Making charity effectiveness transparent: building a stakeholder-focused framework of reporting

Effectiveness in achieving mission is fundamental to evaluating charity performance, and is of central concern to stakeholders who fund, regulate and otherwise engage with such organisations. Exploring the meaning of transparency in the context of stakeholder engagement, and utilising previous research and authoritative sector discussion, this paper develops a novel framework of transparent, stakeholder-focused effectiveness reporting. It is contended that such reporting can assist the charity sector in discharging accountability, gaining legitimacy, and in sharpening mission-centred managerial decision making. Then applying this to UK charities’ publicly-available communications, it highlights significant challenges and weaknesses in current effectiveness reporting.

The role of Lean at the interface with between operations management and applied services within a large aerospace organisation: a boundary spanning perspective

Increased complexity in large design and manufacturing organisations requires improvements at the operations management (OM)–applied service (AS) interface areas to improve project effectiveness. The aim of this paper is explore the role of Lean in improving the longitudinal efficiency of the OM–AS interface within a large aerospace organisation using Lean principles and boundary spanning theory. The methodology was an exploratory longitudinal case approach including exploratory interviews (n = 21), focus groups (n = 2), facilitated action-research workshops (n = 2) and two trials or experiments using longitudinal data involving both OM and AS personnel working at the interface. The findings draw upon Lean principles and boundary spanning theory to guide and interpret the findings. It was found that misinterpretation, and forced implementation, of OM-based Lean terminology and practice in the OM–AS interface space led to delays and misplaced resources. Rather both OM and AS staff were challenged to develop a cross boundary understanding of Lean-based boundary (knowledge) objects in interpreting OM requests. The longitudinal findings from the experiments showed that the development of Lean Performance measurements and lean Value Stream constructs was more successful when these Lean constructs were treated as boundary (knowledge) objects requiring transformation over time to orchestrate improved effectiveness and in leading to consistent terminology and understanding between the OM–AS boundary spanning team.

Exploring the effects of a universal classroom management training programme on teacher and child behaviour: a group randomised controlled trial and cost analysis

Teachers frequently struggle to cope with conduct problems in the classroom. The aim of this study was to assess the effectiveness of the Incredible Years Teacher Classroom Management Training Programme for improving teacher competencies and child adjustment. The study involved a group randomised controlled trial which included 22 teachers and 217 children (102 boys and 115 girls). The average age of children included in the study was 5.3 years (standard deviation = 0.89). Teachers were randomly allocated to an intervention group (n = 11 teachers; 110 children) or a waiting-list control group (n = 11; 107 children). The sample also included 63 ‘high-risk’ children (33 intervention; 30 control), who scored above the cut-off (>12) on the Strengths and Difficulties Questionnaire for abnormal socioemotional and behavioural difficulties. Teacher and child behaviours were assessed at baseline and 6 months later using psychometric and observational measures. Programme delivery costs were also analysed. Results showed positive changes in teachers’ self-reported use of positive classroom management strategies (effect size = 0.56), as well as negative classroom management strategies (effect size = −0.43). Teacher reports also highlight improvements in the classroom behaviour of the high-risk group of children, while the estimated cost of delivering the Incredible Years Teacher Classroom Management Training Programme was modest. However, analyses of teacher and child observations were largely non-significant. A need for further research exploring the effectiveness and cost-effectiveness of the Incredible Years Teacher Classroom Management Training Programme is indicated.

The effectiveness of community-based interventions to improve maternal and infant health in the Northeast of Brazil

EMOND, Alan et al. The effectiveness of community-based interventions to improve maternal and infant health in the Northeast of Brazil. Revista Panamericana de Salud Pública/ Pan American Journal of Public Health , v.12, n.2, p.101-110, 2002

Reprint: Learning With a Strategic Management Simulation Q2 Game: A Case Study

The use of simulation games as a pedagogic method is well established though its effective use is context-driven. This study adds to the increasing growing body of empirical evidence of the effectiveness of simulation games but more importantly emphasises why by explaining the instructional design implemented reflecting best practices. This multimethod study finds evidence that student learning was enhanced through the use of simulation games, reflected in the two key themes; simulation games as a catalyst for learning and simulation games as a vehicle for learning. In so doing the research provides one of the few empirically based studies that support simulation games in enhancing learning and, more importantly, contextualizes the enhancement in terms of the instructional design of the curriculum. This research should prove valuable for those with an academic interest in the use of simulation games and management educators who use, or are considering its use. Further, the findings contribute to the academic debate concerning the effective implementation of simulation game-based training in business and management education.

