What Automated Planning Can Do for Business Process Management

Business Process Management (BPM) is a central element of today organizations. Despite over the years its main focus has been the support of processes in highly controlled domains, nowadays many domains of interest to the BPM community are characterized by ever-changing requirements, unpredictable environments and increasing amounts of data that influence the execution of process instances. Under such dynamic conditions, BPM systems must increase their level of automation to provide the reactivity and flexibility necessary for process management. On the other hand, the Artificial Intelligence (AI) community has concentrated its efforts on investigating dynamic domains that involve active control of computational entities and physical devices (e.g., robots, software agents, etc.). In this context, Automated Planning, which is one of the oldest areas in AI, is conceived as a model-based approach to synthesize autonomous behaviours in automated way from a model. In this paper, we discuss how automated planning techniques can be leveraged to enable new levels of automation and support for business processing, and we show some concrete examples of their successful application to the different stages of the BPM life cycle

Supporting adaptiveness of cyber-physical processes through action-based formalisms

Cyber Physical Processes (CPPs) refer to a new generation of business processes enacted in many application environments (e.g., emergency management, smart manufacturing, etc.), in which the presence of Internet-of-Things devices and embedded ICT systems (e.g., smartphones, sensors, actuators) strongly influences the coordination of the real-world entities (e.g., humans, robots, etc.) inhabitating such environments. A Process Management System (PMS) employed for executing CPPs is required to automatically adapt its running processes to anomalous situations and exogenous events by minimising any human intervention. In this paper, we tackle this issue by introducing an approach and an adaptive Cognitive PMS, called SmartPM, which combines process execution monitoring, unanticipated exception detection and automated resolution strategies leveraging on three well-established action-based formalisms developed for reasoning about actions in Artificial Intelligence (AI), including the situation calculus, IndiGolog and automated planning. Interestingly, the use of SmartPM does not require any expertise of the internal working of the AI tools involved in the system

Creativity Lies at the Edges of Chaos- Reducing Complexity in IT Projects

As businesses operate in increasingly more complex environments, understanding complexity and its sources is becoming increasingly important. These sources range from internal organizational culture to, technical and social environment in which the business operates, to the competitive dynamics aimed at capturing and maximizing market share. The increasing unpredictability and complexity of unforeseen competitive consequences call for novel methods of planning, execution, and management of business. As organizations confront these changes and attempt to adapt to them, they find that management of technology intensive projects can no longer be viewed as a linear process of planned actions. In these project change agents self organize to accomplish pre-determined goals based on the feedback, emerging circumstances, and to cope with future uncertainty. This process of self organization results in organizational evolution and growth based on generative learning that facilitates continuous improvement through action oriented learnings. In doing so, this increased complexity results in complex adaptive systems increasingly evolving throughout the organization and creating unpredictable changes operating between stability and instability. This paper tackles the issue complexity management in technology intensive projects. It particularly focuses on elements of complexity; role of project managers; and theories for managing complexities in projects

Adaptive Process Management in Cyber-Physical Domains

The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time

Investigating causes of delays and cost escalation in project execution during turnarounds.

Master of Business Administration. University of KwaZulu-Natal, Westville 2015.The main purpose of this dissertation is to evaluate the causes and consequences of delays in project execution and their impact on the success of the project. The research methods include qualitative and quantitative methods. Literature provides evidence that poor project management structure, poor planning and inadequate communication contribute negatively to the success of the project. Project planning is an essential part of the project as it provides the tools to plan – the scope, cost, communication, quality, risk evaluation, time frame, integration and the total project management process. In the event that planning is not done properly by the relevant stakeholders the likelihood of failure in projects increases. Understanding the root causes of failure provides the key elements that contribute to adequate methods of implementing corrective actions. This thesis will add value to the project management process as it will equip project managers to understand the main causes and consequences of delays in project execution and to formulate corrective actions in order to prevent delays in future. This thesis points out underlying issues that cause delays; it also attempts to outline the challenges that result in delays and cost escalations; it analyses possible the statements asked in terms of common agreements towards the statements and recommend possible solutions that may remedy delays and avoid cost escalation issues during the execution phase of the projects in turnarounds or shutdown environments. The major findings of this study identify poor communication, repetition of tasks, resource allocation, scope change, procurement process management, inadequate planning and budget estimates as major contributors to delays and cost escalation during project execution – these issues also result in cost escalation during project execution in turnarounds. It is recommended that Engen Refinery put some means together to improve in the above-mentioned issues

