Analyzing Harvard HRM Model in the Context of Future Industries

This report analyzes the Harvard HRM model in the context of the tourism industry, considering the impact of automation and future industries. The report begins by outlining the Harvard HRM model and its key components, including stakeholder interests, situational factors, and long-term consequences. It then examines how these factors are affected by the increasing use of robotics and other smart technologies in the tourism sector. The report argues that the situational factors are currently working against human workers, as machines are emerging as a more efficient and economic option. However, the report suggests that the Harvard HRM model can be reworked to address this issue. Specifically, it proposes introducing "high-order learning" as a necessary component at the entry-level and adapting "HRM Policy Choices" to serve the interests of all stakeholders. The report concludes that while machines may win the battle of efficiency, the Harvard HRM model can help ensure a continued human presence in the tourism industry through regulatory policies and educational reforms. It also references key sources to support the analysis.

Tangible services and “HRM model of Harvard” under the light of “future Industries”
A few years ago author Alec Ross, in his book “the industries of the future” mentioned that
Robotics and other smart gadgets will take over the tangible parts of the services and the roles of
human will confine to facilitate SOS situations (Ross, 2016). The tourism industry is known to
have a big multiplier where humans are involved in the food chain. As a worker serving in the
tourism industry, individuals are worried because Robots and kiosks are ready to replace them at
various levels. This situation can be analyzed with the help of Harvard model of HRM which is
mentioned below in Image 1. The situational factors present in this model can be amended to
facilitate a probable solution for the tourism industry where machines are eager to replace human
beings in the area of providing tangible services. Situational factors can serve as a key result area
because this is part where problem is occurring right now, in the future the ripple effects of this
area can touch other components of this model in the case of the tourism industry.

Image 1: Harvard Model of HRM Developed by Beer and his research mates in the year 1984,
image retrieved from https://www.researchgate.net/figure/The-Harvard-Model-Beer-et-al-1984-
Source-Beer-et-al-1984-Figure-2-1-p16_fig1_308816851
While considering the case of the Tourism industry and its fractions, the factors of “Stakeholder
interest”, Situational factors” and “Long term consequences” can be taken into an account.
Under the present model, the situational factors are working against humans, Robots and other
machines are emerging as a competitor in the labor market, they are presenting an efficient and
economic option (Bondarouk, 2016).
It is a positive sign for some of the stakeholders of the model, investors and management may
reap rich dividends because machines can bring down the cost of the operations, the third

fraction of the stakeholder consists of “Employee groups.” Ignorance of the interests of this
group can lead to long term consequences. It can bring down the multiplier of the tourism
industry and further create a vacuum in the economy.
Many experts believe that HRM model of Harvard may soon face redundancy because the
involvement of humans will minimize and machines barely make any mistake. However, this
situation can be controlled by revising the bracket of “HR outcomes” in the HRM model (Clause,
2019).
For instance in the case of tourism industry, a phase-out of the humans will take place, some
expert believe that regulatory authorities of the industry will force industry players to
accommodate humans amidst the machines or the robots to minimize the margin of errors and
probable mishap that can happen because of the limitations associated with the artificial
intelligence (Clause, 2019).
Harvard HRM model can be reworked for the “HR outcomes,” by introducing the need for “High
order learning” as a necessary component at the entry-level. The theories of management and
social engineering tell us that Education follows the demands generated for “employability
skills.” HRM model of Harvard” can generate the demand for “high order learning at the level of
the “situational factors”. “ HRM Policy Choices” can be reworked in accordance with the new
situations of the market where the interests of all the three stakeholders can be served in an
optimum fashion (Bondarouk, 2016).
Under the present conditions, machines of the future are going to win the battle of “survival of
the fittest.” It is a mathematical certainty because humans cannot match the accuracy and
productivity of the machines. Established models like Harvard HRM has the potential to find an

amicable solution by mitigating this impact, the policymakers at the summit level can come up
with regulations to ensure human presence in mechanical assembly lines in sectors like tourism
where humans were enjoying dominance because of the tangible nature of the job. Harvard HRM
model can be reworked with an intention to create a new pipeline for “HOTS” skills based on the
Taxonomy models and education system at the bottom line can amend its methods to increase
the employability of the individuals during the phase of education.

References
Bondarouk, T. (2016). Conceptualizing the future of HRM and technology research.
International Journal of Human Resource Management,
https://www.tandfonline.com/doi/full/10.1080/09585192.2016.1232296.
Clause, L. (2019). HR disruption—Time already to reinvent talent management. Science Direct,
https://www.sciencedirect.com/science/article/pii/S2340943619302129.
Ross, A. (2016). The Industries of the Future. New York: Simone & Schuster.