Everest - a Simulator

Introduction

In an increasingly more complex context of the managerial workplace, simulations are often used to emulate real life situations. It is an imitation of a real-world process that aims to capacitate managers with leadership and decision-making abilities.

Everest is a simulator designed by Harvard Business School for students to experience organisational challenges. Students are placed in groups of 5-7 with unique roles to undertake two virtual climbs on Mount Everest, with points being awarded for completing personal and team objectives. However, the collision of personal and team objectives creates conflicts which requires team resolution, similar to a realistic, managerial workplace. A laissez faire leadership and intuitive, non-linear decision-making style was employed in the first simulation, whereas in the second simulation the assigned leader of Ellery’s team stepped up to take a more democratic leadership role and influenced decision-making to improve the result.

Differing processes and results of the 2 simulations allows for reflections which are beneficial to the student’s understanding of leadership and decision-making in a managerial environment. This report will provide an overview of the Everest experience, including an examination of issues confronted, critical analysis of the simulation and recommendations for the future, weaved with concepts taught in MGMT1001.

Section 1: Issues Encountered During Everest

Although students are educated through the MGMT1001 course regarding decision-making and the use of leadership, it is not until experiencing simulations that students realised the difficultly and issues in applying theory to practical situations.

The initial simulation was characterised by a laissez-faire and participative leadership style, which prompted an individual-oriented progression (Doucet, Poitras & Chenevert, 2009) rather than team orientation. As health situations deteriorated e.g the environmentalist’s asthma, the lack of team coordination magnified the challenges, leading to the erroneous separation of members. Despite the formally assigned role of leader to Stanley, his lack of directive leadership in an ambiguous situation made it difficult for collaboration. The issue is that during an ambiguous situation where members confront unstructured problems, the lack of leadership makes it increasingly harder for the team to unite in an attempt to maximise goals (Malik 2012). Furthermore, Stanley’s one size fits all leadership style in the first simulation was insensitive to individual needs and characteristics (Malik, 2013).

Poor decision making is another area that ramified an unsuccessful simulation. The team’s intuitive and non-linear propensities made it increasingly difficult to satisfy all goals in a deteriorating progression. Especially in a circumstance where unstructured problems are confronted, as in simulation 1, intuitive and non-linear decisions became issues as personal experience often don’t suffice as resolution (Matzlerz et al, 2007). The group also tended to operate under assumptions of bounded rationality, that is choosing solutions which satisfice rather than maximise. For example, the environmentalist chose to stay at camp 2 for 2 consecutive days to ensure his safety, rather than weighing the significance of group and other personal objectives to determine whether moving on was worth the risk.

Ultimately, intuitive, non-linear propensities and bounded rationality as well as a laissez-faire, supportive leadership style did not respond well against unstructured problems in the first simulation, as reflected by a low team mark of 39%. However, the identification and reflection upon these issues promoted improvements in the latter simulation.

Section 2: Analysis

a) Leadership

In a managerial team, leadership plays a pivotal role in driving success (Doucet, Poitras & Chenevert, 2009), this is exemplified by the correlative relationship between improving leadership and better simulation marks.

The path-goal theory states that it is the leader’s role to assist followers in attaining personal and organisational goals (Malik, 2012). In the first simulation, the assigned, formal leader of Ellery’s team - Stanley, adopted a participative approach in which he consulted the group’s suggestions prior to making decisions. However, participative leadership is more effective when subordinates demand autonomy and are capable of formulating decisions unilaterally (Malik, 2012). Given a situation where individual goals are defined but team goals are ambiguous, participative leadership was insufficient in maximising team objectives (Malik, 2012). Ellery’s team needed a leader who would consider both personal and team goals, and subsequently provide directions as to what actions to pursue. Consequently, the team was separated as members were individually oriented, leading to a low team score of 39% in the first simulation. Upon reflection, Stanley confronted this issue by becoming a directive leader. This provided specified procedures and actions (Fulk & Wendler, 1982), e.g. by advising and occasionally deciding whether members shall stay or move on to the next camp. The shift in leadership style facilitated team collaboration and thus improved to a mark of 54% in the 2nd simulation.

Path-goal theory proposes 2 situational or contingency variables that moderate leadership behaviour outcome; external or environmental factors and personal characteristics of followers (Teng, 2004). The environment of the virtual simulation could be described as somewhat ambiguous, as weather and health conditions are generally hard to predict throughout the climb. The ambivalence and resulting inertia in the first simulation lead to a frustrating and time-consuming process as members are often indecisive on whether to proceed to the next camp. Consequently, Stanley’s shift from a participative to a directive approach was suitable, as directive leadership leads to greater satisfaction amidst ambiguity (Malik, 2013). Empirically, Stanley’s leadership behaviour became more flexible in the second simulation. He demonstrated a participative leadership style to all members in the first simulation, but vacillated between directive and supportive leadership to respond to different members in the latter. For example, he played a more supportive role to the environmentalist, Matthew and medic Sarith but was directive to the marathon runner Ishaan. Stanley identified that Ishaan, as an Asian, overseas student with a high context culture, he is likely to have an external locus of control (Hill et al., 2017) and thus perform better under directive leadership (Malik, 2013). In contrast, Matthew and Sarith are Australians with internal locus of control who prefers greater autonomy (Malik, 2013). Stanley’s flexibility in response to the contingency variables is a perfect model for a path-goal leader, therefore lead the team to better results in the latter simulation.

Informal leadership is another factor which improved the team’s results, it refers to the ability of a person to influence others by means other than formal authority (Hills, 2014). Unlike Stanley who was formally assigned the leadership role, Ellery, the observer emerged as an informal leader in simulation 2 through referent power. His clear insights and outstanding communication skills are inherent to informal leaders (Hills, 2014). He acted as a trouble shooter and occasionally a conflict manager to reduce Stanley’s burden. In the first simulation, Ellery’s laissez-faire leadership style did not make him an obvious leader, but his transformation into a democratic leader in the 2nd simulation illuminated his informal leadership. His leadership traits e.g. honesty and self-confidence (Judge, 2002) encouraged the group to become more proactive and engaged. Ultimately, the emergence of an informal leader in the latter simulation contributed to a better result.

b) Decision-Making

The differing results between simulations reflects that changes in decision making impacts on team objectives. Woolf.K & Dacre. J’s research, although conducted on a medical field supports with relevant evidence that biases in decision-making can affect outcomes (2015).

Ellery’s team acted intuitively and in a non-linear fashion during the first simulation. Intuition is derived from personal experience and by recognising patterns (Matzleret et al, 2007). But because problems were unstructured and members have little knowledge with extremities (i.e climbing mount Everest and confronting unprecedented weather conditions), pure intuition and a non-linear approach was inappropriate. As the environmentalist, my poor individual performance of 43% also reflected that as a student, insufficient practical experience can impede on intuitive decision-making. Some of these problems transformed into structured problems that could be resolved by programmed decisions in the latter simulation, e.g. members decided without doubt to move on to camp 2 from experience that health conditions are generally not a concern until camp 3. Despite this simplification, Ellery’s team began to employ more external sources and secondary information by analysing and sharing the