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 opens with the current crisis for Amazon because of its alleged use of sensitive and confidential business information from third-party sellers on its platform to develop competing products under Amazon's private label (PL) brands, a practice at odds with the company's stated policy. Such allegations not only hurt Amazon's reputation as one of the largest e-tailers but also brought to light a larger debate about the right way to launch PL brands. Although Amazon claims to have prohibited its employees from using nonpublic, seller-specific data, it agrees to have used aggregate customer data like other brick-and-mortar stores to improve customer experience. However, the third- party sellers feel that Amazon's unfair practice of using their private information has hurt them, decreasing their return on investment and compromising their product innovations. Russell Grandinetti, who currently runs Amazon's international consumer business, faces the following dilemma: Should Amazon continue its PL brands? Because PL brands are important for Amazon's business, Grandinetti must find ways to build synergy with third-party retailers while developing Amazon's PL brands. Grandinetti needs to address these concerns in the next shareholder's meeting.