Knowledge and Suggestion Schemes
The companies investigated were primarily machine bureaucracies, though the police force and medical services companies had elements of professional bureaucracy. It was therefore not surprising that the ideas handled by their suggestion schemes were explicit, non-professional suggestions mainly targeted at improving and refining the encoded knowledge of the organisation that governed working procedures.
Amongst those attracted were suggestions recommending modifications to the design of forms, suggestions for automating clerical activities and a suggestion to set up a web based service to clarify the procedures surrounding internal promotion. In a non-clerical setting, employees suggested the use of sheep to control the growth of vegetation around electrical installations.
A significant feature of suggestions is that they are often based on either an intimate knowledge of detailed procedures or of the reactions of customers to an organizations behavior. Neither of these experiences is automatically available to those within the machine bureaucracy who have the task of encoding the organization’s knowledge into work procedures.
Neither, on the other hand, do the greater body of employees in machine bureaucracies have the flexibility in their job descriptions that would enable them to improve their work processes with out some appeal to a higher authority. The suggestion schemes studied were run by enterprises that were convinced that it was people at the „sharp end‟ who were best placed to identify problems and suggest improvements.
Some of the organisations deliberately used their suggestion schemes to harvest the creativity arising from this knowledge. Scheme administrators also saw their schemes as facilitating the sharing of best practice. This was particularly possible where a fully automated scheme gave employees access to past suggestions and enabled them to contact their suggesters.
Although scheme administrators could see the potential for secondary analysis of the database of suggestions to identify, for example, common features in suggestions or areas of the organization that needed more encouragement to be innovative, the organizations they represented made relatively little attempt to use the suggestions in this way.
The companies investigated were primarily machine bureaucracies, though the police force and medical services companies had elements of professional bureaucracy. It was therefore not surprising that the ideas handled by their suggestion schemes were explicit, non-professional suggestions mainly targeted at improving and refining the encoded knowledge of the organisation that governed working procedures.
Amongst those attracted were suggestions recommending modifications to the design of forms, suggestions for automating clerical activities and a suggestion to set up a web based service to clarify the procedures surrounding internal promotion. In a non-clerical setting, employees suggested the use of sheep to control the growth of vegetation around electrical installations.
A significant feature of suggestions is that they are often based on either an intimate knowledge of detailed procedures or of the reactions of customers to an organizations behavior. Neither of these experiences is automatically available to those within the machine bureaucracy who have the task of encoding the organization’s knowledge into work procedures.
Neither, on the other hand, do the greater body of employees in machine bureaucracies have the flexibility in their job descriptions that would enable them to improve their work processes with out some appeal to a higher authority. The suggestion schemes studied were run by enterprises that were convinced that it was people at the „sharp end‟ who were best placed to identify problems and suggest improvements.
Some of the organisations deliberately used their suggestion schemes to harvest the creativity arising from this knowledge. Scheme administrators also saw their schemes as facilitating the sharing of best practice. This was particularly possible where a fully automated scheme gave employees access to past suggestions and enabled them to contact their suggesters.
Although scheme administrators could see the potential for secondary analysis of the database of suggestions to identify, for example, common features in suggestions or areas of the organization that needed more encouragement to be innovative, the organizations they represented made relatively little attempt to use the suggestions in this way.