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This book directly addresses the explosion of literature about
leveraging analytics with employee data and how organizational
psychologists and practitioners can harness new information to help
guide positive change in the workplace. In order for today's
organizational psychologists to successfully work with their
partners they must go beyond behavioral science into the realms of
computing and business acumen. Similarly, today's data scientists
must appreciate the unique aspects of behavioral data and the
special circumstances which surround HR data and HR systems.
Finally, traditional HR professionals must become familiar with
research methods, statistics, and data systems in order to
collaborate with these new specialized partners and teams. Despite
the increasing importance of this diversity of skill, many
organizations are still unprepared to build teams with the
comprehensive skills necessary to have high performing HR Analytics
functions. And importantly, all these considerations are magnified
by the introduction and acceleration of machine learning in HR.
This book will serve as an introduction to these areas and provide
guidance on building the connectivity across domains required to
establish well-rounded skills for individuals and best practices
for organizations when beginning to apply advanced analytics to
workforce data. It will also introduce machine learning and where
it fits within the larger HR Analytics framework by explaining many
of its basic tenets and methodologies. By the end of the book,
readers will understand the skills required to do advanced HR
analytics well, as well as how to begin designing and applying
machine learning within a larger human capital strategy.
This book directly addresses the explosion of literature about
leveraging analytics with employee data and how organizational
psychologists and practitioners can harness new information to help
guide positive change in the workplace. In order for today's
organizational psychologists to successfully work with their
partners they must go beyond behavioral science into the realms of
computing and business acumen. Similarly, today's data scientists
must appreciate the unique aspects of behavioral data and the
special circumstances which surround HR data and HR systems.
Finally, traditional HR professionals must become familiar with
research methods, statistics, and data systems in order to
collaborate with these new specialized partners and teams. Despite
the increasing importance of this diversity of skill, many
organizations are still unprepared to build teams with the
comprehensive skills necessary to have high performing HR Analytics
functions. And importantly, all these considerations are magnified
by the introduction and acceleration of machine learning in HR.
This book will serve as an introduction to these areas and provide
guidance on building the connectivity across domains required to
establish well-rounded skills for individuals and best practices
for organizations when beginning to apply advanced analytics to
workforce data. It will also introduce machine learning and where
it fits within the larger HR Analytics framework by explaining many
of its basic tenets and methodologies. By the end of the book,
readers will understand the skills required to do advanced HR
analytics well, as well as how to begin designing and applying
machine learning within a larger human capital strategy.
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