A Change Execution System for Enterprise Services with Compensation Support

Modern enterprises rely on a distributed IT infrastructure to execute their business processes, adopting Service Oriented Architectures in order to improve the flexibility and ease of adaptation of their functions. Nowadays this is a vital characteristic, as the increased competition forces companies to continuously evolve and adapt. SOA applications must be supported by management and deployment systems, which have to continuously apply modifications to the distributed infrastructure. This article presents a modelbased solution for automatically applying change plans to heterogeneous enterprise managed environments. The proposed solution uses models which describe in an abstract language the changes that need to be applied to the environment, and executes all the required operations to the specific managed elements. Also, to ensure that the environment ends in a stable state, compensation for previously executed operations is supported. The validation results from a case study taken from the banking domain are also presented here

A planning approach to the automated synthesis of template-based process models

The design-time specification of flexible processes can be time-consuming and error-prone, due to the high number of tasks involved and their context-dependent nature. Such processes frequently suffer from potential interference among their constituents, since resources are usually shared by the process participants and it is difficult to foresee all the potential tasks interactions in advance. Concurrent tasks may not be independent from each other (e.g., they could operate on the same data at the same time), resulting in incorrect outcomes. To tackle these issues, we propose an approach for the automated synthesis of a library of template-based process models that achieve goals in dynamic and partially specified environments. The approach is based on a declarative problem definition and partial-order planning algorithms for template generation. The resulting templates guarantee sound concurrency in the execution of their activities and are reusable in a variety of partially specified contextual environments. As running example, a disaster response scenario is given. The approach is backed by a formal model and has been tested in experiment

QoS-Aware Middleware for Web Services Composition

The paradigmatic shift from a Web of manual interactions to a Web of programmatic interactions driven by Web services is creating unprecedented opportunities for the formation of online Business-to-Business (B2B) collaborations. In particular, the creation of value-added services by composition of existing ones is gaining a significant momentum. Since many available Web services provide overlapping or identical functionality, albeit with different Quality of Service (QoS), a choice needs to be made to determine which services are to participate in a given composite service. This paper presents a middleware platform which addresses the issue of selecting Web services for the purpose of their composition in a way that maximizes user satisfaction expressed as utility functions over QoS attributes, while satisfying the constraints set by the user and by the structure of the composite service. Two selection approaches are described and compared: one based on local (task-level) selection of services and the other based on global allocation of tasks to services using integer programming

An agile business process and practice meta-model

Business Process Management (BPM) encompasses the discovery, modelling, monitoring, analysis and improvement of business processes. Limitations of traditional BPM approaches in addressing changes in business requirements have resulted in a number of agile BPM approaches that seek to accelerate the redesign of business process models. Meta-models are a key BPM feature that reduce the ambiguity of business process models. This paper describes a meta-model supporting the agile version of the Business Process and Practice Alignment Methodology (BPPAM) for business process improvement, which captures process information from actual work practices. The ability of the meta-model to achieve business process agility is discussed and compared with other agile meta-models, based on definitions of business process flexibility and agility found in the literature. (C) 2017 The Authors. Published by Elsevier B.V

Planning and Scheduling of Business Processes in Run-Time: A Repair Planning Example

Over the last decade, the efficient and flexible management of business processes has become one of the most critical success aspects. Furthermore, there exists a growing interest in the application of Artificial Intelligence Planning and Scheduling techniques to automate the production and execution of models of organization. However, from our point of view, several connections between both disciplines remains to be exploited. The current work presents a proposal for modelling and enacting business processes that involve the selection and order of the activities to be executed (planning), besides the resource allocation (scheduling), considering the optimization of several functions and the reach of some objectives. The main novelty is that all decisions (even the activities selection) are taken in run-time considering the actual parameters of the execution, so the business process is managed in an efficient and flexible way. As an example, a complex and representative problem, the repair planning problem, is managed through the proposed approach.Ministerio de Ciencia e Innovación TIN2009-13714Junta de Andalucía P08-TIC-0409