Why and how did we develop the Push-out Score™?
When a top manager leaves the position, a crucial question arises:
Is it a forced or a voluntary departure?
The answer can be difficult. C-suite executives are rarely openly fired. And the problem starts with the definition of “forced” and “voluntary”.
Is it a voluntary departure when the CEO, according to the corporate announcement, “provided notice to the Company that he will voluntarily retire”, whereas there is strong reason to believe that the manager took advantage of the opportunity to resign before being pushed out in disgrace?
The difficulty is that both the company (namely, the board) and the executive in question have motives not to reveal forced turnovers as such. Board and management are, within certain limits, not necessarily required to reveal the reason for a departure. Therefore, they will defend their own interests.
The result is unsatisfactory for many stakeholders of the company, including investors, creditors, customers, employees and the public. They need to know what happened. And they have legitimate interests in learning what is going on. It also affects them.
“People familiar with the matter” and “people familiar with the board’s thinking” may give additional (and alternative) facts or complex answers to simple questions in order to influence media coverage. They may provide valuable information. But anonymous sources that cannot be held liable for their statements must be considered with caution. They are not primarily committed to the truth. First and foremost, they follow their own (or their clients’) interest and may be inclined to give biased information.
For academic researchers, a common categorization procedure is to use some variant of the Parrino (1997) algorithm to classify CEO turnover. This rule-based method allows a relatively rough classification: voluntary or forced. The risk of misclassification is relatively high.
Some years ago, Daniel Schauber, a veteran business editor, started a research project to determine whether a new approach, inspired by the push and pull factors theory in migration research, would prove more fruitful.
The central question of the research project was:
On a scale of 0 to 10, how likely is it the manager was pushed out or felt pressure to leave the post?
The Push-out Score™ would give the answer.
The Push-out Score was developed in an inductive way and in close interaction with experts — among them personnel professionals, executive search firms, investors and corporate governance experts. To develop the Push-out Score, we used a text corpus containing thousands of management-change announcements and regulatory filings from the last ten years.
Ultimately, 9 criteria turned out to be particularly suitable to determine the likelihood of a forced turnover:
- Form of the management-change announcement
- Language in the announcement
- Age of the departing executive
- Notice period (time between announcement and departure)
- Share price development
- Official reason given
- Circumstances of the management change (e.g., firm and industry performance, peer group performance, severance payment),
- Succession (e.g., external vs. internal, permanent vs. interim solution).
The Push-out Score was introduced in September 2016 and quickly gained popularity among executive search firms, hedge funds and corporate governance experts.
Among the first researchers attracted by the Push-out Scoring System and the underlying algorithms and data was David F. Larcker, Director of the Corporate Governance Research Initiative at the Stanford Graduate School of Business and senior faculty member at the Rock Center for Corporate Governance at Stanford University.
A September 2016 “Research Spotlight” by David F. Larcker and Brian Tayan from Stanford Graduate School of Business provides a summary of the academic literature on the relationship between CEO performance and turnover.
Among the first journalists interested in the creation of the Push-out Score algorithm and exechange’s use of smart machines to write copy was Julia Kirby, Senior Editor at Harvard University Press and co-author of the book “Only Humans Need Apply: Winners & Losers in the Age of Smart Machines” (HarperCollins).