Evaluation of the applicability of investment appraisal techniques for assessing the business value of IS services.

There is a consensus among academics and practitioners that ICT investments should be carefully justified, measured and controlled. This is not different for the development of a service architecture or the development of particular services as such. In practice, the traditional capital investment appraisal techniques (CIAT’s) such as payback period or net present value are by far the most used techniques for assessing the feasibility of ICT investments. Nevertheless, serious doubts about the fitness of these techniques in a service based value net environment arise. Value nets have special characteristics such as high flexibility and agility, re-use of services,… that makes the use of these techniques very difficult and the reliability of the outcome most uncertain. Efforts are made to find more appropriate techniques. In the past, CIAT’s have been adjusted so that these techniques become more reliable in an ICT environment and new justification methods and techniques have been developed. However neither these adjusted techniques nor the new techniques are frequently used. This might be explained by the fact that the outcome of these techniques is difficult to interpret and to use and the fact that some significant problems (like the estimation of hidden costs) remain unsolved. Moreover, most of the new techniques are still in the conceptual phase. In this paper we evaluate these adjusted and new techniques in the light of service oriented architectures. We will argue that non of the techniques offers a good solution for assessing the business value of IS services. Despite the existence of a wealth of literature, the IS community appears to be no nearer to a solution to many problems associated with ICT appraisal. This is potentially problematic when dealing with investments in emerging technology such as IS services or service architectures. Since all techniques presented in the article have their drawbacks, it is safe to say that reliance on a sole technique may lead to sub-optimalisation or even failure. Therefore it makes sense to use a mixture of techniques, eliminating or diminishing the weaknesses of each of the techniques used. We strongly recommend a multi-layer evaluation process, or an evaluation process derived from the balanced scorecard, for the appraisal of investments in services or service architectures.

Existence dependency-based domain modeling for improving stateless process enactment.

In a process-enabled service oriented architecture, a process engine typically stores the state of the process instances during enactment. As an alternative, stateless process enactment entails that process state is derived from the state of business objects, which are organized in a domain model. The business objects are referred to in pre- and post-conditions of activities, which determine when the activity is enabled and completed, respectively. Despite the fact that the latter approach has multiple benefits compared with the former, the repeated state (re)calculations deteriorate performance and the formulation of clear conditions is not self-evident if typical domain modeling techniques (e.g. UML or ER) are adopted. In this paper we show that by adopting a specific domain modeling technique, which is based on the notion of existence dependency between the business objects, the performance and comprehensibility issues can proficiently be dealt with. We illustrate the technique using a real-world case from the insurance domain and analyze the emerging duality between process modeling and domain modeling.

A stigmergy based approach to data mining.

Data; Data mining;

A new approach for discovering business process models from event logs.

Process mining is the automated acquisition of process models from the event logs of information systems. Although process mining has many useful applications, not all inherent difficulties have been sufficiently solved. A first difficulty is that process mining is often limited to a setting of non-supervised learnings since negative information is often not available. Moreover, state transitions in processes are often dependent on the traversed path, which limits the appropriateness of search techniques based on local information in the event log. Another difficulty is that case data and resource properties that can also influence state transitions are time-varying properties, such that they cannot be considered ascross-sectional.This article investigates the use of first-order, ILP classification learners for process mining and describes techniques for dealing with each of the above mentioned difficulties. To make process mining a supervised learning task, we propose to include negative events in the event log. When event logs contain no negative information, a technique is described to add artificial negative examples to a process log. To capture history-dependent behavior the article proposes to take advantage of the multi-relational nature of ILP classification learners. Multi-relational process mining allows to search for patterns among multiple event rows in the event log, effectively basing its search on global information. To deal with time-varying case data and resource properties, a closed-world version of the Event Calculus has to be added as background knowledge, transforming the event log effectively in a temporal database. First experiments on synthetic event logs show that first-order classification learners are capable of predicting the behavior with high accuracy, even under conditions of noise.Credit; Credit scoring; Models; Model; Applications; Performance; Space; Decision; Yield; Real life; Risk; Evaluation; Rules; Neural networks; Networks; Classification; Research; Business; Processes; Event; Information; Information systems; Systems; Learning; Data; Behavior; Patterns; IT; Event calculus; Knowledge; Database; Noise;

Ants constructing rule-based classifiers.

Classifiers; Data; Data mining; Studies;

Predicting business/ICT alignment with AntMiner+.

In this paper we report on the results of a European survey on business/ICT alignment practices. The goal of this study is to come up with some practical guidelines for managers on how to strive for better alignment of ICT investments with business requirements. Based on Luftman's alignment framework we examine 18 ICT management practices belonging to 6 different competency clusters. We use AntMiner+, a rule induction technique, to create an alignment rule set. The results indicate that B/ICT alignment is a multidimensional goal which can only be obtained through focused investments covering different alignment aspects. The obtained rule set is an interesting mix of both formal engineering and social interaction processes and structures. We discuss the implication of the alignment rules for practitioners.Alignment; Artificial ant systems; Business; Business/ICT alignment; Data; Data mining; Framework; Investment; Investments; Management; Management practices; Managers; Practical guidelines; Processes; Requirements; Rules; Structure; Studies; Systems;

Implementing Consistency Management Techniques for Conceptual Modeling

Most software development methodologies justify the use of multiple independent models to represent all aspects at the different stages in the development process. This can make the resulting information system inconsistent at different levels: inconsistencies can arise between different views of a single system, between documents at different development life cycle stages, or in a single document. The use of a single model and different views to that model can avoid this problem: all views have to be built according to well-formedness rules for that view and consistency between the related views must be checked. In this way it is possible to obtain a model that reaches a feasible level of validity and improved completeness. Validity means that all statements made by the model are correct and relevant to the problem, whereas completeness means that the model contains all the statements about the domain. This paper presents different techniques to maintain consistency of one view and the use of the same techniques to enforce and check consistency between the views. First we discuss the three strategies of consistency management: consistency by analysis, consistency by monitoring and consistency by construction. Finally we present a concrete implementation of these rules in a modeling tool, based on the object-oriented domain modeling method MERODE.In Lecture Notes of Computer Sciencestatus: publishe

EM-BrA 2 CE v0.1: A Vocabulary and Execution Model for Declarative Business Process Modeling

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