Special trains are unscheduled trains run to meet the unexpected surge in demand during holidays and festive seasons, which is generally difficult to predict. Special trains were therefore allocated at SCR using rule-based processes, resulting in suboptimal revenues and occupancy rates. This case presents a data-driven approach to schedule special trains based on passenger waitlist data and application of statistical techniques.
During the summer of 2021, Sumana G., Chief Technology Officer of South Central Railway, was reviewing the annual productivity reports of field employees. This was an annual exercise that was crucial to central planning as it helped identify potential weaknesses and possibilities for improvement. Sumana knew that evaluating the productivity of store personnel would be the most challenging task because Indian Railways (IR) managed over 280,000 items stocked in 215 depots across the country. While reviewing the time sheets, Sumana quickly realized that field officers were spending a significant time amount of time on materials purchase, especially items purchased locally by field offices. On further inquiry, field officers revealed that retrieving data from the stores database based on item descriptions posed considerable challenges, and in most cases, the search results were not very useful. Sumana was quick to realize that an artificial intelligence (AI)-based search engine could solve this problem.
The case is designed to be used in courses on Nonprofit Operations Management, Data Analytics, Six Sigma, and Business Process Excellence/Improvement in MBA or Executive MBA programs. It is suitable for teaching students about the common problem of lower rates of volunteerism in nonprofit organizations. Further, the case study helps present the importance and application of inferential statistics (data analytics) to identify the impact of various factors on the problem (effect). The case is set in early 2021 when Shefali Sharma, the Strategy and Learning Manager with Teach For India (TFI), faced a few challenging questions from a professor at the Indian School of Business (ISB) during her presentation at an industry gathering in Hyderabad, India. Sharma was concerned about the low matriculation rate of TFI fellows, despite the rigorous recruitment, selection, and matriculation (RSM) process. A mere 50-60% matriculation rate was not a commensurate return for an investment of INR 6.5 million and the massive effort put into the RSM process. In 2017, Sharma organized focused informative and experiential events to motivate candidates to join the fellowship, but it was not very clear if these events impacted the TFI matriculation rate. After the industry gathering at ISB, Sharma followed up with the professor to seek his guidance in performing data analytics on the matriculation data. Sharma wondered if inferential data analysis could help her understand which demographic factors and events impact the matriculation rate.
The case goes on to describe the enormous challenges involved in building the 4.94 km long Bogibeel Bridge in the North Eastern Region (NER) of India. When it was finally commissioned in 2018, it was hailed as a marvel of engineering. With two rail lines and a two-lane road over it, the bridge spanned the mighty Brahmaputra river. The Bogibeel Bridge was India's longest and Asia's second-longest road and rail bridge with fully-welded bridge technology that met European codes and welding standards. The interstate connectivity provided by the bridge enabled important socio-economic developments in the NER that included improved logistics and transportation, the growth of medical and educational facilities, higher employment, and the rise of international trade and tourism. While the outcomes of the project were significant, the efforts that went into constructing the Bogibeel Bridge were equally so. This case study is designed to teach the importance of effective risk planning in project management. Further, the case introduces students to earned value analysis and project oversight in managing large projects. The case centers on Indian Railways' need to quickly discover why the Bogibeel project was not going according to plan. The case also serves as a resource to teach public operations management where the focus is on projects and operations that result in socio-economic outcomes.
The case describes a complex problem faced by the Indian Railways (IR), a more than 150-year-old public sector enterprise, in India. During the summer of 2009, IR was under tremendous public pressure to address the problems of its age-old toilet disposal system. The train toilet problem was complicated as it touched on all three dimensions of sustainability: social, environmental and economic. After examining a few technological options, Sanjeev Kishore, the Executive Director of Mechanical Engineering of the Ministry of Railways, had to decide whether to choose the most suitable solution from among the ready-to-use options available, or adopt a grounded approach to designing an alternative bio-toilets solution, using the Defense Research and Development Organization's (DRDO) inoculum bacteria. The search for a solution led to a collaboration between IR and DRDO that gave birth to a customized bio-toilet design. After successfully testing a prototype, the IR team implemented 245,775 bio-toilets in 68,694 coaches over a 10-year period. Students are encouraged to use their critical thinking and decision-making skills to address the business situation.
Set in 2016 in Hyderabad, India, the case follows Puvvala Yugandhar, Senior Vice President at Dr. Reddy's Laboratories (DRL), as he decides what to do about an underperforming production policy at their plants. Adopted a decade earlier, the policy, called Replenish to Consumption -Pooled (RTC-P), had not delivered the expected results. Specifically, the plants had been seeing an increase in production switchovers and creeping buffer levels for certain products, which had led to higher holding costs and lost sales for certain products. A senior consultant had suggested that DRL switch to a demand estimation-based policy called Replenish to Anticipation (RTA), which attempted to address the above concerns by segregating production capacity and updating buffer levels using demand estimates. However, Yugandhar, well aware of the challenges of changing production policies, wanted to explore a variant of RTC-P called Replenish to Consumption -Dedicated (RTC-D), which followed the same buffer update rules as RTC-P but maintained dedicated capacities for a subset of products.
Manish Bhardwaj, co-founder of Innovators in Health, is contemplating setting up Aahan, a community based tuberculosis (TB) control program in rural India. The case describes TB diagnosis and treatment in the public and private healthcare sectors in India and the attendant challenges. A number of candidate interventions aimed at improving the existing system of healthcare delivery are presented at the end of the case, each one of which could form the core of Aahan. Students are encouraged to use operations management principles to quantify the potential public health benefits and costs of these interventions and prioritize them accordingly. Key concepts include process flow mapping, flow balance, Little's Law and selection of appropriate process measures based on the strategic objective of the process.