidence in its technologies to support decision-making and acts, based on the implemented technologies, in a preventive</td><td>[20]</td></tr><tr><td>manages to capture data in all its operational processes and organize it to derive value from it</td><td>[19]</td></tr><tr><td>has autonomous cells, that is, they operate independently in the entire manufacturing operation</td><td>[20]</td></tr><tr><td>has activity digitization that helps management</td><td>[21]</td></tr><tr><td>has vertical integration (the information sharing from the shop floor to company executives) and horizontal integration (the connection between all sectors of the production chain)</td><td>[21]</td></tr><tr><td>all those responsible for dealing with implemented Industry 4.0 technologies have the knowledge and skills to perform this role</td><td>[24]</td></tr><tr><td>can proactively plan for future occurrences because of the implemented Industry 4.0 technologies</td><td>[2]</td></tr><tr><td>has adapted the structure and layout throughout the entire manufacturing area to receive Industry 4.0 technologies</td><td>[23]</td></tr><tr><td>has high levels of standardization in processes and products, following norms and specifications</td><td>[2]</td></tr><tr><td>uses integrated systems throughout the manufacturing unit that allow the sharing of data information from the factory floor with the operational and executive levels</td><td>[9]</td></tr><tr><td>uses technologies such as Big Data Analytics, CPS, IoT, and Artificial Intelligence in all its manufacturing processes</td><td>[2, 10–12, 27]</td></tr><tr><td>has a management system for all logistical links, from supplier data, and inventory, to sales</td><td>[21]</td></tr><tr><td>has systems capable of accumulating knowledge and autonomously making decisions, performing analyzes of the results accumulated in the manufacturing operations</td><td>[22]</td></tr><tr><td>has systems capable of accumulating knowledge and making decisions in a semi-autonomous way (with human intervention), performing analyzes of the results accumulated in the manufacturing operations</td><td>[22]</td></tr></tbody></table>

Source: Prepared by the authors
# 4 Results and Discussion

Preliminary to the questionnaire, on adherence to perspective two of the model by Henderson and Venkatraman [5], questions were asked that helped to typify the respondent company, and the compilation of the eleven companies is presented in Table 2.

<table><caption>**Table 2.** Typification of respondent companies</caption><thead><tr><td></td><td>Type of industry</td><td>Range of number of employees</td><td>Annual billing range</td></tr></thead><tbody><tr><td>Company 1</td><td>Metallurgical</td><td>10 to 49</td><td>Between BRL 360 thousand and BRL 4.8 million</td></tr><tr><td>Company 2</td><td>Electronics</td><td>50 to 249</td><td>Greater than BRL 300 million</td></tr><tr><td>Company 3</td><td>Cosmetics</td><td>250 or more</td><td>Greater than BRL 300 million</td></tr><tr><td>Company 4</td><td>Chemistry</td><td>0 to 9</td><td>Between BRL 360 thousand and BRL 4.8 million</td></tr><tr><td>Company 5</td><td>Metallurgical</td><td>50 to 249</td><td>Between BRL 360 thousand and BRL 4.8 million</td></tr><tr><td>Company 6</td><td>Metallurgical</td><td>250 or more</td><td>Greater than BRL 300 million</td></tr><tr><td>Company 7</td><td>Steel Mill</td><td>250 or more</td><td>Greater than BRL 300 million</td></tr><tr><td>Company 8</td><td>Mining</td><td>250 or more</td><td>Greater than BRL 300 million</td></tr><tr><td>Company 9</td><td>Metallurgical</td><td>250 or more</td><td>Greater than BRL 300 million</td></tr><tr><td>Company 10</td><td>Cosmetic</td><td>250 or more</td><td>Greater than BRL 300 million</td></tr><tr><td>Company 11</td><td>Automobile</td><td>250 or more</td><td>Greater than BRL 300 million</td></tr></tbody></table>

Source: Prepared by the authors

As shown in Table 2, the number of employees combined with the billing classify the companies surveyed can be considered as large. There is a variety of areas of activity, and in the metallurgical segment, there are four companies, followed by the cosmetics area with two companies interviewed.

The level of training and experience of the respondents were also mapped. The minimum training is higher education, with more than 4 years in the company, all of them occupying a management position in the companies they operate.

Table 3 shows the data collected from the fourteen assertions, the sum was tabulated and calculated for each respondent company, considering that the higher the total value, with seventy being the maximum, the greater the company's adherence to perspective two of the strategic alignment model of Henderson and Venkatraman [5].