A gestão da informação sob a luz do Enterprise Content Management (ECM): um estudo de caso em uma universidade pública

This work involves the organization and content perspectives on Enterprise Content Management (ECM) framework. The case study at the Federal University of Rio Grande do Norte was based on ECM model to analyse the information management provided by the three main administrative systems: The Integrated Management of Academic Activities (SIGAA), Integrated System of Inheritance, and Contracts Administration (SIPAC) and the Integrated System for Administration and Human Resources (SIGRH). A case study protocol was designed to provide greater reliability to research process. Four propositions were examined in order to reach the specific objectives of identification and evaluation of ECM components from UFRN perspective. The preliminary phase provided the guidelines for the data collection. In total, 75 individuals were interviewed. Interviews with four managers directly involved on systems design were recorded (average duration of 90 minutes). The 70 remaining individuals were approached in random way in UFRN s units, including teachers, administrative-technical employees and students. The results showed the presence of many ECM elements in the management of UFRN administrative information. The technological component with higher presence was "management of web content / collaboration". But initiatives of other components (e.g. email and document management) were found and are in continuous improvement. The assessment made use of eQual 4.0 to examine the effectiveness of applications under three factors: usability, quality of information and offered service. In general, the quality offered by the systems was very good and walk side by side with the obtained benefits of ECM strategy adoption in the context of the whole institution

The evolution and performance of river basin management in the Murray-Darling Basin

We explore bioregional management in the Murray-Darling Basin (MDB) in Australia through the institutional design characteristics of the MDB River Basin Organization (RBO), the actors and organizations who supported and resisted the establishment of the RBO, and the effectiveness of the RBO. During the last 25 years, there has been a major structural reform in the MDB RBO, which has changed from an interstate coordinating body to an Australian government agency. Responsibility for basin management has been centralized under the leadership of the Australian government, and a comprehensive integrated Basin plan has been adopted. The driving forces for this centralization include national policy to restore river basins to sustainable levels of extraction, state government difficulties in reversing overallocation of water entitlements, the millennium drought and its effects, political expediency on the part of the Australian government and state governments, and a major injection of Australian government funding. The increasing hierarchy and centralization of the MDB RBO does not follow a general trend toward multilevel participative governance of RBOs, but decentralization should not be overstated because of the special circumstances at the time of the centralization and the continuing existence of some decentralized elements, such as catchment water plans, land use planning, and water quality. Further swings in the centralization–decentralization pendulum could occur. The MDB reform has succeeded in rebalancing Basin water allocations, including an allocation for the environment and reduced diversion limits. There are some longer term risks to the implementation of reform, including lack of cooperation by state governments, vertical coordination difficulties, and perceived reductions in the accountability and legitimacy of reform at the local level. If implementation of the Basin plan is diverted or delayed, a new institution, the Commonwealth Environmental Water Holder, can play a major role in securing and coordinating environmental water supplies.

Diagnostic Tests and their Application in the Management of Soil- and Water-borne Oomycete Pathogen Species

Oomycete diseases cause significant losses across a broad range of crop and aquaculture commodities worldwide. These losses can be greatly reduced by disease management practices steered by accurate and early diagnoses of pathogen presence. Determinations of disease potential can help guide optimal crop rotation regimes, varietal selections, targeted control measures, harvest timings and crop post-harvest handling. Pathogen detection prior to infection can also reduce the incidence of disease epidemics. Classical methods for the isolation of oomycete pathogens are normally deployed only after disease symptom appearance. These processes are often-time consuming, relying on culturing the putative pathogen(s) and the availability of expert taxonomic skills for accurate identification; a situation that frequently results in either delayed application, or routine ‘blanket’ over-application of control measures. Increasing concerns about pesticides in the environment and the food chain, removal or restriction of their usage combined with rising costs have focussed interest in the development and improvement of disease management systems. To be effective, these require timely, accurate and preferably quantitatve diagnoses. A wide range of rapid diagnostic tools, from point of care immunodiagnostic kits to next generation nucleotide sequencing have potential application in oomycete disease management. Here we review currently-available as well as promising new technologies in the context of commercial agricultural production systems, considering the impacts of specific biotic and abiotic and other important factors such as speed and ease of access to information and cost effectiveness

The effectiveness of community-based interventions to improve maternal and infant health in the Northeast of Brazil

