Information technology (IT) service providers competing for high valued contracts need to produce a compelling proposal with competitive price. The traditional approach to pricing IT service deals, which builds up the bottom-up costs from the hierarchy of services, is often time consuming, resource intensive, and only available late as it requires granular information of a solution. Recent work on top-down pricing approach enables efficient and early estimates of cost and prices using high level services to overcome and complement these problems. In this paper, we describe an extended pricing method for top-down pricing using the secondary service level. The method makes use of data lower level services to calculate improved estimates, yet still requires minimal input. We compare the previous and new approaches based on industrial data on historical and market deals, and demonstrate that the new approach can generate more accurate estimates. In addition, we also show that mining historical data would yield more accurate estimation than using market data for services, experimental results are in consistent with our findings in previous work.
['Kugamoorthy Gajananan', 'Aly Megahed', 'Mari Abe', 'Taiga Nakamura', 'Mark A. Smith']
A Top-Down Pricing Algorithm for IT Service Contracts Using Lower Level Service Data