Company 7 was the only one that the respondent scored with the highest value on the scale for all assertions, something expected of the high level of investment in recent years in innovative technologies of the company in the steel segment, mainly aimed at improving the ability to collect and transfer data in your processes. Company 8 had the lowest average, although, with high dispersion, the result is linked to the
<table><caption>**Table 3.** Sum of points by company where 70 is the maximum value</caption><thead><tr><th>Company</th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>7</th><th>8</th><th>9</th><th>10</th><th>11</th></tr></thead><tbody><tr><th>Sum</th><td>44</td><td>51</td><td>42</td><td>42</td><td>42</td><td>66</td><td>70</td><td>33</td><td>42</td><td>59</td><td>58</td></tr></tbody></table>

Source: Prepared by the authors

company's operating segment (mining) in which investments in I4.0 technologies do not confirm perspective two of strategic alignment as dominant, because there are occasional and dispersed applications of new technologies in their manufacturing processes. The other companies, to a lesser and greater degree, corroborate the understanding that the strategic alignment has been guided by the use of ITDC enablers of I4.0 to improve production processes, as recommended by the strategic alignment model of Henderson and Venkatrama [5].

# 5 Conclusion

The emerging technologies of I4.0 have contributed companies to be more agile in their production processes. Agility is achieved by collecting, transforming and transmitting data more quickly to decision makers. However, the mere availability of new technologies does not mean a return of superior results if there is not an adequate strategic alignment.

In the eleven companies studied, it was possible to identify the predominant adherence to perspective technological transformation, in which the technologies structured in I4.0 aim to support the organizational strategy. On the one hand, it means obtaining results in a pragmatic with improved levels of information, but the competitive advantage that comes from this perspective is temporary, as it is easily imitated by other competitors. Organizations interested in achieving perennial competitive results should align efforts in the application of I4.0 technologies to offer differentiated, customized products and services focused on servitization, as recommended by perspectives three and four of the strategic alignment model.

Although new digital transformation technologies can be applied to many manufacturing processes, their access is still restricted to large companies due to the high investment required. This characteristic was identified in the eleven companies studied when analyzing their size and revenue.

Analyzing how obtaining new technologies incorporated into I4.0 is converting into benefits in the strategic field plays an important role, as argued by Karpovsky [14]. Supporting a proposition to be tested in future works, named here as P1.

P1. Organizations that apply the new I4.0 technologies adhering to their business strategies can obtain a higher return on investment.

Although there is no consolidated model to typify the companies that align the new technologies of the I4.0 to their strategies. The model by Henderson and Venkatraman [5], published in 1993, proved to be adequate to characterize the companies studied from the perspective of technological transformation, but there is another gap for study, declared in the proposition to be tested in future works regarding the applicability of the other perspectives.
P2. The application and use of new technologies incorporated in I4.0 can characterize organizations in any of the four perspectives of strategic alignment, depending on the way they were implemented.

The presented propositions have the limitation of the few respondents, opening opportunities for future research, in which the methodological procedures could be either case studies or surveys.

As in any research, there are limitations inherent to the methodology, such as considering a restricted group of companies, and not being possible to generalize the findings, which opens the opportunity for further research with a larger sample base.

This study was partially financed by the Coordination for the Improvement of Higher Education Personnel - Brazil (CAPES) – Financial Code 001.

## References

1. Tyas, W.P., Hutama, J.K.P.: Strategy and innovation of home based enterprises for local development in the 4.0 era: a bibliographic study. In: IOP Conference Series Earth Environment Science, vol. 673, no. 1, pp. 0–14 (2021)

2. Kamble, S.S., et al.: Smart manufacturing process and system automation—a critical review of the standards and envisioned scenarios. J. Manuf. Syst. 56(4), 312–325 (2020)

3. Cordeiro, G.A., Ordóñez, R.E.C., Ferro, R.: Theoretical proposal of steps for the implementation of the Industry 4.0 concept. Brazilian J. Oper. Prod. Manag. 16(2), 166–179 (2019)

4. Hitt, M.A., Ireland, R.D., Hoskisson, R.E.: Administração Estratégica. Cengage Learning Edições (2008)

5. Henderson, J.C., Venkatraman, H.: Strategic alignment: leveraging information technology for transforming organizations. IBM Syst. J. 38(2.3), 472–484 (1993)

6. Fernandes, A.A., Abreu, V.F.: implantando a governança de TI: da estratégia à Gestão dos Processos e Serviços. BRASPORT, Rio de Janeiro (2014)

