Valeria Becker

Industry Operations Architecture for Business Process Model Collections

The absence of a holistic industry-centric architecture for processes is an important BPM shortfall that impacts model collections. This paper introduces a Componentized Industry Business Architecture as a vehicle to address this gap and to make processes better integrated with other critical dimensions in organizational design. This architecture provides the foundation for a taxonomy of processes and enables process models to be created or potentially rationalized against a comprehensive framework.

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

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.

A Method for Selecting Peer Deals in IT Service Contracts

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 estimating annual cost reduction of IT service deals

Highly valued Information technology (IT) service contracts involve the delivery of complex IT services, such as migrating the clients IT infrastructure to the Cloud, Mainframes, among others. IT service providers usually compete to win these IT service contracts. In order to bid on such deals, IT service providers need to price/quote the solution that they propose to the client, trying to convince him to use their services. A few analytical methods in the literature have been provided for pricing these deals. However, these methods ignore an important characteristic of these services; that is they are typically characterized by a decreasing cost profile in subsequent years to the first year. Typically, these methods require solutioners to manually input these annual cost reductions. In this paper, we present an analytical way for calculating this cost reduction, if applicable, via mining historical data. We show that using our methodology could achieve significant increase in the accuracy of estimating the costs and prices of IT service deals.

Integrating Service Release Management with Service Solution Design

Web-delivered services such as Web or Cloud services are often made available to users in a fast cadence of releases, taking advantage of the single deployment environment of a centrally controlled service. This enables organizations to bring service enhancements to customers in a timely way and respond quickly to market demands. Organizations use multiple Web-delivered services by one or multiple vendors to compose complex solutions to their business problems in conjunction with standard applications and custom implementation and delivery services. Designing these complex solutions often takes considerable time and multiple new releases of a service and a changed service roadmap may have influence on a customer’s solution design. Existing IT service management and software development best practices do not consider the relationship between service release management and service design sufficiently to address frequent releases and changes to a service roadmap. This paper discusses the relationship from both the point of view of the service provider and the service customer and proposes an approach to manage those interdependencies between service design and release management.

The Structure of Cross-Functional Process Model Collections: An Empirical Investigation

Firms organize work across functional line-of-businesses to deliver the most important outcomes that are needed for clients and other key stakeholders. These cross-functional operations are represented as business processes and are known to be the most critical ones in a firm. However, little is known about business-relevant families of processes because most available BPM literature deals with examples including only a couple of processes or very small collections for very specialized and narrow areas of the organization. The modeling and understanding of cross-functional processes in an industry segment is then a very important task. The representation of these collections involves a network of N core activities that a typical organization carries out in its individual functions as well as the coordination of selected subsets of these activities into a family of P cross-functional processes. In this paper, we present a study of the structure of these cross-functional process models. We show some properties of these collections through extensive experimentation with well-established families of processes for Property and Casualty, Health Care, and Life and Pension harvested in the Insurance Industry for more than 15 years. For the first time in the literature, the structure of a process model collection is studied and shown. The statistical laws followed by these collections of actual and real process models are shown in three major insurance industry segments. One remarkable result shows that the frequency of reused activities follows long-tail distributions. Some statistical tests are applied to determine the specific type of this and related distributions of N activities and to verify whether their tails follow a power-law or other forms. We conjecture that all process model collections capturing all key operations done in an organization (both cross-functional or within a significant Line of Business) exhibit this long-tail behavior. We also investigate the effect of different partitioning criteria by grouping the N activities into K components by following two criteria. In one of them the goal is to achieve a balance between the cost of interactions needed by the P processes across such components and the complexity of managing O(N/K) activities in each component. The other criterion delves into graph community formation by suitable edge criticality properties. This chapter of our work offers a preliminary investigation into Simons principle of organizing complexity as a set of loosely-coupled interactions among a smaller number of coarser grain components in an enterprise.