Using spreadsheets in production planning in a pharmaceutical company

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementLiving in the technological era, a successful company nowadays is the company that integrates Information Technology (IT) with its business. Otherwise, it might face a huge risk of not being able to survive in today’s market against the huge competition that is highly influenced by IT. However, integrating IT with business is not so simple due to several factors, namely: the available resources, choosing the right solution, top management support, time constraints, and finally achieving the proper user training and adoption. It is obviously not so wise to keep on waiting until all these obstacles are solved when there is a possibility of using some of the available resources such as Microsoft Office tools that might ease several processes of the business until the needed system is implemented and used. In a supply chain, as a supplier or a manufacturer, production usually follows a production plan that is typically created by the supply planning department. A production plan relies on a demand forecast, whereas a demand forecast usually relies on historical data, but the market demand changes and a forecast does not always match the demand, so whenever there is a change in the forecast, production plans are updated accordingly (Graves, 2011). Therefore, if we are looking to optimize the supply chain, it is necessary to build a strong relationship between the supply chain partners because their collaboration becomes vital in such a scenario. This collaboration means that the partners of the supply chain must share their information with each other (Groznik & Maslaric, 2012). Such information can be about the inventory stock levels of the customer towards the supplier which helps in optimizing the Reorder Level that is defined as “the point at which the company will reorder stock” (Meng, 2006), resulting in creating more successful production plans that matches the market demand. However, these processes can hardly be done and managed manually, theyactually require the help of an IT system that is integrated with the supply chain for achieving the expected results. Aligning IT with the supply chain and using e-business to manage the relationship between suppliers and customers can lower costs, this is due to the fact that IT can contribute in supporting the collaboration and coordination through an easy way of information sharing between the partners of the supply chain (Auramo, Kauremaa, & Tanskanen, 2005). Moreover, using IT in a supply chain does not necessarily need to be costly or difficult to use; insteadspreadsheets for instance can be used for Inventory Planning that is defined as “figuring out what your inventory should be (not counting what you have)” (Estep, 2012). Even though using spreadsheet tools such as Microsoft Office tools does not require purchasing an IT system, it is still considered a type of integrating IT with a business process that can significantly improve the supply chain

Tackling Dierent Business Process Perspectives

Business Process Management (BPM) has emerged as a discipline to design, control, analyze, and optimize business operations. Conceptual models lie at the core of BPM. In particular, business process models have been taken up by organizations as a means to describe the main activities that are performed to achieve a specific business goal. Process models generally cover different perspectives that underlie separate yet interrelated representations for analyzing and presenting process information. Being primarily driven by process improvement objectives, traditional business process modeling languages focus on capturing the control flow perspective of business processes, that is, the temporal and logical coordination of activities. Such approaches are usually characterized as \u201cactivity-centric\u201d. Nowadays, activity-centric process modeling languages, such as the Business Process Model and Notation (BPMN) standard, are still the most used in practice and benefit from industrial tool support. Nevertheless, evidence shows that such process modeling languages still lack of support for modeling non-control-flow perspectives, such as the temporal, informational, and decision perspectives, among others. This thesis centres on the BPMN standard and addresses the modeling the temporal, informational, and decision perspectives of process models, with particular attention to processes enacted in healthcare domains. Despite being partially interrelated, the main contributions of this thesis may be partitioned according to the modeling perspective they concern. The temporal perspective deals with the specification, management, and formal verification of temporal constraints. In this thesis, we address the specification and run-time management of temporal constraints in BPMN, by taking advantage of process modularity and of event handling mechanisms included in the standard. Then, we propose three different mappings from BPMN to formal models, to validate the behavior of the proposed process models and to check whether they are dynamically controllable. The informational perspective represents the information entities consumed, produced or manipulated by a process. This thesis focuses on the conceptual connection between processes and data, borrowing concepts from the database domain to enable the representation of which part of a database schema is accessed by a certain process activity. This novel conceptual view is then employed to detect potential data inconsistencies arising when the same data are accessed erroneously by different process activities. The decision perspective encompasses the modeling of the decision-making related to a process, considering where decisions are made in the process and how decision outcomes affect process execution. In this thesis, we investigate the use of the Decision Model and Notation (DMN) standard in conjunction with BPMN starting from a pattern-based approach to ease the derivation of DMN decision models from the data represented in BPMN processes. Besides, we propose a methodology that focuses on the integrated use of BPMN and DMN for modeling decision-intensive care pathways in a real-world application domain

