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Analytics for All - How Analytics can Solve Organizational and Individual Problems Simultaneously: A Case from the Global Learning Industry*

ET Cases - GSMC, 12 pages
AUTHOR(S) : Kushal Saha & Anjan Ghosh - IIM Calcutta, Kakoli Sen - Independent Consultant, Pallavi Dhyani - Accenture

Case Preview

Analytics for All – How Analytics can Solve Organizational and Individual Problems Simultaneously: A Case from the Global Learning Industry


It was a pleasant early winter evening during the year 2013. Kajol Goala (Goala) was enjoying his cup of late-evening tea sitting on his favourite beat-up chair on the balcony of his cosy apartment at Chittaranjan Park, Delhi, staring at the starry night sky. His mind gradually wandered into the events that had taken place at his office that day. The last few months had been uncharacteristically hectic, even for a seasoned consultant like him. He couldn’t help but think about the situation in his office which had been a roller coaster ride. All the efforts he and his team had been putting in the recent past ultimately bore result. ‘Proactive Student Retention Solution’, a new offering was officially added to the existing set of knowledge and learning-based services offered by ‘Integrated Knowledge Solutions’ (IKS, name changed to maintain confidentiality) the organization Goala has been working for the last 10 years. This recent addition to the bouquet of services already being offered by IKS was his brainchild. It also gave him a feeling of immense satisfaction as he and his team had been instrumental in conceptualization and operationalization of the
whole process.

Goala joined IKS as a Management Trainee in 2003, just after completing his master’s degree in Business Management from one of premier management institute in northern India. IKS specializes in extending services related to learning, strategy and development to its clients from both corporate and academic world. In his latest assignment Goala was working as a Senior Consultant with one of their biggest divisions – ‘Integrated Services’. The services offered by ‘Integrated Services’ ranged from learning content development, management, delivery of third party learning programs, etc., to the implementation and management of learning management technologies. Through these services, IKS allowed the clients to outsource all the supporting and peripheral activities and focus instead on their core competencies..........

The Opportunity for Analytics

During one such trip to the US in 2012, IKS’s sales team setup a meeting with the program management office of ‘The Top University’ (TTU, name changed to maintain confidentiality). At that time, TTU was one of the largest providers of post-secondary education with locations across US and Canada. Goala as part of the team, visited TTU and presented a sales pitch before the program management team of TTU to give them an overview of the standard set of services provided by IKS. At the end of the meeting, the Program Director from TTU communicated to the IKS team that at that point in time they were unable to identify any area in their operational landscape where IKS could chip in with any of their standard services..............

Stage I: The Predictive Approach using Statistical Analysis

Goala, after returning to Delhi, quickly put together a team who had an engineering or mathematics background to analyze the data. Their idea was not to mining the data but to prepare the ground and find ways so the processing of the data happened towards a plausible direction. The team decided first to convert the raw physical data to digital ones. A vendor specialized in data transcription, agreed to do the job. Soon the data was converted and delivered to Goala in a spreadsheet. The team now met to decide on the next steps.............

Stage II: Factors for Students Dropout

With decade of experience in the learning industry, Goala knew very well that just detecting the students with high chances of leaving does not serve any purpose unless appropriate interventions are undertaken to get connected and work with such students so that they don’t leave the program. He knew that the analytic indicators helped to focus on students to see their probability of leaving the program. Such detection gets complemented through the understanding of the key factors that caused the students to dropout. Goala thus, undertook another initiative to find the key reasons for students leaving academic programs. The statistically significant dependent variables, as found during the statistical analysis phase, now guided him to detect the under-surface factors for student dropout..............

Stage III: Pro-active Measurements to Address Student Dropout

Being a veteran of solution architect in the learning industry, Goala could sense that the client could only be benefited when a student with high probability of dropout would be supported by the school in addressing factors leading the student’s dropout. Thus, the need was to create a student support system that could arrest dropout. With that thought in mind, Goala started designing a centralized support desk. His design reflected an integrated and hosted technology and service solution where the IT system would fetch the real-time data from TTU’s server, run the statistical analysis and detect the students at risk.............

Project Success and Beyond

Post the project management challenges of rolling out a new initiative, the solution met with considerable success. In the first three months of the project going live (only with the analytics part), TTU could detect 80% of the potential dropout candidates, before the dropouts actually took place. In the next phase, the interventions solutions were rolled out. Year-end data suggested a steady decrease in the dropout in comparison to the previous year’s dropout figures. The success of the initiative not only helped IKS to secure long term contract with TTU, it also made them deciding on a sew service offering “Proactive Student Retention Services” with Goala as its head.............

Assignment Questions

I. What are the limitations of the reactive approach and the benefits of a proactive approach?
II. What additional determinants of the problem of student attrition could IKS unearth using the proactive approach?
III. ...............


