Preface

Written for anyone in any organization making human capital management (HCM) decisions, including C-level executives and all managers, this book does several things:

• It provides a summary of implications associated with new research on how decisions are made and what motivates us.

• It develops an evidence-based approach using advanced analytics to assist organizations with developing a collaborative workplace and with selecting and motivating people.

• It applies the new thinking associated with advances in behavioral economics, psychology, and machine learning to the decision-making process and refers to this as “The New Human Science.”

• And it further recognizes the value of human experience and expertise and provides a mechanism for applying both advanced analytics and intuition or expert knowledge.

Here is how the book is structured.

Chapter 1, “Challenges and Opportunities with Optimal Decision Making and How Advanced Analytics Can Help,” provides the overall framework and discusses how it is to be applied to human capital management (HCM) decision making. This framework builds on the work of Nobel Prize winning social psychologist Daniel Kahneman, along with others, to provide strong evidence that we do not decide rationally. The chapter discusses the role biases play in decision making and how the use of advanced analytics can help eliminate bias from decisions.

Chapter 2, “Collaboration, Cooperation, and Reciprocity,” focuses on the role of collaboration, information sharing, and decentralized decision making. In this chapter, some of the old thinking about what motivates us is dispelled, and new findings are applied. Economic science has long held that we are generally self-centered, selfish, inherently lazy, and largely interested in only income maximization. This assumption about our natures has had a substantial impact on the way in which the employment relationship has been structured and has generally led to mistrust and noncooperative behaviors. Recent evidence finds that we are actually unselfish, cooperative, altruistic, and potentially very self-motivated. This has substantial implications for how we ideally organize ourselves. The role and importance of collaboration and cooperation is also discussed.

Chapter 3, “Value Creation and Advanced Analytics,” covers evidence where value is found within organizations and how getting the right mix of human capital, HCM practices and policies, and technology will ultimately lead to better performance outcomes. The loss associated with high employee turnover is discussed, as is how human science can help reduce the loss of expertise associated with human capital leaving the organization.

Chapter 4, “Human Science and Selection Decisions,” covers how advanced analytics can reduce and eliminate discriminatory hiring and promotion decisions. The focus of the chapter is on the use of bio data to make better hiring predictions.

Chapter 5, “Human Science and Incentives,” focuses on how advanced analytics can assist with decisions associated with developing incentive contracts. New evidence on what motivates people is discussed, as well as how a focus on tournament compensation is suboptimal. Application of human science including advanced analytics to practical incentive contract challenges is made.