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Management Observation Program Best Practice 6 – Observation Announcement Timing
Philosophically speaking, no one, including managers, should ever be afraid to have ‘the boss’ know or observe what he or she is doing. Being human, we naturally feel self imposed pressure to perform well especially when we are being watched. Subsequently, management observations will always make the conscientious employee at least somewhat nervous. When then does a manager announce that he or she will be observing an individual’s performance? In most cases, shortly before the observation begins.
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Management observations profoundly influence the behaviors of those observed. Done well, this tool positively reinforces desired behaviors. Performed poorly, this tool will undermine the management team’s credibility and fosters cynicism towards managers and their performance standards requirements. Therefore, it is critical that those performing these observations do so in a consistent, high quality manner.
Fact or fiction, anything formally documented assumes an air of legitimacy. Combine this implied legitimacy with the stark black and white of the printed words and any identified improvement opportunity can appear overly harsh and critical, especially to those responsible for the performance. Apparent aggressiveness within a self assessment can result in resistance to the evaluation findings; often by those who stand to benefit the most and who must own the corrective actions.
Management observation programs seek to reinforce desired behaviors while also capturing data to enable the identification of improvement opportunities. Both of these objectives require observation repetition in order to be effective; enough reinforcement points to alter or establish reflexive behaviors and an adequate number of data points collected to enable a statistically sound conclusion to be formed. Realizing the desired number of observations is most easily achieved through a quota system.
An organization's performance and the environment in which it operates change dynamically. Subsequently, most measures reflecting these performance variables are also dynamic; challenging analysts to interpret historical and predict future movement.
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