Predictive people analytics is an emerging science and practice to make predictions of how key people, like managers, would behave under plausible future scenarios.
“The latest data and analytics buzz comes from the field of advanced HR analytics, where the application of new techniques and new thinking to talent management is becoming more mainstream.” – stated in McKinsey Quarterly, March 2015. – “Advanced analytics provides a unique opportunity for human-capital and human-resources professionals to position themselves as fact-based strategic partners of the executive board, using state-of-the-art techniques to recruit and retain the great managers and great innovators who so often drive superior value in companies.”
Knowledge of the skill-levels so obtained can be especially useful for predictive-analysis. This new, analytical approach is employed when an organization faces (or might soon be facing) a new challenge, which suggests that certain managerial/leadership/strategic skills are particularly valuable to successfully manage them. One of the useful applications of predictive analysis is in the case of planned mergers and acquisitions, where the incompatibility of organizational cultures can be – and often is – a fundamental cause of failure. Special game-based learning solutions (like FLIGBY), used appropriately, can help corporations build strategic skills in a timely, cost-effective and focused manner – a critical capability in today’s dynamic business environments.
The large and uniquely unbiased leadership-skill databank generated by FLIGBY’s players is a tool for supporting new types of both academic and practice-oriented research on leadership. FLIGBY’s contribution here is the unbiased nature of the skills-data-observations generated by its players. Both of the widely-used standard approaches to obtaining leadership-skill data – self-assessment and third-party evaluations – tend to be biased.
FLIGBY creates an environment that offers a new type of platform for observing management behavior. The player gets totally absorbed into the story (indicated by the fact that the global average actual playing time is 7.5 hours), concentrating on handling the 150+ decisions that he or she has to make. Since the “scoring” of those decisions (about 90 of the total) – in terms of any of the 29 leadership skills being measured takes place behind the scenes – and the player is completely unaware of how his or her decisions might affect his or her skill scores, the player unwittingly reveals his or her real self. This approach to testing skills is non-intrusive. It is not influenced by the Idiosyncratic Rater Effect. It is not distorted by the player feeling observed and thinking that he/she must respond as expected. And the player is not worried about the embarrassment of having to respond in front of peers, who will judge him/her. In playing FLIGBY, each player can and will behave as he/she would in similar situations in real life; being true to himself/herself.
Core elements of FLIGBY’s predictive analytics software architecture:
Given the large size and the uniquely unbiased properties of the FLIGBY databank, it obviously represents a great empirical resource for leadership research.