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.

A Top-Down Pricing Algorithm for IT Service Contracts Using Lower Level Service Data

This paper takes a cross-disciplinary view of the ontology of “business process”: how the concept is treated in the IS research literature and how related concepts (with stronger human behavioural orientation) from organisation and management sciences can potentially inform this IS perspective. In particular, is there room for socio-technical concepts such as technology affordance, derived from the constructivist tradition, in improving our understanding of operational business processes, particularly human-centric business processes? The paper presents a theoretical framework for understanding the role of business processes in organisational agility that distinguishes between the process-as-designed and the process-as-practiced. How this practice aspect of business processes also leads to the improvisation of various information technology enablers, is explored using a socio-technical lens. The posited theoretical framework is illustrated and validated with data drawn from an interpretive empirical case study of a large IT services company. The research suggests that processes within the organisation evolve both by top-down design and by the bottom-up routinisation of practice and that the tension between these is driven by the need for flexibility.

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Business processes in the agile organisation: a socio-technical perspective

In order for an Information Technology (IT) service provider to respond to a client’s request for proposals of a complex IT services deal, they need to prepare a solution and enter a competitive bidding process. A critical factor in this solution is the pricing of various services in the deal. The traditional way of pricing such deals has been the so-called bottom-up approach, in which all services are priced from the lowest level up to the highest one. A previously proposed more efficient approach and its enhancement aimed at automating the pricing by data mining historical and market deals. However, when mining such deals, some of the services of the deal to be priced might not exist in them. In this paper, we propose a method that deals with this issue of incomplete data via modeling the problem as a machine learning recommender system. We embed our system in the previously developed method and statistically show that doing so could yield significantly more accurate results. In addition, using our method provides a complete set of historical data that can be used to provide various analytics and insights to the business.

Top-Down Pricing of IT Services Deals with Recommendation for Missing Values of Historical and Market Data

The SaaS model is software delivery model that allow the end user to use the software online without it being installed on their computer. The end user is charged by the service provider for using the services. Most of the existing Cloud cost models determine usage-charges based on infrastructure cost. In this paper, the cost model for the SaaS services is proposed that focuses not only on infrastructure but also on service parameters. The proposed model considers the service parameter for the SaaS such as customization, configurability, portability, security, QoS parameters including performance, usability, response timeliness, scalability and reliability, interoperability, data isolation and application isolation. With the help of proposed model, the service provider is able to calculate the efforts in developing the service more accurately and provide better service package deals to the service consumer.

Cost model for software as a service

To respond to requests for proposals from clients requiring complex Information technology (IT) services, IT service providers have to prepare a solution composed of the multiple services requested by the clients and price that solution. Then, each provider competes in a tender-kind of process trying to convince the client with their solution. Pricing these solutions/deals, using historical and market data, is a complex task that we studied in our previous works. In our prior pricing approaches, we used a simple algorithm for selecting similar historical and market deals to the one we are trying to price, before we mine the data of these deals to estimate the costs of that latter deal. However, there are multiple limitations to that algorithm that we overcome in the novel approach that we present in this paper. These limitations include missing on some similar deals due to the way we chose them. Our new approach involves an iterative algorithm that selects peer deals at different levels until a pre-specified number of deals is determined. We present a proof-of-concept implementation of our approach, using real-world data, to illustrate its efficiency.

A Method for Selecting Peer Deals in IT Service Contracts

Cloud computing is experiencing phenomenal growth and there are now many vendors offering their cloud services. In cloud computing, cloud providers cooperate together to offer their computing resource as a utility and software as a service to customers. The demands and the price of cloud service should be negotiated between providers and users based on the Service Level Agreement (SLA). In order to help cloud providers achieving an agreeable price for their services and maximizing the benefits of both cloud providers and clients, this paper proposes a cloud pricing system consisting of hierarchical system, M/M/c queuing model and pricing model. Simulation results verify the efficiency of our proposed system.

A Hierarchical Cloud Pricing System

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A Hierarchical Cloud Pricing System