Realizing an optimal task scheduling by taking into account the business importance of jobs has become a matter of interest in pay and use model of Cloud computing. Introduction of an appropriate model for an efficient task scheduling technique could derive benefit to the service providers as well as clients. In this paper, we have addressed two major challenges which has implications on the performance of the Cloud system. One of the major issues is handling technical aspects of distributing the tasks for targeted gains and the second issue is related to the handling of the business priority for concurrently resolving business complexity related to cloud consumers. A coordinated scheduling can be achieved by considering the weightage of both aspects viz. technical requirements and business requirements appropriately. It can be done in such a way that it meets the QoS requirements of technical domain as well as business domain. Along with the technical priority a business Bp is required in creating a resultant priority which could be given to stages of further processing, like task allocation and arbitration schemes. Here we consider a technical priority Tp that is governed by a semi-adaptive scheduling algorithm whereas the resultant priority is derived in which a Business Priority Bp layer encapsulates the Technical Priority Tp to achieve the overall priority of the incoming tasks. It results in a Hybrid priority creation, which is a combination of both technical priority Tp and business priority Bp. By taking into account the business priority of the jobs it is possible to achieve a higher service level satisfaction for the tasks which are submitted with their native technical priority. With this approach the waiting time of the tasks tends to get reduced and it gives a better service level satisfaction.