EMOND, Alan et al. The effectiveness of community-based interventions to improve maternal and infant health in the Northeast of Brazil. Revista Panamericana de Salud Pública/ Pan American Journal of Public Health , v.12, n.2, p.101-110, 2002

BUILDING EFFICIENT AND COST-EFFECTIVE CLOUD-BASED BIG DATA MANAGEMENT SYSTEMS

In today’s big data world, data is being produced in massive volumes, at great velocity and from a variety of different sources such as mobile devices, sensors, a plethora of small devices hooked to the internet (Internet of Things), social networks, communication networks and many others. Interactive querying and large-scale analytics are being increasingly used to derive value out of this big data. A large portion of this data is being stored and processed in the Cloud due the several advantages provided by the Cloud such as scalability, elasticity, availability, low cost of ownership and the overall economies of scale. There is thus, a growing need for large-scale cloud-based data management systems that can support real-time ingest, storage and processing of large volumes of heterogeneous data. However, in the pay-as-you-go Cloud environment, the cost of analytics can grow linearly with the time and resources required. Reducing the cost of data analytics in the Cloud thus remains a primary challenge. In my dissertation research, I have focused on building efficient and cost-effective cloud-based data management systems for different application domains that are predominant in cloud computing environments. In the first part of my dissertation, I address the problem of reducing the cost of transactional workloads on relational databases to support database-as-a-service in the Cloud. The primary challenges in supporting such workloads include choosing how to partition the data across a large number of machines, minimizing the number of distributed transactions, providing high data availability, and tolerating failures gracefully. I have designed, built and evaluated SWORD, an end-to-end scalable online transaction processing system, that utilizes workload-aware data placement and replication to minimize the number of distributed transactions that incorporates a suite of novel techniques to significantly reduce the overheads incurred both during the initial placement of data, and during query execution at runtime. In the second part of my dissertation, I focus on sampling-based progressive analytics as a means to reduce the cost of data analytics in the relational domain. Sampling has been traditionally used by data scientists to get progressive answers to complex analytical tasks over large volumes of data. Typically, this involves manually extracting samples of increasing data size (progressive samples) for exploratory querying. This provides the data scientists with user control, repeatable semantics, and result provenance. However, such solutions result in tedious workflows that preclude the reuse of work across samples. On the other hand, existing approximate query processing systems report early results, but do not offer the above benefits for complex ad-hoc queries. I propose a new progressive data-parallel computation framework, NOW!, that provides support for progressive analytics over big data. In particular, NOW! enables progressive relational (SQL) query support in the Cloud using unique progress semantics that allow efficient and deterministic query processing over samples providing meaningful early results and provenance to data scientists. NOW! enables the provision of early results using significantly fewer resources thereby enabling a substantial reduction in the cost incurred during such analytics. Finally, I propose NSCALE, a system for efficient and cost-effective complex analytics on large-scale graph-structured data in the Cloud. The system is based on the key observation that a wide range of complex analysis tasks over graph data require processing and reasoning about a large number of multi-hop neighborhoods or subgraphs in the graph; examples include ego network analysis, motif counting in biological networks, finding social circles in social networks, personalized recommendations, link prediction, etc. These tasks are not well served by existing vertex-centric graph processing frameworks whose computation and execution models limit the user program to directly access the state of a single vertex, resulting in high execution overheads. Further, the lack of support for extracting the relevant portions of the graph that are of interest to an analysis task and loading it onto distributed memory leads to poor scalability. NSCALE allows users to write programs at the level of neighborhoods or subgraphs rather than at the level of vertices, and to declaratively specify the subgraphs of interest. It enables the efficient distributed execution of these neighborhood-centric complex analysis tasks over largescale graphs, while minimizing resource consumption and communication cost, thereby substantially reducing the overall cost of graph data analytics in the Cloud. The results of our extensive experimental evaluation of these prototypes with several real-world data sets and applications validate the effectiveness of our techniques which provide orders-of-magnitude reductions in the overheads of distributed data querying and analysis in the Cloud.

