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Mechanistic and bureaucratic organisations will probably struggle to encourage organisational learning. Critically evaluate this statement in relation to the Mechanistic and Learning perspectives.

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Mechanistic and bureaucratic organisations will probably struggle to encourage organisational learning. Critically evaluate this statement in relation to the Mechanistic and Learning perspectives.
Mechanistic and bureaucratic organisations will probably struggle to encourage organisational learning. Critically evaluate this statement in relation to the Mechanistic and Learning perspectives.

To evaluate this statement we first need to define what the mechanistic and learning approach is. Then define exactly what organisational learning is and what impact the characteristics of the mechanistic approach will have on it.

The two approaches involve theories and models about the adaptability and the learning skills of organizations. Bureaucracies clearly lack these characteristics in comparison to other approaches.
The mechanistic approach operates the organisation in the same way a machine operates - efficient, specialised, reliable, predictable, logical and with no opinions (has no heart).
The model which refers to this approach would be the Taylor model (Taylorism - 21st century scientific management). Frederick Winslow Taylor was a mechanical engineer who strived to improve industrial efficiency. He was a pioneer in the field of scientific management. The Taylor model consists of 4 components. 'Division of labour' where responsibility is shifted from worker to manager. 'One best way' where the scientific methods determine the most efficient way to operate. 'Scientific selection and training' which means the best person is selected depending on experience and qualifications. They are trained to work as efficiently as possible. Finally, 'monitor performance' where operations and performance is observed and monitored through an organisational hierarchy and through supervision. This basic concept further developed into Fordism and finally into TQM.
The mechanistic approach works well when the task is clear and straightforward. A complex task may be difficult to adapt / change regularly to make it more efficient. It also works well when there is a stable environment with predictable demands from customers. It is also easier to apply the

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