Toward joint Medical Logistics 2010 and beyond: process innovation and redesign of Class VIII supply chain at a medical logistics company

The purpose of this thesis is to evaluate current Class VIII supply chain procedures at a U.S. Medical Logistics Company (Med Log Co), process map the "as is" baseline process and propose possible "to be" process redesign alternatives that will possibly improve efficiency and produce long-term cost savings. To perform this analysis, the 1st Med Log Co at Camp Pendleton, CA was chosen. The assessment of their "as is" process includes a historical background on medical logistics within the Department of Defense, a comprehensive material logistics literature review, site visits, personnel interviews, process mapping of the baseline "as is" process, and proposal of two redesign alternatives for the "to be" process. A comprehensive analysis was conducted using Thomas Davenport's Process Innovation Framework and quantitative measurements were obtained using the Knowledge-based Organizational Process Redesign (KOPeR) methodology to diagnosis existing pathologies. KOPeR measurements indicate that the 1st Med Log Co's existing "as is" process is a fragmented, mostly manual procurement process that can be innovated now using information technology as a process enabler. Our results indicate that by formally injecting the use of electronic mail and shared databases into the "as is" procurement process an immediate impact can be realized. Further efficiency and cost savings can be accomplished by coupling the injection of information technology with a web- based end-to-end procurement process that assigns a case manager to the "to be" process.http://www.archive.org/details/towardjointmedic00auguMajor, United States Marine CorpsLieutenant, United States NavyApproved for public release; distribution is unlimited

Improving Data-Driven Decision Making through Human-Centered Knowledge Sharing

This research focuses on human-centered knowledge sharing within data-driven decision-making processes enabled by advanced analytics. The paper describes an exploratory study of an innovative approach to ongoing improvement of complex data-driven decision making processes found in a large retail distribution company by considering a complex interplay of business intelligence (BI) /business analytics, business processes and human-centered knowledge management. Using the relevant IS frameworks as analytical lens the paper investigates the evolving relationship between decision-making and decision-support technology, as well as the relationship among information, decisions and the corresponding business processes in this context. The most important finding of this research is in identification of human-centered knowledge sharing as the key success factor for ongoing improvement of BI-enabled decision making in the case organisation, rather than complex technology. This in turn indicates the significance of various organisational factors, including carefully designed and implemented human-resource (HR) strategies to encourage knowledge sharing among decision makers using advanced analytics systems. Finally, this paper also confirms the latest industry reports that more mature analytical organisations are looking beyond technology and focusing on business-related issues as the next source of competitive advantage, as it was the case with our chosen organisation

Principles in Patterns (PiP) : Project Evaluation Synthesis

Evaluation activity found the technology-supported approach to curriculum design and approval developed by PiP to demonstrate high levels of user acceptance, promote improvements to the quality of curriculum designs, render more transparent and efficient aspects of the curriculum approval and quality monitoring process, demonstrate process efficacy and resolve a number of chronic information management difficulties which pervaded the previous state. The creation of a central repository of curriculum designs as the basis for their management as "knowledge assets", thus facilitating re-use and sharing of designs and exposure of tacit curriculum design practice, was also found to be highly advantageous. However, further process improvements remain possible and evidence of system resistance was found in some stakeholder groups. Recommendations arising from the findings and conclusions include the need to improve data collection surrounding the curriculum approval process so that the process and human impact of C-CAP can be monitored and observed. Strategies for improving C-CAP acceptance among the "late majority", the need for C-CAP best practice guidance, and suggested protocols on the knowledge management of curriculum designs are proposed. Opportunities for further process improvements in institutional curriculum approval, including a re-engineering of post-faculty approval processes, are also recommended

Dynamic Knowledge Support Model for Decision-Making and Sustainable Growth : An Empirical Study