Use of sulfuryl fluoride in the management of strongly phosphine-resistant insect pest populations in bulk grain storages in Australia

Sulfuryl fluoride (SF), an effective structural fumigant, is registered recently as Profume™ for controlling insect pests of stored grains and processed commodities. Information on its effectiveness in disinfestation of bulk grain, however, is limited. The ongoing problem with the strong level of resistance to phosphine has been addressed recently through deployment of SF as a ‘resistance breaker’ in bulk storages in Australia. This paper discusses important results on the efficacy of SF against key phosphine- resistant insect pests, lesser grain borer, Rhyzopertha dominca, red flour beetle, Tribolium castaneum, rice weevil, Sitophilus oryzae and the rusty grain beetle, Cryptolestes ferrugineus. We have established CT (g-hm3) profiles for SF against these insect pests at two temperature regimes 25 and 30°C, that showed that both temperature and exposure period (t) has significant influence on the effectiveness of SF than the concentration. Over a seven days fumigation period, CTs of 800 and 400 g-hm3 achieved complete control of all the target pests, including the most strongly phosphine - resistant species, C. ferrugineus at 25 and 30°C, respectively. Results from four industry scale field trials involving currently registered rate of SF (1500 g-hm3) over 2–14 d exposure period, confirmed its effectiveness in achieving complete control of the target pest species. The assessment of postfumigation grain samples across all the test storages indicated that the reinfestation occurs after three months. Monitoring resistance to phosphine in C. ferrugineus over a six year period (2009–2015), showed a significant reduction in resistant populations after the introduction of SF into the fumigation strategy at problematic storage sites. Overall our research concludes that SF is a good candidate to be used as a ‘resistance breaker’ where phosphine resistance is prevalent.

A generic method of engagement to elicit regional coastal management options

Stakeholder engagement is important for successful management of natural resources, both to make effective decisions and to obtain support. However, in the context of coastal management, questions remain unanswered on how to effectively link decisions made at the catchment level with objectives for marine biodiversity and fisheries productivity. Moreover, there is much uncertainty on how to best elicit community input in a rigorous manner that supports management decisions. A decision support process is described that uses the adaptive management loop as its basis to elicit management objectives, priorities and management options using two case studies in the Great Barrier Reef, Australia. The approach described is then generalised for international interest. A hierarchical engagement model of local stakeholders, regional and senior managers is used. The result is a semi-quantitative generic elicitation framework that ultimately provides a prioritised list of management options in the context of clearly articulated management objectives that has widespread application for coastal communities worldwide. The case studies show that demand for local input and regional management is high, but local influences affect the relative success of both engagement processes and uptake by managers. Differences between case study outcomes highlight the importance of discussing objectives prior to suggesting management actions, and avoiding or minimising conflicts at the early stages of the process. Strong contributors to success are a) the provision of local information to the community group, and b) the early inclusion of senior managers and influencers in the group to ensure the intellectual and time investment is not compromised at the final stages of the process. The project has uncovered a conundrum in the significant gap between the way managers perceive their management actions and outcomes, and community's perception of the effectiveness (and wisdom) of these same management actions.

New developments in UAV remote sensing for pest management and the implications for cotton

Efficient crop monitoring and pest damage assessments are key to protecting the Australian agricultural industry and ensuring its leading position internationally. An important element in pest detection is gathering reliable crop data frequently and integrating analysis tools for decision making. Unmanned aerial systems are emerging as a cost-effective solution to a number of precision agriculture challenges. An important advantage of this technology is it provides a non-invasive aerial sensor platform to accurately monitor broad acre crops. In this presentation, we will give an overview on how unmanned aerial systems and machine learning can be combined to address crop protection challenges. A recent 2015 study on insect damage in sorghum will illustrate the effectiveness of this methodology. A UAV platform equipped with a high-resolution camera was deployed to autonomously perform a flight pattern over the target area. We describe the image processing pipeline implemented to create a georeferenced orthoimage and visualize the spatial distribution of the damage. An image analysis tool has been developed to minimize human input requirements. The computer program is based on a machine learning algorithm that automatically creates a meaningful partition of the image into clusters. Results show the algorithm delivers decision boundaries that accurately classify the field into crop health levels. The methodology presented in this paper represents a venue for further research towards automated crop protection assessments in the cotton industry, with applications in detecting, quantifying and monitoring the presence of mealybugs, mites and aphid pests.