Adaptive Time- and Process-Aware Information Systems

For the digitized enterprise the proper handling of the temporal aspects of its business processes is vital. Delivery times, appointments and deadlines must be met, processing times and durations be monitored, and optimization objectives shall be pursued. However, contemporary Process-Aware Information Systems (PAISs)--the go-to solution for the computer-aided support of business processes—still lack a sophisticated support of the time perspective. Hence, there is a high demand for a more profound support of temporal aspects in PAISs. Accordingly, both the specification and the operational support of temporal aspects constitute fundamental challenges for the further development and dissemination of PAISs. The aim of this thesis is to propose a framework for supporting the time perspective of business processes in PAISs. As PAISs enable the design, execution and evolution of business processes, the designated framework must support these three fundamental phases of the process life cycle. The ATAPIS framework proposed by this thesis essentially comprises three major com-ponents. First, a universal and comprehensive set of time patterns is provided. Respective time patterns represent temporal concepts commonly found in business processes and are based on empirical evidence. In particular, they provide a universal and comprehensive set of notions for describing temporal aspects in business processes. Moreover, a precise formal semantics for each of the time patterns is provided based on an in-depth analysis of a large set of real-world use cases. Respective formal semantics enable the proper integration of the time patterns into PAISs. In turn, the latter will allow for the specification of time-aware process schemas. Second, a generic framework for implementing the time patterns based on their formal semantics is developed. The framework and its techniques enable the verification of time-aware process schemas regarding their temporal consistency, i. e., their ability to be successfully executed without violating any of their temporal constraints. Subsequently, the framework is extended to consider advanced aspects like the contingent nature of activity durations and alternative execution paths as well. Moreover, an algorithm as well as techniques for executing and monitoring time-aware process instances in PAISs is provided. Based on the presented concepts, it becomes possible to ensure that a time-aware process instance may be executed without violating any of its temporal constraints. Third, a set of change operations for dynamically modifying time-aware process instances during run time is suggested. Respective change operations ensure that a modified time-aware process instance remains temporally consistent after the respective modification. Moreover, to reduce the complexity involved when applying multiple change operations a sophisticated approximation-based technique is presented. Overall, the developed change operations allow providing the flexibility required by business processes in practice. Altogether, the ATAPIS framework provides fundamental concepts, techniques and algorithms for integrating the time perspective into PAISs. As beauty of this framework the specification, execution and evolution of business processes is supported by an integrated approach

Discovery and Evaluation of Coordination Patterns for Business Processes in many-to-many Relationships

Today, organisations use process-oriented systems to manage and automate the enactment of their business processes. The cornerstone artifact is the process model, which at design-time is used to describe the steps that need to be fulfilled in order to reach a business goal. At run-time, the process model is executed and process instances are created. The existing modelling approaches are based on three main paradigms: the more traditional activity-centric paradigm, the case handling paradigm and the more recent data-centric paradigm. Process models can be classified into monolithic and interacting process models. Monolithic process models are predominantly created in the activity-centric and case-handling paradigm. In a monolithic process model, all the involved resources and activities are contained in one vast model. In monolithic process models, interactions occur between the different partners involved in a cross-organisational setting which exchange messages with one another. Interacting process models are prevalent in the data-centric paradigm. In interacting process models, interdependent processes interact with one another such that on a meta-level a composite business process is achieved. In both types of models, interactions between interrelated processes need to be properly coordinated such that a common business objective can be reached. Handling the complexity generated by highly interconnected scenarios, involving hundreds of processes, is a challenge in business process management. Process management systems for such collaborations must be capable of handling both synchronous and asynchronous process interactions. In the context of process management systems, different pattern catalogues such as the Service Interaction Pattern or Correlation Pattern have been used for describing fundamental types of interactions that repeatedly arise during business process modelling. Yet, until now, none of the existing pattern catalogues has explicitly tackled the interactions of heterogeneous business processes in a many-to-many relationship setting. Furthermore, the existing pattern catalogues for the interaction-perspective are not paradigm independent, but mainly focus on the activity-centric paradigm. For modelling multiple interacting processes with different dependency constraints, a collection of patterns that explicitly describes interactions among processes in different types of relationships, in a paradigm-independent manner, is required. This thesis proposes a catalogue of patterns, named the Process Coordination Patterns, describing process interactions in a one-to-many and many-to-many relationship setting. In the developed pattern catalogue, the discovered seven patterns are illustrated by abstracting from any specific paradigm. The PCPs may be used as guidance for evaluating the degree to which existing approaches capture more complex process interactions. In this thesis, the proposed pattern catalogue is put into practice by evaluating the degree to which two modelling approaches, based on different paradigms, can support the seven Process Coordination Patterns