In January 2020, Ashwani Gupta took over as COO at Nissan Motor Corporation, and several weeks later, the COVID-19 pandemic began. Nissan's Business Continuity Plan (BCP) had been key to the resilience of Nissan's supply chain. It had enabled Nissan to recover from past supply chain disruptions, mainly natural disasters, sooner than its competitors. This case describes the BCP, within the context of Nissan's production methods, organizational principles and current financial position. It relates how Gupta managed the rapidly-evolving restrictions that the coronavirus pandemic required as it spread from China to other countries where Nissan's assembly plants and suppliers were located. Based on his experience with the COVID-19 pandemic, Gupta considers how to improve the BCP. This case also covers a specific situation in India, where Nissan had to quickly find an alternate supplier for a unit of dashboard gauges. The team in India developed four options that can be evaluated by students.

Pradeep Gupta founded Axis My India (AMI) as a printing and publishing company in 1998. In 2013, AMI expanded into consumer research and election forecasting. Although a relatively unknown entity, AMI predicted several election results accurately. Gupta describes AMI's rigorous process of research, primary data collection from each constituency, quality checking of data by auditors and data analysis. AMI partnered with India Today Group to broadcast its forecasts for post-poll studies. For pre-poll studies and market research, its clients now included political parties and corporates. In 2019, as the Haryana state elections were drawing to a close, Gupta found that his team's prediction for the election result was distinctly different from all other pollsters. Puzzled by this, he had asked for one more day to verify his data. As Gupta reviewed his team's analysis (which had been confirmed by another round of interviews during the last 24 hours), he considered whether he should publish these numbers or revise them just enough to avoid controversy.

This reading provides an introduction to forecasting methods. It includes a brief summary of methods based on judgment and a longer section on quantitative analysis. It also provides sample data so readers can develop an understanding of concepts such as correlation, covariance, time-series data, moving averages, exponential smoothing, time-series decomposition, trend estimation, simple linear regression, autocorrelation, and multiple linear regression.

Describes the death of a cancer patient in one of the nation's premier cancer treatment centers and examines the organizational and process characteristics that may have contributed to the medical error.