Author supplied Business rules play a critical role in an organization’s daily activities. With the increased use of business rules (solutions) the interest in modelling guidelines that address the manageability of business rules has increased as well. However, current research on modelling guidelines is mainly based on a theoretical view of modifications that can occur to a business rule set. Research on actual modifications that occur in practice is limited. The goal of this study is to identify modifications that can occur to a business rule set and underlying business rules. To accomplish this goal we conducted a grounded theory study on 229 rules set, as applied from March 2006 till June 2014, by the National Health Service. In total 3495 modifications have been analysed from which we defined eleven modification categories that can occur to a business rule set. The classification provides a framework for the analysis and design of business rules management architectures.
De markt voor Business Process Management (BPM) software groeit razend snel. Voor 2010 wordt er een marktomvang voorspeld van tussen de 1 tot 6 miljard dollar, dit betekend dat deze markt sinds 2005 meer dan verdubbeld is. BPM krijgt ook in toenemende mate publiciteit in de markt echter dan gaat het veelal om wat BPM nu precies wel en niet is en niet over hoe het toegepast kan worden. Hetzelfde geldt voor BPM software, beter bekend als Business Process Management Systemen (BPMS). Het onderzoek beschreven in dit proefschrift focust op BPMS, het ontstaan, waar het naartoe gaat en wat er allemaal komt kijken bij de invoering en het gebruik ervan. De hoofdonderzoeksvraag in dit proefschrift is: Welke factoren en competenties bepalen het succes van de implementatie van Business Process Management Systemen in een specifieke situatie? Centraal in dit proefschrift staan de volgende onderzoeksvragen: 1. Wat zijn de succes factoren bij de implementatie van Business Process Management Systemen? 2. Welke competenties hebben stakeholders in een Business Process Management Systeem implementatie project nodig? 3. Hoe ziet een Business Process Management Systeem implementatie methodiek eruit welke rekening houdt met de omgevingsfactoren van een organisatie?
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We give a refinement of the well known business model canvas by Osterwalder and Pigneur by splitting the basic blocks into further subblocks to reduce confusion and increase its expressive power. The splitting is used in an online tool which in addition comes with a set of questions to further structure the business modelling process and help doing thought experiments.
In order to stay competitive and respond to the increasing demand for steady and predictable aircraft turnaround times, process optimization has been identified by Maintenance, Repair and Overhaul (MRO) SMEs in the aviation industry as their key element for innovation. Indeed, MRO SMEs have always been looking for options to organize their work as efficient as possible, which often resulted in applying lean business organization solutions. However, their aircraft maintenance processes stay characterized by unpredictable process times and material requirements. Lean business methodologies are unable to change this fact. This problem is often compensated by large buffers in terms of time, personnel and parts, leading to a relatively expensive and inefficient process. To tackle this problem of unpredictability, MRO SMEs want to explore the possibilities of data mining: the exploration and analysis of large quantities of their own historical maintenance data, with the meaning of discovering useful knowledge from seemingly unrelated data. Ideally, it will help predict failures in the maintenance process and thus better anticipate repair times and material requirements. With this, MRO SMEs face two challenges. First, the data they have available is often fragmented and non-transparent, while standardized data availability is a basic requirement for successful data analysis. Second, it is difficult to find meaningful patterns within these data sets because no operative system for data mining exists in the industry. This RAAK MKB project is initiated by the Aviation Academy of the Amsterdam University of Applied Sciences (Hogeschool van Amsterdan, hereinafter: HvA), in direct cooperation with the industry, to help MRO SMEs improve their maintenance process. Its main aim is to develop new knowledge of - and a method for - data mining. To do so, the current state of data presence within MRO SMEs is explored, mapped, categorized, cleaned and prepared. This will result in readable data sets that have predictive value for key elements of the maintenance process. Secondly, analysis principles are developed to interpret this data. These principles are translated into an easy-to-use data mining (IT)tool, helping MRO SMEs to predict their maintenance requirements in terms of costs and time, allowing them to adapt their maintenance process accordingly. In several case studies these products are tested and further improved. This is a resubmission of an earlier proposal dated October 2015 (3rd round) entitled ‘Data mining for MRO process optimization’ (number 2015-03-23M). We believe the merits of the proposal are substantial, and sufficient to be awarded a grant. The text of this submission is essentially unchanged from the previous proposal. Where text has been added – for clarification – this has been marked in yellow. Almost all of these new text parts are taken from our rebuttal (hoor en wederhoor), submitted in January 2016.
