Effectiveness of service complexity configurations in top-down complex services design
Abstract:
One embodiment provides a method comprising receiving historic peer deals relating to at least one service, and a baseline and cost percentage estimation for each service. Historic peer cost data for each service is clustered to form at least one cluster. Each cluster includes similar unit costs, and has an assigned label. A classification model is trained based on each baseline received, each cost percentage estimation received, and each assigned label. For each assigned label, a corresponding probability distribution is computed based on the classification model. For each service of a new client solution, an assigned label for the service is predicted based on the classification model, and, based on a probability distribution corresponding to the assigned label predicted, transforming an initial range of historic peer cost data relating to the service into a narrower range for use in estimating a cost of the service with improved accuracy.
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