Birinder S. Sandhawalia & Darren Dalcher, ‘Dynamic Knowledge Support Model for Decision-Making and Sustainable Growth: An Empirical Study’, Group Decision and Negotiation, Vol. 24 (5): 803-823, first published online 26 August 2014. The final publication is available at Springer via doi: 10.1007/s10726-014-9413-7. © Springer Science + Business Media Dordrecht 2014An effective knowledge-centric approach requires that tacit and explicit knowledge are mobilised, integrated, and made available to support collaboration between team members. Most knowledge management (KM) frameworks lay an emphasis on managing explicit knowledge by focussing on the processes of capture, storage, retrieval, transfer and application. Tacit knowledge, on the other hand, needs the key mechanisms of interaction and feedback for effective sharing and use. The paper presents a model validated during a case study conducted at one of the world’s leading software organisations. The model addresses the need to make both tacit and explicit knowledge available and accessible for effective decision-making and sustainable development, and improved environmental impact. It makes use of the mechanisms of interaction and feedback to facilitate the flow and availability of tacit knowledge within organisational practices and routines. The paper establishes that knowledge flows between functional areas and supports tasks and activities of an organisation’s development effort. The findings have longer-term implications regarding organisations’ ability to manage context, provide feedback and facilitate interaction, and therefore build upon their existing knowledge resources to improve decision-making and sustainabilityPeer reviewe

Practices of knowledge intensive process management: quantitative insights

Purpose – In contemporary businesses, the importance of knowledge workers and the knowledge intensive business processes (KIBPs) is ever increasing, yet they seem very hard to control and manage. The purpose of this paper is to grasp the specific characteristics of KIBPs and how they differ from non‐knowledge intensive business processes (non‐KIBP), also to question how organizations are using business process management (BPM) to manage and improve KIBPs. The differences in maturity and effectiveness of both types of processes are also evaluated. Design/methodology/approach – Data for this research were collected through an online survey. The survey was designed based on a previously conducted exploratory study with semi‐structured interviews as well as the literature. The target group was BPM practitioners and the final sample included 98 respondents. Due to non‐normality, the analyses were conducted with non‐parametric tests. The research questions were analysed using Mann‐Whitney U test and Spearman's correlations. Findings – It was found that KIBP and non‐KIBP have clearly different characteristics, such as the level of complexity, repeatability and creativity required. Also it was found that these processes are not managed or improved differently than non‐KIBPs, and suggest that organizations need to take these differences into consideration while managing and improving these processes. Furthermore, the results suggest that applying methodologies that aim to provide operational improvements may not necessarily produce the best results for KIBPs. Originality/value – The paper answers a call for further development of the body of knowledge on knowledge‐intensive business processes, a rapidly emerging field of interest for BPM practitioners, where a clear gap in literature exists

Dynamic process modelling for business engineering and information systems evaluation

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This research is concerned with the pre-implementation evaluation of investments in Information Systems (IS). IS evaluation is important as organisations need to assess the financial justifiability of business change proposals that include (but usually are not limited to) the introduction of IS applications. More specifically, this research addresses the problem of benefits assessment within IS evaluation. We contend that benefits assessment should not be performed at the level of the IS application, as most extant evaluation methods advocate. Instead, to study the dynamics and the interactions of the IS applications with their surrounding environment, we propose to adopt the business process as the analytic lens of evaluation and to assess the impacts of IS on organisational, rather than on technical, performance indicators. Drawing on these propositions, this research investigates the potential of dynamic process modelling (via discrete-event simulation) as a facilitator of IS evaluation. We argue that, in order to be effective evaluation tools, business process models should be able to explicitly incorporate the effects of IS introduction on business performance, an issue that is found to be under-researched in previous literature. The above findings serve as the central theme for the development of a design theory of IS evaluation by simulation. The theory provides prescriptive elements that refer both to the design products of the evaluation and the design process by which these products can come into reality. The theory draws on a set of kernel theories from the business engineering domain and proposes a set of meta-requirements that should be satisfied by business process models, a meta-design structure that meets these requirements, and a design method that provides guidance in applying the theoretical propositions in practice. The design theory is developed and empirically tested by means of two real-life case studies. The first study is used to complement the findings of a literature review and to drive the development of the design theory's components, while the second study is employed to validate and further enhance the theory's propositions. The research results support the arguments for simulation-assisted IS evaluation and demonstrate the contribution of the design theory to the field

