Jain University’s Business School and Its Problems

Business Issues

Jain University’s business school currently faces several problems which complicate its functioning as a respectable educational institution. The first issue stems from the lack of the graduates’ ability to find employment. According to the school’s dean’s statements, there have been reports of many alumni failing to find a placement. This is a critical issue because the quality of an educational institution is assessed based on the success of its students after their graduation. The fewer of them are employable; the greater is the damage to the business school’s reputation. Therefore, the business school faces negative publicity, which is caused by the poor performance of its graduates.

The second issue is the status of the establishment. The business school exists within the framework of Jain University, which is a deemed-to-be-university. Although it has grown substantially over the years, it remains an institution with a weaker accreditation than fully-fledged universities. The reason why it constitutes a problem for the business school lies in the list of governmentally approved B-schools with MBA programs. This list did not encompass deemed-to-be-universities and private universities, which is true for Jain University in both cases. Within the context of an increasing number of management institutes, the value of existing business schools decreases.

The third problem is the deficiencies of the business school admission policy. The reports concerning the placement of students revealed that twenty percent of graduates did not receive placement in 2013. The underlying explanation was that these students did not perform with enough efficiency. The placement team acknowledged the inability to find employment for them. However, the team attributes this result to the failings of the 2011 admission campaign, which allowed these applicants to enter, even though, in reality, they did not satisfy the goal of the admission campaign. As a result, the difficulties in running the business school start with the admission of new students.

Analytics Techniques

Business analytics presupposes different sources of data. Descriptive techniques are better at ascertaining the current state of affairs within the organization, while predictive analysis will help make future decisions. The business school’s dean should tackle the first issue with descriptive analytics. The quality of education is a difficult parameter to measure. Nevertheless, it is possible to review the existing disciplines in relation to the companies’ requirements (Clarke, 2017). This technique will allow the dean to identify what disciplines do not acquaint students with business specifics and prevent them from getting employed. It will also provide insight into the usefulness of having such disciplines in the curricula.

The status problem of the university cannot be solved by the dean. However, the real reason why the governmental list of the approved business school mattered in the first place lies in the abundance of institutions seemingly offering the same services. This creates the problem of excess supply on the market. Therefore, the dean can order another descriptive analysis of the business schools’ offers, including his own one. The resulting data should indicate what makes Jain University’s business school unique. Subsequently, the admission campaign ought to accentuate the specific features which distinguish this educational establishment from others.

Using predictive analytics can help resolve the issue of poor admission criteria. The results of 2011 admission should be compared with each consecutive year. It is highly unlikely that the percentage of graduates who ended up without placement stayed the same. It is possible to predict students’ future academic performance based on the completion of homework assignments (Elbadrawy et al., 2016). Therefore, drawing a linear chart will yield either a progression or a regression. In either case, the dean will be able able to make a conclusion about what way to change the admission rules.

Variables

The first analysis will involve a bar chart with several variables. As the purpose is to identify what disciplines are the most effective in preparing students for corporate work, it is reasonable to use their criteria as the variables. For instance, some common business competencies include strategic leadership, conflict management, communication skills, leadership mindset, and emotional intelligence (Shaikh, Bisschoff, and Botha, 2018). They can be used in evaluating how effective the disciplines are at cultivating these abilities. The least useful ones will likely be omitted or restructured.

The second technique would necessitate the use of two comparative histograms. One of them would incorporate the data on the most common offers of other business schools. Another one would encompass the exact same parameters for Jain University’s business school. Depending on the results of the descriptive analysis of the competitors’ offers, variables may include campus slots, work placement, state approval, and partner companies (Marimon et al., 2019). The ultimate goal is to get enough data to see what would draw attention to Jain University’s business school.

The third chart will likely be a linear regression because of the falling number of graduates who get the placement. There are several factors that may be critical in the graduates’ employability (Elbadrawy et al., 2016). The variable will be students’ grades, which will show whether academic performance is essential in acquiring the placement. Alternatively, admission results can be used as the variables, which might hint at the problem with the curricula. Another variable could be primary education, which will give the admission team a clue about which regions not to trust. Overall, in each case, the team will get insight into the problems the admission campaign creates.

Ethical Issues

Naturally, viewing people exclusively through the lens of numbers and charts will produce some ethical implications. The first issue is attributing the success of education to the fact of placement or employment. It should be noted that acquiring a job is not an end in itself. The purpose of education is to teach the students to use the tools to learn complex spheres of knowledge on their own (Clarke, 2017). Changing the curricula to fit the employment criterion will rob students of educational opportunities. A possible solution is to change the metrics, shifting from employment-centered education to a knowledge-centered one.

The second issue is the use of other educational establishments as the arguments for choosing Jain University’s business school. Not only does it involve institutional prying, but it also compromises Jain University as the institute, which is not able to promote itself without criticizing others. Alternative marketing would focus on the positive sides of the business school, which are not often seen in other cases.

Finally, restricting the admission of a certain group of people can be seen as discriminatory. For instance, in case the regression analysis shows that applicants from a certain region perform poorly and do not get placement, the team will be tempted to limit entry from this area. Such decisions are fraught with biases, which will negatively impact the university’s reputation (Elbadrawy, A. et al., 2016). As in the first case, refraining from overemphasizing employment will help avoid prejudice.

References

Clarke, M. (2017) ‘Building employability through graduate development programmes’, Personnel Review, 46(4), pp. 792-808.

Elbadrawy, A. et al. (2016). ‘Predicting student performance using personalized analytics’, Computer, 49(4), pp. 61-69.

Marimon, F., et al. (2019). UnivQual: a holistic scale to assess student perceptions of service quality at universities. Total Quality Management & Business Excellence, 30(1-2), pp. 184-200.

Shaikh, A., Bisschoff, C.A. and Botha, C.J., (2018). ‘Measuring management and leadership competencies of business school educated managers in South Africa’. Journal of Business and Retail Management Research, 13(2). pp. 152-166.

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