Exhibit I: Process Flow for Data Analysis Using Regression

Exhibit II: Output of Data Analysis Using Regression

Exhibit III: Histogram Created on Test Data

Exhibit IV: Workflow for Statistical Analysis

Exhibit V: Validity Test Results

Exhibit VI: Factors Influencing Student Dropouts


Annexure I: Introduction to Logistic Regression (I)

Annexure II: Introduction to Logistic Regression (II)

Teaching Note Preview

Analytics for All – How Analytics can Solve Organizational and Individual Problems Simultaneously: A Case from the Global Learning Industry



The theme of the case is to sensitize the participants on the importance of understanding of analytics for practicing managers. The case – developed on  primary data collected from one of the largest post-secondary education provider in North American region – revolves around a real-life problem faced by the educational institute mentioned above. The case aims to highlight the criticality of understanding about the power of data analytics in solving various problems an organization faces on regular basis.

The case elaborates upon the problem of involuntary student withdrawals leading to substantial student attrition that was plaguing the organization and how they tried to bring in certain ‘reactive’ interventions to arrest the deteriorating student retention rates. But the interventions did not succeed in attaining the intended set of results. The case then narrates how external help was sought and, using the predictive power of statistical techniques, reactive interventions were turned into proactive ones. This proactive approach was ultimately successful in putting a check on the increasing student attrition ratios.

Through this case study, the audience/students would recognize that it was not the character of interventions that made them successful in the latter case, but merely the awareness about the potential analytical techniques offer helped in making the organization’s approach proactive from reactive and that’s what ultimately worked for it. It presents a scenario where a structured, not-so-complex statistical technique helped the organization tackle a challenge it has been suffering for quite some time. The case can also be used to refute popular misconceptions like ‘only big companies need data analytics’ or ‘value realization of analytics comes with a big price tag’. The organization considered here is not very big in size or scope; neither the capabilities are costly. Moreover, it is an academic institution. In this particular case the effective intervention was designed by an external consultant. But had the people in charge of the program management office of the academic institution had a rough idea about the potential that statistical/analytical procedures offer, they themselves could have identified what was wrong with their earlier approach and accordingly had taken corrective steps.

Teaching Objective and Teaching Framework

The objective of the case is to help the participants to develop a basic understanding regarding data analytics – how and when analytical tools/processes can add value to an organization etc. – and at the same time refute some basic misconceptions related to application of analytical tools. The case, through its narratives and subsequent discussions systematically dwells upon the above mentioned concepts.

Case Positioning and Setting

--Target Audience

  • • Introductory undergraduate
  • • Advanced undergraduate
  • • Graduate (master’s) class
  • • Executive programme


--Functional Area

  • • Information System (Analytics)


Discussion Questions

  • I. What are the limitations of the reactive approach and the benefits of a proactive approach?
  • II. What additional determinants of the problem of student attrition could IKS unearth using the proactive approach?
  • III. Once the determinants have been identified, how could TTU, in collaboration with IKS, restructure its mechanism of intervention?
  • IV. ..................



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Using primary data from a leading educational institution from the US, the case aims to refute popular misconceptions like 'only big companies need data analytics' or 'value realization of analytics comes with a big price tag'. The organization considered here is not a 'big' corporate player; neither the capabilities developed are costly. The case also showcases how analytics can be used to solve organizational and individual problems simultaneously. For that an understanding of analytics is required for the practicing managers.

The case deals with the issue of student retention which has always been a significant challenge in the context of higher education. Students deciding not to persist with the programs they have enrolled into not only affect their careers, but also the concerned institutions. From a student's perspective, involuntary withdrawal prevents him from realizing his career objectives and is likely to inflict an adverse long-term economic impact upon his life. The institution, on the other hand, stands to get affected in multiple ways. Attrition results in a sheer wastage of institutional resources. Apart from direct financial implications, institutions also suffer from significant reputation losses. Instances of drop-outs would lead them to incur higher cost for attracting next batch of in-coming students.

It then becomes imperative for such institutions to implement appropriate measures to try to retain the students. But success of any such intervention is conditional upon their ability to identify, at regular intervals, the students at risk of dropping out. The case talks about how, utilizing the power of analytics, such a risk-profiling capability could be developed to help the administration categorize the students on the basis of their probability of withdrawing themselves from the respective programs. Appropriate recommendations are then made regarding the intervention mechanisms to be used to retain the students in their programs of study.

Pedagogical Objectives

The objective of this teaching case is to introduce analytics to the students and practitioners of business management. The case shows how the basic understanding of analytics can push practitioners to treat available data and information in a strategic way to unlock data possibilities in enhancing performance, solving business problems and even developing new solutions and additional revenue stream therein. In a way, it provides insights into the core attributes of analytics and its relationship with organizational strategy.

Case Positioning and Setting

Functional areas where the case can be used are:

  • Introduction to Business Analytics (Management Information System)
  • Resource and Capabilities (Strategy)
  • Learning Strategy and Development (OD)
  • New initiatives (Entrepreneurship and Innovation)

* GSMC 2016, IIM Raipur

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