ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

Current trends on ICT technologies for enterprise information s²ystems

The proposed paper discusses the current trends on ICT technologies for Enterprise Information Systems. The paper starts by defining four big challenges of the next generation of information systems: (1) Data Value Chain Management; (2) Context Awareness; (3) Interaction and Visualization; and (4) Human Learning. The major contributions towards the next generation of information systems are elaborated based on the work and experience of the authors and their teams. This includes: (1) Ontology based solutions for semantic interoperability; (2) Context aware infrastructures; (3) Product Avatar based interactions; and (4) Human learning. Finally the current state of research is discussed highlighting the impact of these solutions on the economic and social landscape

Design and Planning of Manufacturing Networks for Mass Customisation and Personalisation: Challenges and Outlook

AbstractManufacturers and service providers are called to design, plan and operate globalized manufacturing networks, addressing to challenges such as ever-decreasing lifecycles and increased product complexity. These factors, caused primarily by mass customisation and demand volatility, generate a number of issues related to the design and planning of manufacturing systems and networks, which are not holistically tackled in industrial and academic practices. The mapping of production performance requirements to process and production planning requires automated closed-loop control systems, which current systems fail to deliver. Technology-based business approaches are an enabler for increased enterprise performance. Towards that end, the issues discussed in this paper focus on challenges in the design and planning of manufacturing networks in a mass customization and personalization landscape. The development of methods and tools for supporting the dynamic configuration and optimal routing of manufacturing networks and facilities under cost, time, complexity and environmental constraints to support product-service personalization are promoted

Multi Agent Systems in Logistics: A Literature and State-of-the-art Review

Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?†Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution.supply chain;MAS;multi agent systems

Research in Business Process Management: A bibliometric analysis

It contains several growing subtopics such as process mining, process flexibility and process compliance. BPM is also highly relevant for numerous related fields, such as Business Intelligence, ERP systems or Knowledge Management. The growing number of publications and the variety of topics in BPM make it useful to apply bibliometric methods on this scientific field. With bibliometric methods, topical clusters, essential authors and the relationships between them can be discovered. In this work, the BibTechMon software from the Austrian Institute of Technology is utilized to perform the bibliometric analyses. As a novelty for the work with BibTechMon, data from Google Scholar is used as the basis of the analyses. The nature of Google Scholar data differs significantly from the data of other scientific databases. These differences lead to changes on how the bibliometric analyses can be performed. After these changes have been assessed, several bibliometric analyses in the BPM field and related fields are performed. As a result of these analyses, diverse topical clusters in BPM and its related fields could be discovered. Additionally, important authors for each cluster and for the BPM field as a whole were determined. In order to evaluate the results of the bibliometric analyses, I conducted an interview on BPM with Professor Reichert, who is an active researcher in the field. Subsequently, his statements are compared with the results of the bibliometric analyses and the match between the bibliometric analyses and his statements is assessed

Business process modelling in ERP implementation literature review

Business processes are the backbone of any Enterprise Resource Planning (ERP) implementation. Business process modelling (BPM) has become essential for modern, process driven enterprises due to the vibrant business environments. As a consequence enterprises are dealing with a substantial rate of organizational and business processes change. Business process modelling enables a common understanding and analysis of the business processes, which is the first step in every ERP implementation methodology (blueprint phase). In order to represent enterprise processes models in an accurate manner, it is paramount to choose a right business process modeling technique and tool. The problem of many ERP projects rated as unsuccessful is directly connected to a lack of use of business process models and notations during the blueprint phase. Also, blueprint implementation phase is crucial in order to fit planned processes in an organization with processes implemented in the solution. However, business analysts and ERP implementation professionals have substantial difficulties to navigate through a large number of theoretical models and representational notations that have been proposed for business process modeling (BPM). As the availability of different business process modeling references is huge, it is time consuming to make review and classification of all modeling techniques. Therefor, in reality majority of ERP implementations blueprint documents have no business process modeling included in generating blueprint documents. Choosing the right model comprise the purpose of the analysis and acquaintance of the available process modelling techniques and tools. The number of references on business modelling is quit large, so it is very hard to make a decision which modeling notation or technique to use. The main purpose of this paper is to make a review of business process modelling literature and describe the key process modelling techniques. The focus will be on all business process modeling that could be used in ERP implementations, specifically during the blueprint phase of the implementation process. Detailed review of BPM (Business process modeling) theoretical models and representational notations, should assist decision makers and ERP integrators in comparatively evaluating and selecting suitable modeling approaches

From strategy to operations and vice-versa: a bridge that needs an Island

The Information Systems support particularly for Tactical Management is not an explicit or distinct term. There are many concepts and artifacts that are providing contemporary foundations for Information systems in the companies, both in theory and in practice. We tried to analyze different approaches, in order to determine their support specifically for tactical management. Out of this attempt, the realization is that these seemingly overarching bridges from Operations to Strategy and vice-versa appear to be overshooting an important island - the tactical management level, particularly in recognizing its distinct characteristics to be served with adjusted concepts and solutions. We see tactical management as the managerial function that implements strategies, by deploying and utilizing specific resources from the operational level in order to gain that specific competitive advantage prescribed in the strategy. The diversity of approaches and tools is provided for the strategic and overwhelmingly for operational management issues. This theoretical research is analyzing the specifics of the Sense-and-Respond Framework on a tactical level towards perfecting the sensing part of it (in terms of sustaining "low latency" (instead of operational "no latency") and striving for tactical need for "right-time" (instead of the current and hot operational "real-time") information), and how it is being closed in theory and practice on a strategic, tactical and operational level with 'endings'. Also, the tactical management characteristic of working in unpredicted environment and needing high adaptability, requires involvement of concepts and approaches that provide adaptability such as, in our opinion, the Sense-and-Respond managerial concept and the SIDA loop. To some extent, tactical management is being assimilated either by strategy or by operations, as this research confirms. Hopefully, we will result with increased perceptiveness that tactical management needs special theoretical and practical focus and output propositions. The specific sensing and interpreting, deciding and acting, in the role of a tactical manager is neither only automatic, data-capturing process nor a person-independent or company-independent one. If, and after this viewpoint is shared, much more efforts will be streamlined in the tactical management "how" to do "what" is expected, on theoretical and on practical level

Handbook of Computational Intelligence in Manufacturing and Production Management

Artificial intelligence (AI) is simply a way of providing a computer or a machine to think intelligently like human beings. Since human intelligence is a complex abstraction, scientists have only recently began to understand and make certain assumptions on how people think and to apply these assumptions in order to design AI programs. It is a vast knowledge base discipline that covers reasoning, machine learning, planning, intelligent search, and perception building. Traditional AI had the limitations to meet the increasing demand of search, optimization, and machine learning in the areas of large, biological, and commercial database information systems and management of factory automation for different industries such as power, automobile, aerospace, and chemical plants. The drawbacks of classical AI became more pronounced due to successive failures of the decade long Japanese project on fifth generation computing machines. The limitation of traditional AI gave rise to development of new computational methods in various applications of engineering and management problems. As a result, these computational techniques emerged as a new discipline called computational intelligence (CI)