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A System and method for optimal investment Scheduling for transformation of a service delivery system

IP.com Disclosure Number: IPCOM000239699D
Publication Date: 2014-Nov-26
Document File: 5 page(s) / 190K

Publishing Venue

The IP.com Prior Art Database

Abstract

Principles and embodiments here provide techniques for service delivery system transformation based on an optimization model to solve the investment scheduling problem. The objective of optimization problem is to identify the space (service component) and time (weekly basis) for new investment so as to meet the service level objectives while minimizing the overall cost and/or delay for system transformation. The model also involves a number of implementation constraints from ground reality as the change in KPI on a certain component depends on multiple time and capacity-dependent factors. Detailed analysis of the implementation constraints are very important for transformation of a human-centric service delivery system. Thus, we perform the implementation validity on each iteration and reaches to the final optimum solution

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A System and method for optimal investment Scheduling for transformation of a service delivery system

Field

    Embodiments here generally relates techniques for service delivery system transformation based on an optimization model to solve the investment scheduling

problem. The objective of optimization problem is to identify the space (service component) and time (weekly basis) for new investment so as to meet the service level objectives while minimizing the overall cost and/or delay for system transformation. The model also involves a number of implementation constraints from ground reality as the change in KPI on a certain component depends on multiple time and capacity-dependent factors. Detailed analysis of the implementation constraints are very important for transformation of a human-centric service delivery system. Thus, we perform the implementation validity on each iteration and reaches to the final optimum solution.

Detailed Description

Principles here includes investment scheduling in service delivery system transformation to meet the service level objectives.

    For a given KPI network, a time-dependent multivariate regression model is formulated to represent the system outcomes as a linear function of KPI variables with appropriate time-lags. For multiple outcome prediction, the prediction model is applied separately for each outcome since the impact delays between the KPI variables and each outcome could be different.

To develop the budget allocation model, we define the following notations

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about the service delivery system and the its service level objectives.

We need to decide the investment amount at each candidate node so as to meet the

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desired outcome requirements within an overall budget and time. The general

problem is to choose the investment-ready nodes (Hi= 1) and the corresponding KPI values xi , so as to minimize the weighted combination of normalized transformation time t/T and normalized cost Ó Qi Hi (xi - xi0)/B , subject to the constraints that the outcome values are greater than the desired levels, required transformation time is bounded by the upper limit T and the total investment does not exceed the overall budget B .

Now we can state the problem as a ma...