7. Gadekar, R., Sarkar, B., Gadekar, A.: Assessment of key success factors for Industry 4.0 implementation in manufacturing industry using EDAS. Int. J. Innov. Eng. Sci. 6(1), 1–11 (2021)

8. Nosalska, K., Piątek, Z.M., Mazurek, G., Rzadca, R.: Industry 4.0: coherent definition framework with technological and organizational interdependencies. J. Manuf. Technol. Manag. 31(5), 837–862 (2019)

9. Lee, C.K.M., Lin, B.B., Ng, K.K.H., Lv, Y.Q., Tai, W.C.: Smart robotic mobile fulfillment system with dynamic conflict-free strategies considering cyber-physical integration. Adv. Eng. Inf. 42, 100998 (2019)

10. Culot, G., Orzes, G., Sartor, M., Nassimbeni, G.: The future of manufacturing: a delphi-based scenario analysis on Industry 4.0. Technol. Forecast. Soc. Change 157, 120092 (2020)

11. El Zant, C., Benfriha, K., Loubère, S., Ouassat, A., Adjoul, O.: A design methodology for modular processes orchestration. CIRP J. Manuf. Sci. Technol. 35, 106–117 (2021)

12. Zheng, T., Ardolino, M., Bacchetti, A., Perona, M.: The applications of Industry 4.0 technologies in manufacturing context: a systematic literature review. Int. J. Prod. Res. 59(6), 1922–1954 (2021)

13. Mitropoulos, S.: An integrated model for formulation, alignment, execution and evaluation of business and IT strategies. Int. J. Bus. Syst. Res. 15(1), 90–111 (2021)

14. Karpovsky, A., Galliers, R.D.: Aligning in practice: from current cases to a new agenda. J. Inf. Technol. 30(2), 136–160 (2015)
15. Ullah, A., Lai, R.: A systematic review of business and information technology alignment. ACM Trans. Manag. Inf. Syst. 4(1), 1–30 (2013)

16. Ghobakhloo, M., Fathi, M.: Corporate survival in Industry 4.0 era: the enabling role of lean-digitized manufacturing. J. Manuf. Technol. Manag. 31(1), 1–30 (2020). https://doi.org/10.1108/JMTM-11-2018-0417

17. Gajsek, B., Marolt, J., Rupnik, B., Lerher, T., Sternad, M.: Using maturity model and discrete-event simulation for Industry 4.0 implementation. Int. J. Simul. Model. 18(3), 488–499 (2019)

18. Lang, S., Reggelin, T., Jobran, M., Hofmann, W.: Towards a modular, decentralized and digital Industry 4.0 learning factory, pp. 123–128 (2018)

19. Ribeiro, P.P., de M. Lopes, C., Correia, A.M.: Avaliação da gestão de estoque em uma microempresa de autopeças utilizando a curva abc como ferramenta de apoio. Rev. CEREUS 12(2), 130–145 (2020)

20. Hoffmann Souza, M.L., da Costa, C.A., de Oliveira Ramos, G., da Rosa Righi, R.: A survey on decision-making based on system reliability in the context of Industry 4.0. J. Manuf. Syst. 56, 133–156 (2020)

21. Belinski, R., Peixe, A.M.M., Frederico, G.F., Garza-Reyes, J.A.: Organizational learning and Industry 4.0: findings from a systematic literature review and research agenda. Benchmarking 27(8), 2435–2457 (2020)

22. Kamble, S.S., Gunasekaran, A., Sharma, R.: Analysis of the driving and dependence power of barriers to adopt industry 4.0 in Indian manufacturing industry. Comput. Ind. 101, 107–119 (2018)

23. Espinola, A.J.C., da Sí, Diniz, R., de Oliveira, G.F.: Níveis De Ocupação No Brasil Com a Indústria 4.0: Desafio Ou Caos? Rev. FATEC SEBRAE EM DEBATE Gestão, Tecnol. e Negócios 07(11), 41 (2020)

24. Pacchini, A.P.T., Lucato, W.C., Facchini, F., Mummolo, G.: The degree of readiness for the implementation of Industry 4.0. Comput. Ind. 113, 103125 (2019)

25. Stebbins, R.A.: Exploratory Research in the Social Sciences: Qualitative Reserach Methods Series, vol. 48. Sage University Paper, Thousand Oaks (2001)

26. Pereira, G.B., Nogueira, G.C., Oliveira, G.F.: Maturity in Industry 4.0: study in eleven companies located in greater São (2021)

27. Buchi, G., Cugno, M., Castagnoli, R.: Smart factory performance and Industry 4.0. Technol. Forecast. Soc. Change 150, 119790 (2020)