Mehmet Sayal

Business process intelligence

Business Process Intelligence (BPI,) is an emerging area that is getting increasingly popularfor enterprises. The need to improve business process efficiency, to react quickly to changes and to meet regulatory compliance is among the main drivers for BPI. BPI refers to the application of Business Intelligence techniques to businessprocesses andcomprises a large range ofapplication areas spanning from process monitoring and analysis to process discovery, conformance checking, prediction and optimization. This chapter provides an introductory overview of BPI and its application areas and delivers an understanding of how to apply BPI in ones own setting. In particular it shows how process mining techniques such as process discovery and conformance checking can be used to support process modeling and process redesign. In addition, it illustrates how processes can be improved and optimized over time using analytics for explanation, prediction, optimization and what-if-analysis. Throughout the chapter a strong emphasis is given to describe tools that use these techniques to support BPI. Finally, major challenges for applying BPI in practice and future trends are discussed.

Automated SLA Monitoring for Web Services

SLA monitoring is difficult to automate as it would need precise and unambiguous specification and a customizable engine that collects the right measurement, models the data and evaluates the SLA at certain times or when certain events happen. Also most of the SLA neglect client side measurement or restrict SLAs to measurements based only on server side. In a cross-enterprise scenario like web services it will be important to obtain measurements at multiple sites and to guarantee SLAs on them. In this article we propose an automated and distributed SLA monitoring engine.

Developing E-Services for Composing E-Services

The Internet is rapidly becoming the preferred mean through which companies provide services to businesses and customers. A large number of e-services, including for instance stock trading, customized newspapers, real-time traffic report, or itinerary planning, is already available on the Web, and the type and number of e-services grows on a daily basis. In order to support the development and deployment of e-services, software vendors are developing e-services frameworks and platforms, that provide a language for describing an e-service, and then allow service providers to register, advertise and securely deliver e-services to (authorized) users. A composite e-service is an e-service defined by composing other basic or composite e-services. As the e-service paradigm becomes popular and more and more applications are developed or deployed as e-services, the need and opportunity for defining composite service become manifest. This paper presents a specific type of e-service (or, rather, a meta e-service) called Composition E-Service (CES), that allows the definition, execution, management, and monitoring of composite e-services. We first describe the advantages and the functionality of such a service. Next, we present the language used for specifying the composition, also discussing why existing workflow languages are not suitable for this purpose. Finally, we present the architecture and implementation of the CES we developed to deliver the service on top of the e-services platform e-speak. An analogous architecture and implementation strategy can be followed with any other e-services platform.

Integrating workflow management systems with business-to-business interaction standards

Business-to-business (B2B) e-commerce is emerging as a new market with tremendous potential. Organizations are trying to link services across organizational boundaries in order to electronically trade goods and services. Standards such as RosettaNet, CBL, ED1, OB1, and cXML, describe how electronic B2B interactions should be carried on so that dynamic trade partnerships can be established and transactions can be executed across organizations. While the development of standards is a fundamental step towards enabling e-business, the problem of linking B2B interactions with internal business processes is still a challenge. In addition, as the industry standards evolve continuously based on changing needs, organizations have to adopt new standards quickly. In this paper we describe how workflow technology can be extended in order to support B2B interactions and to link them with the internal workflows. The proposed framework can be used to speed up both the development of new business processes that support B2B interaction standards and the enhancement of the existing business processes by the addition of B2B interaction capability.

Load balancing in distributed workflow management system

Management Systems (WFMS) play a very important role in constructing todays e-commerce environment through automating intra-enterprise business processes and inter-enterprise services. To handle the rapidly changing business environment and global competition, WFMSs should have flexibility and scalability to meet the business requirement and to quickly introduce new and efficient business services. Achieving load balancing is essential to ensure scalability in a distributed WFMS. In this paper we discuss load-balancing technology for distributed WFMSs. First, we introduce a workflow load index to measure load level of workflow engines. Then we present a WFMS cluster architecture with a load balancing subsystem. We compare the performance of round robin versus load- aware scheduling under the same load pattern. The experimental results show that the load index that we define in this paper is a good indicator of the load level in a distributed WMFS. The results also suggest that the load- aware scheduling algorithm can distribute workload fairly on heterogeneous WFMSs; instead, the round robin scheduling can only guarantee load balance in uniform WFMS with uniform workload and resource capabilities.