AI in medical diagnosis : AI prediction & human judgment

AI has long been regarded as a panacea for decision-making and many other aspects of knowledge work; as something that will help humans get rid of their shortcomings. We believe that AI can be a useful asset to support decision-makers, but not that it should replace decision-makers. Decision-making uses algorithmic analysis, but it is not solely algorithmic analysis; it also involves other factors, many of which are very human, such as creativity, intuition, emotions, feelings, and value judgments. We have conducted semi-structured open-ended research interviews with 17 dermatologists to understand what they expect from an AI application to deliver to medical diagnosis. We have found four aggregate dimensions along which the thinking of dermatologists can be described: the ways in which our participants chose to interact with AI, responsibility, 'explainability', and the new way of thinking (mindset) needed for working with AI. We believe that our findings will help physicians who might consider using AI in their diagnosis to understand how to use AI beneficially. It will also be useful for AI vendors in improving their understanding of how medics want to use AI in diagnosis. Further research will be needed to examine if our findings have relevance in the wider medical field and beyond

Reengineering BPR: a critical exploration

Purpose and aims of the thesis: This thesis critically reviews the current BPR literature through the perspective of the systemic/holistic management thinking, in such a way as to bring the study of BPR into a new era. Central to this holistic type of thinking are the concepts of Processes, Radicality, IT/IS, Culture and Human Element awareness: these concepts are used to explore core publications in reengineering literature. More specifically the aims of the thesis are to (i) explain why BPR needs redefining, (ii) redefine it as a holistic activity, (iii) provide guidelines to do that and also (iv) show the feasibility of this approach.Research Method: For the achievement of the above aims, a combination of research methodology strategies and techniquesw as used.T hesei nclude a documentary review approach and a comparative analysis for gathering and disseminating the data. These were complemented by case study material, which is used to assess the plausibility of the suggestions made in this particular thesis.Findings: While exploring the notion of BPR it was identified that (i) the notion has no universally accepted definition, (ii) largely the definitions and numerous core reengineering readings (Davenport 1993, Johansson et al.1993, etc.) give emphasis to different extreme orientations (e.g., IT oriented, processes oriented) and thereby attract negative criticism (Jones 1996, Case 1999), (iii) there is no code of practice (no formal guidelines) when practising reengineering, and largely (iv) there is a great amount of inconsistency between what the examined BPR authors say they do, and what they actually do in practice (e. g., Hammer and Champy 1993).Recommendations: Recognising the novel link between a number of major fields of activity (Processes, Radicality, IT/IS, Culture and Human Element), enabled a new holistic definition and a new form of guidelines to emerge, and be operationalised; that is, for this author to present a set of theoretical and practical ways of improving the BPR managerial tool. Such guidance, though, is not intended to be sterile and staid. Indeed, this guidance will itself incorporate critical thinking around the issues involved in an intervention like BPR, by the further enhancement of multi disciplinary discourse about organisational learning and awareness. It is concluded that this set of recommended guidelines could provide a framework for an enriched, holistic and successful BPR initiative

Novel analysis and modelling methodologies applied to pultrusion and other processes

Often a manufacturing process may be a bottleneck or critical to a business. This thesis focuses on the analysis and modelling of such processest, to both better understand them, and to support the enhancement of quality or output capability of the process. The main thrusts of this thesis therefore are: To model inter-process physics, inter-relationships, and complex processes in a manner that enables re-exploitation, re-interpretation and reuse of this knowledge and generic elements e.g. using Object Oriented (00) & Qualitative Modelling (QM) techniques. This involves the development of superior process models to capture process complexity and reuse any generic elements; To demonstrate advanced modelling and simulation techniques (e.g. Artificial Neural Networks(ANN), Rule-Based-Systems (RBS), and statistical modelling) on a number of complex manufacturing case studies; To gain a better understanding of the physics and process inter-relationships exhibited in a number of complex manufacturing processes (e.g. pultrusion, bioprocess, and logistics) using analysis and modelling. To these ends, both a novel Object Oriented Qualitative (Problem) Analysis (OOQA) methodology, and a novel Artificial Neural Network Process Modelling (ANNPM) methodology were developed and applied to a number of complex manufacturing case studies- thermoset and thermoplastic pultrusion, bioprocess reactor, and a logistics supply chain. It has been shown that these methodologies and the models developed support capture of complex process inter-relationships, enable reuse of generic elements, support effective variable selection for ANN models, and perform well as a predictor of process properties. In particular the ANN pultrusion models, using laboratory data from IKV, Aachen and Pera, Melton Mowbray, predicted product properties very well