Florian Pinel

Artifact-Based Transformation of IBM Global Financing

IBM Global Financing (IGF) is transforming its business using the Business Artifact Method, an innovative business process modeling technique that identifies key business artifacts and traces their life cycles as they are processed by the business. IGF is a complex, global business operation with many business design challenges. The Business Artifact Method is a fundamental shift in how to conceptualize, design and implement business operations. The Business Artifact Method was extended to solve the problem of designing a global standard for a complex, end-to-end process while supporting local geographic variations. Prior to employing the Business Artifact method, process decomposition, Lean and Six Sigma methods were each employed on different parts of the financing operation. Although they provided critical input to the final operational model, they proved insufficient for designing a complete, integrated, standard operation. The artifact method resulted in a business operations model that was at the right level of granularity for the problem at hand. A fully functional rapid prototype was created early in the engagement, which facilitated an improved understanding of the redesigned operations model. The resulting business operations model is being used as the basis for all aspects of business transformation in IBM Global Financing.

Siena: From PowerPoint to Web App in 5 Minutes

Siena lets users design web applications using commonly available PowerPoint as the modeling/development tool. From PowerPoint, users can model business artifacts and processes, transform applications to a standard representation and then immediately deploy and execute these composite applications on a model execution engine.

Integrated model-driven dashboard development

Business performance modeling and model-driven business transformation are two research directions that are attracting much attention lately. In this study, we propose an approach for dashboard development that is model-driven and can be integrated with the business performance models. We adopt the business performance modeling framework, and we extend it in order to capture the reporting aspect of the business operation. We describe models that can effectively represent all the elements necessary for the business performance reporting process, and the interactions among them. We demonstrate how all these models can be combined and automatically generate the final solution. We further extend the proposed framework with mechanisms that can detect changes in the models and incrementally update the deployed solutions. Finally, we discuss our experience from the application of our technique in a real-world scenario. This case study shows that our technique can be efficiently applied to and handle changes in the underlying business models, delivering significant benefits in terms of both development time and flexibility.

A RESTful Architecture for Service-Oriented Business Process Execution

This paper presents a new approach to designing business process management solutions leveraging the principles of service-oriented computing and representational state transfer. We discuss the IT artifacts that underpin this new design, illustrate the design using a real world example, and present an evaluation highlighting several desirable features of our approach.

Cognition as a part of computational creativity

Computational creativity and cognitive computing are distinct fields that have developed in a parallel fashion. In this paper, we examine the relationship between the two, concluding that the two fields overlap in one precise way: the evaluation or assessment of artifacts with respect to creativity. Furthermore, we discuss a particular instance of computational creativity, culinary recipe design, and how cognitive informatics and cognitive computation enter into the domain.

Computational creativity for culinary recipes

Computational creativity is an emerging branch of artificial intelligence that places computers in the center of the creative process. This demonstration shows a computational system that creates flavorful, novel, and perhaps healthy culinary recipes by drawing on big data techniques. It brings analytics algorithms together with disparate data sources from culinary science, chemistry, and hedonic psychophysics. In its most powerful manifestation, the system operates through a mixed-initiative approach to human-computer interaction via turns between human and computer. In particular, the sequential creation process is modeled after stages in human cognitive processes of creativity. The end result is an ingredient list, ingredient proportions, as well as a directed acyclic graph representing a partial ordering of culinary recipe steps.

Optimizing system monitoring configurations for non-actionable alerts

Todays competitive business climate and the complexity of IT environments dictate efficient and cost effective service delivery and support of IT services. This is largely achieved through automating of routine maintenance procedures including problem detection, determination and resolution. System monitoring provides effective and reliable means for problem detection. Coupled with automated ticket creation, it ensures that a degradation of the vital signs, defined by acceptable thresholds or monitoring conditions, is flagged as a problem candidate and sent to supporting personnel as an incident ticket. This paper describes a novel methodology and a system for minimizing non-actionable tickets while preserving all tickets which require corrective action. Our proposed method defines monitoring conditions and the optimal corresponding delay times based on an off-line analysis of historical alerts and the matching incident tickets. Potential monitoring conditions are built on a set of predictive rules which are automatically generated by a rule-based learning algorithm with coverage, confidence and rule complexity criteria. These conditions and delay times are propagated as configurations into run-time monitoring systems.

An integrated framework for optimizing automatic monitoring systems in large IT infrastructures

The competitive business climate and the complexity of IT environments dictate efficient and cost-effective service delivery and support of IT services. These are largely achieved by automating routine maintenance procedures, including problem detection, determination and resolution. System monitoring provides an effective and reliable means for problem detection. Coupled with automated ticket creation, it ensures that a degradation of the vital signs, defined by acceptable thresholds or monitoring conditions, is flagged as a problem candidate and sent to supporting personnel as an incident ticket. This paper describes an integrated framework for minimizing false positive tickets and maximizing the monitoring coverage for system faults. In particular, the integrated framework defines monitoring conditions and the optimal corresponding delay times based on an off-line analysis of historical alerts and incident tickets. Potential monitoring conditions are built on a set of predictive rules which are automatically generated by a rule-based learning algorithm with coverage, confidence and rule complexity criteria. These conditions and delay times are propagated as configurations into run-time monitoring systems. Moreover, a part of misconfigured monitoring conditions can be corrected according to false negative tickets that are discovered by another text classification algorithm in this framework. This paper also provides implementation details of a program product that uses this framework and shows some illustrative examples of successful results.

Model-Driven Dashboards for Business Performance Reporting

Business performance modeling and model-driven business transformation are two research directions that are attracting much attention lately. In this study, we propose an approach for dashboard development that is model-driven and can be integrated with the business performance models. We adopt the business performance modeling framework, and we extend it in order to capture the reporting aspect of the business operation. We describe models that can effectively represent all the elements necessary for the business performance reporting process, and the interactions among them. We also demonstrate how all these models can be combined and automatically generate the final solution. Finally, we discuss our experience from the application of our technique in a real-world scenario. This case study shows that our technique can be efficiently applied to and handle changes in the underlying business models, delivering significant benefits in terms of both development time and flexibility

A Culinary Computational Creativity System

Compared to artifacts in expressive or performance domains, work products resulting from scientific creativity (including culinary recipes) seem much more conducive to data-driven assessment. If such products are viewed as an assembly of constituents that follow certain association principles, one could apply computationally intensive techniques to generate many possible combinations and use automated assessors to evaluate each of them. Assembly work plans for the selected novel products could subsequently be inferred from existing records. In this chapter, we report on our efforts to build a computational creativity system for culinary recipes. After gathering data and creating a knowledge base of recipes and ingredients, the system generates ingredient combinations that satisfy user inputs such as the choice of key ingredient, desired dish, and cuisine. Once a combination has been selected with the help of novelty and quality evaluators, the system further recommends ingredient proportions using a distributional conformance method and generates recipe steps using a subgraph composition algorithm. The time durations or efforts of atomic steps are estimated by solving an inverse problem from data on complete recipes. The example of culinary recipes could be generalized and applied to other scientific domains; manufacturing products and business processes could potentially follow a similar recipe for success.