It Services Support Rapid Response Process Modeling And Its Application

The goal of IT service is to restore system operation as quickly as possible for users. Responding speed and success rate are the two most important indicators as both are highly concerned by the service provider and the client. Meanwhile, less concerned by the client, the service provider needs to pay high attention on the service cost. The purpose of this thesis is to study the best way service providers can do to realize fastest responding speed at a controllable service cost.The top three challenges to establish fast responding organism is to firstly, earlier identify root cause and task objectives; secondly, be able to carry out a real-time dynamic task plan; Once the root causes being identified, we can define task objectives and find pin-pointed solutions; proper task planning can improve utilization and reduce, accordingly, service responding time improved. Last but not least, ensure all the resources and supports needed for completing the tasks are well planned. With clear objectives as early as possible, sufficient resources preparation, optimizing execution plan, realize as quickly as possible to help as more as possible users is to restore normal service.In this thesis the main contribution of work and the research content is as follows:1. Model A, which can figure out the failure cause during information communication with users, called off-site fault diagnosis model, according to the relationship between the cause of the fault and the phenomenon, the algorithm can work out a question for identification automatically and another one after answer and up to result. Its accuracy depends on how much magnitudes of the relationship between the cause of the fault and the phenomenon had known. As a maintainable self-learn system, it can ensure the accuracy of identification of the fault reason to increase substantially.2. Model B, which can decomposition pressure according to area of events and dynamic programming task sequence, called grids -queue task management model. On the basis of the mission in different area, dynamic optimize tasks in the pool of the independent area in accordance with different response requirement and status of tasks, ensure all the tasks response in schedule time.3. Efficiency and effectiveness of task implementation, therefore the two models above are organically combined, are achieved by the completely solution framework.4. Model A and group of management methods which support task execution and reasonable control of cost constitute the service cost control mechanism.As a successful applied example of IT service fast responding organism, service provider not only have made great progress of success rate, responding speed and service cost, but also established a manageable service productivity model.