BYGUM – a new tool for BarnYard Grass Understanding and Management

Weed management has become increasingly challenging for cotton growers in Australia in the last decade. Glyphosate, the cornerstone of weed management in the industry, is waning in effectiveness as a result of the evolution of resistance in several species. One of these, awnless barnyard grass, is very common in Australian cotton fields, and is a prime example of the new difficulties facing growers in choosing effective and affordable management strategies. RIM (Ryegrass Integrated Management) is a computer-based decision support tool developed for the south-western Australian grains industry. It is commonly used there as a tool for grower engagement in weed management thinking and strategy development. We used RIM as the basis for a new tool that can fulfil the same types of functions for subtropical Australian cotton-grains farming systems. The new tool, BYGUM, provides growers with a robust means to evaluate five-year rotations including testing the economic value of fallows and fallow weed management, winter and summer cropping, cover crops, tillage, different herbicide options, herbicide resistance management, and more. The new model includes several northernregion- specific enhancements: winter and summer fallows, subtropical crop choices, barnyard grass seed bank, competition, and ecology parameters, and more freedom in weed control applications. We anticipate that BYGUM will become a key tool for teaching and driving the changes that will be needed to maintain sound weed management in cotton in the near future.

Supporting self-management: development and evaluation of a digital resource for adults with asthma

The problem: Around 300 million people worldwide have asthma and prevalence is increasing. Support for optimal self-management can be effective in improving a range of outcomes and is cost effective, but is underutilised as a treatment strategy. Supporting optimum self-management using digital technology shows promise, but how best to do this is not clear. Aim: The purpose of this project was to explore the potential role of a digital intervention in promoting optimum self-management in adults with asthma. Methods: Following the MRC Guidance on the Development and Evaluation of Complex Interventions which advocates using theory, evidence, user testing and appropriate modelling and piloting, this project had 3 phases. Phase 1: Examination of the literature to inform phases 2 and 3, using systematic review methods and focussed literature searching. Phase 2: Developing the Living Well with Asthma website. A prototype (paper-based) version of the website was developed iteratively with input from a multidisciplinary expert panel, empirical evidence from the literature (from phase 1), and potential end users via focus groups (adults with asthma and practice nurses). Implementation and behaviour change theories informed this process. The paper-based designs were converted to the website through an iterative user centred process (think aloud studies with adults with asthma). Participants considered contents, layout, and navigation. Development was agile using feedback from the think aloud sessions immediately to inform design and subsequent think aloud sessions. Phase 3: A pilot randomised controlled trial over 12 weeks to evaluate the feasibility of a Phase 3 trial of Living Well with Asthma to support self-management. Primary outcomes were 1) recruitment & retention; 2) website use; 3) Asthma Control Questionnaire (ACQ) score change from baseline; 4) Mini Asthma Quality of Life (AQLQ) score change from baseline. Secondary outcomes were patient activation, adherence, lung function, fractional exhaled nitric oxide (FeNO), generic quality of life measure (EQ-5D), medication use, prescribing and health services contacts. Results: Phase1: Demonstrated that while digital interventions show promise, with some evidence of effectiveness in certain outcomes, participants were poorly characterised, telling us little about the reach of these interventions. The interventions themselves were poorly described making drawing definitive conclusions about what worked and what did not impossible. Phase 2: The literature indicated that important aspects to cover in any self-management intervention (digital or not) included: asthma action plans, regular health professional review, trigger avoidance, psychological functioning, self-monitoring, inhaler technique, and goal setting. The website asked users to aim to be symptom free. Key behaviours targeted to achieve this include: optimising medication use (including inhaler technique); attending primary care asthma reviews; using asthma action plans; increasing physical activity levels; and stopping smoking. The website had 11 sections, plus email reminders, which promoted these behaviours. Feedback during think aloud studies was mainly positive with most changes focussing on clarification of language, order of pages and usability issues mainly relating to navigation difficulties. Phase 3: To achieve our recruitment target 5383 potential participants were invited, leading to 51 participants randomised (25 to intervention group). Age range 16-78 years; 75% female; 28% from most deprived quintile. Nineteen (76%) of the intervention group used the website for an average of 23 minutes. Non-significant improvements in favour of the intervention group observed in the ACQ score (-0.36; 95% confidence interval: -0.96, 0.23; p=0.225), and mini-AQLQ scores (0.38; -0.13, 0.89; p=0.136). A significant improvement was observed in the activity limitation domain of the mini-AQLQ (0.60; 0.05 to 1.15; p = 0.034). Secondary outcomes showed increased patient activation and reduced reliance on reliever medication. There was no significant difference in the remaining secondary outcomes. There were no adverse events. Conclusion: Living Well with Asthma has been shown to be acceptable to potential end users, and has potential for effectiveness. This intervention merits further development, and subsequent evaluation in a Phase III full scale RCT.