Chapter 79 – Business Process Cockpit: Extended Abstract

Publisher Summary This chapter describes the business process cockpit (BPC), a tool that supports real-time monitoring, analysis, and management of business processes running on top of Hewlett-Packard Process Manager (HPPM), the Business Process Management Systems (BPMS) developed by Hewlett-Packard (HP). Business process management systems (BPMSs) are software platforms that support the definition, execution, and tracking of business processes. They are often used to support administrative and production processes as well as to implement complex web services, delivered by composing existing ones according to some process logic. BPMSs have the ability of logging information about the business processes they support, including for instance the start and completion time of each activity, its input and output data, the resource that executed it, as well as events (messages) sent or received.workflow, business process, HPPM (HP Process Manager), data analysis, visualization of data Business Process Cockpit (BPC) is a tool that supports real-time monitoring, analysis, management, and optimization of business processes running on top of HP Process Manager, the Business Process Management System developed by HewlettPackard. The main goal of the Business Process Cockpit is to enable business users to perform business-level quality analysis, monitoring, and management of business processes. The BPC visualizes process execution data according to different focus points that identify the process entities that are the focus of the analysis, and different perspectives that define a way to look at the information. The BPC also allows users to define new concepts, such as “slow” and “fast” executions, and use those concepts to categorize the viewed data and make it much easier for users to interpret.

Business Process Cockpit: Extended Abstract

Publisher Summary This chapter describes the business process cockpit (BPC), a tool that supports real-time monitoring, analysis, and management of business processes running on top of Hewlett-Packard Process Manager (HPPM), the Business Process Management Systems (BPMS) developed by Hewlett-Packard (HP). Business process management systems (BPMSs) are software platforms that support the definition, execution, and tracking of business processes. They are often used to support administrative and production processes as well as to implement complex web services, delivered by composing existing ones according to some process logic. BPMSs have the ability of logging information about the business processes they support, including for instance the start and completion time of each activity, its input and output data, the resource that executed it, as well as events (messages) sent or received.workflow, business process, HPPM (HP Process Manager), data analysis, visualization of data Business Process Cockpit (BPC) is a tool that supports real-time monitoring, analysis, management, and optimization of business processes running on top of HP Process Manager, the Business Process Management System developed by HewlettPackard. The main goal of the Business Process Cockpit is to enable business users to perform business-level quality analysis, monitoring, and management of business processes. The BPC visualizes process execution data according to different focus points that identify the process entities that are the focus of the analysis, and different perspectives that define a way to look at the information. The BPC also allows users to define new concepts, such as “slow” and “fast” executions, and use those concepts to categorize the viewed data and make it much easier for users to interpret.

Semantic Analysis of E-Business Operations

An e-business infrastructure is comprised of a large number of business processes that are exposed through web services. To manage such an infrastructure, it is necessary for business managers to be able to observe their e-business operations in greater detail. In particular, a framework and a tool is required that allows business users to define qualitative and quantitative metrics, depending on their own (business or IT) goals. Once metrics have been defined, the tool should be able to measure them and support users in semantic analysis of the results, allowing them to quickly identify quality degradations as well as their causes.

Improving process models by discovering decision points

Workflow management systems (WfMS) are widely used by business enterprises as tools for administrating, automating and scheduling the business process activities with the available resources. Since the control flow specifications of workflows are manually designed, they entail assumptions and errors, leading to inaccurate workflow models. Decision points, the XOR nodes in a workflow graph model, determine the path chosen toward completion of any process invocation. In this work, we show that positioning the decision points at their earliest points can improve process efficiency by decreasing their uncertainties and identifying redundant activities. We present novel techniques to discover the earliest positions by analyzing workflow logs and to transform the model graph. The experimental results show that the transformed model is more efficient with respect to its average execution time and uncertainty, when compared to the original model.

Compact Bidding Languages and Supplier Selection for Markets with Economies of Scale and Scope

Combinatorial auctions have been used in procurement markets with economies of scope. Preference elicitation is already a problem in single-unit combinatorial auctions, but it becomes prohibitive even for small instances of multi-unit combinatorial auctions, as suppliers cannot be expected to enumerate a sufficient number of bids that would allow an auctioneer to find the efficient allocation. Auction design for markets with economies of scale and scope are much less well understood. They require more compact and yet expressive bidding languages, and the supplier selection typically is a hard computational problem. In this paper, we propose a compact bidding language to express the characteristics of a suppliers cost function in markets with economies of scale and scope. Bidders in these auctions can specify various discounts and markups on overall spend on all items or selected item sets, and specify complex conditions for these pricing rules. We propose an optimization formulation to solve the resulting supplier selection problem and provide an extensive experimental evaluation. We also discuss the impact of different language features on the computational effort, on total spend, and the knowledge representation of the bids. Interestingly, while in most settings volume discount bids can lead to significant cost savings, some types of volume discount bids can be worse than split-award auctions in simple settings.