Problem
Susan Cassidy at BGI Case Questions ( HBS Case study)
I. Do you agree with the People Analytics team that Dan is at risk of leaving BGI, but not Jen. Are there any biases in this assessment?
II. How does the promotion algorithm work? Does it make sense? Does it fit with the firm's culture and goals?
III. Should Susan seek the social network data Raul is promising? How is this data collected? Should Susan trust this social network data?
IV. (i) What are the implications of Susan's decision for Jen's career? (ii) Is Jen going to leave if passed over for this promotion? (Hint: Think about LMX and psychological contracts).
V. How can firms create mechanisms to reduce biases in managerial decision-making? 10. What are the strengths and weaknesses of human and algorithmic decision-making? Think of situations where using one or the other makes more sense.