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.
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.
The case describes operations of one of the early entrants in the Online Grocery Delivery industry in India, AtMyDoorsteps.com (AMD). After having run the company for three years, the founder, Sushant Junnarkar, is looking for big ticket funding. As he prepares his pitch, he wonders whether his business is lucrative enough for investors. What changes could be possibly made to the existing model to improve profitability for the company? He intends to revisit some of the strategic and tactical decisions that he had made at the time of inception of AMD. Junnarkar's final decision would determine the fate of his pitch to investors and subsequently the future sustainability of his venture.