Using vulnerability performance indicators to attain food supply chain robustness

High effectiveness and leanness of modern supply chains (SCs) increase their vulnerability, i.e. susceptibility to disturbances reflected in non-robust SC performances. Both the SC management literature and SC professionals indicate the need for the development of SC vulnerability assessment tools. In this article, a new method for vulnerability assessment, the VULA method, is presented. The VULA method helps to identify how much a company would underperform on a specific Key Performance Indicator in the case of a disturbance, how often this would happen and how long it would last. It ultimately informs the decision about whether process redesign is appropriate and what kind of redesign strategies should be used in order to increase the SC's robustness. The applicability of the VULA method is demonstrated in the context of a meat SC using discrete-event simulation to conduct the performance analysis.

Community convergence and recruitment of keystone species as performance indicators of artificial reefs

An experimental artificial reefwas constructed in Strangford Lough, Northern Ireland as part of trials to regenerate damaged biogenic reefs formed by the horse mussel Modiolus modiolus. Experimental reef plots were constructed using Pecten maximus shell as cultch. Clumps of live adult M. modiolus were translocated from nearby natural reefs into cultchwith a high profile (elevated cultch), cultch with a lowprofile (flattened cultch), as well as directly into the seafloor. The aim of the study was to test the hypothesis that translocated mussel clumps would increase habitat complexity thus accelerating community succession and enhancing natural recruitment of M. modiolus spat. These effects were predicted to be greater on elevated cultch due to greater protection from
predators and increased accessibility to food resources. Within the artificial reef array the translocated clumps had a significant positive effect on recruitment compared to cultch without mussels with average densities of spat settled on the translocated M. modiolus clumps ranging from 100 to 200 individuals m-2 compared to 4 to 52 spat m-2 on cultch without mussels. Recruitment of M. modiolus spat was also significantly higher on translocated horse mussels when compared to natural reefs where densities of 8–36 spat m-2 were recorded.
Reef elevation appeared to provide some degree of protection from predators but differences in translocated M. modiolus survival on the different elevation treatments were not significant. In total, 223 taxa were recorded 12 months after reef construction. The presence of translocated clumps ofM. modiolus was the main driver of the increases in faunal diversity and species abundance. Application of objective criteria to assess the performance of artificial reefs suggested that translocation of M. modiolus clumps alone achieved most of the restoration objectives. Consequently this pilot study demonstrates a straightforward and realistic intervention technique that could be used to kick start the regeneration and expansion of impacted mussel and similar biogenic reefs elsewhere.

Key performance indicators – A new approach for specifying concrete and assessing state of health of concrete structure

The focus of this paper is to outline a method for consolidating and implementing the work on performance-based specification and testing. First part of the paper will review the mathematical significance of the variables used in common service life models. The aim is to identify a set of significant variables that influence the ingress of chloride ions into concrete. These variables are termed as Key Performance Indicators (KPI’s). This will also help to reduce the complexity of some of the service life models and make them more appealing for practicing engineers. The second part of the paper presents a plan for developing a database based on these KPI’s so that relationships can then be drawn between common concrete mix parameters and KPI’s. This will assist designers in specifying a concrete with adequate performance for a particular environment. This, collectively, is referred to as the KPI based approach and the concluding remarks will outline how the authors envisage the KPI theory to relate to performance assessment and monitoring.

Outcomes and process in reading tutoring

Background: Large-scale randomised controlled trials are relatively rare in education. The present study approximates to, but is not exactly, a randomised controlled trial. It was an attempt to scale up previous small peer tutoring projects, while investing only modestly in continuing professional development for teachers.Purpose: A two-year study of peer tutoring in reading was undertaken in one local education authority in Scotland. The relative effectiveness of cross-age versus same-age tutoring, light versus intensive intervention, and reading versus reading and mathematics tutoring were investigated.Programme description (if relevant): The intervention was Paired Reading, a freely available cross-ability tutoring method applied to books of the pupils' choice but above the tutee's independent readability level. It involves Reading Together and Reading Alone, and switching from one to the other according to need.Sample: Eighty-seven primary schools of overall average socio-economic status, ability and gender in one council in Scotland. There were few ethnic minority students. Proportions of students with special needs were low. Children were eight and 10 years old as the intervention started. Macro-evaluation n = 3520. Micro-evaluation Year 1 15 schools n = 592, Year 2 a different 15 schools n = 591, compared with a comparison group of five schools n = 240.Design and methods: Almost all the primary schools in the local authority participated and were randomly allocated to condition. A macro-evaluation tested and retested over a two-year period using Performance Indicators in Primary Schools. A micro-evaluation tested and retested within each year using norm-referenced tests of reading comprehension. Macro-evaluation was with multi-level modelling, micro-evaluation with descriptive statistics and effect sizes, analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA).Results: Macro-evaluation yielded significant pre-post gains in reading attainment for cross-age tutoring over both years. No other differences were significant. Micro-evaluation yielded pre-post changes in Year 1 (selected) and Year 2 (random) greater than controls, with no difference between same-age and cross-age tutoring. Light and intensive tutoring were equally effective. Tutoring reading and mathematics together was more effective than only tutoring reading. Lower socio-economic and lower reading ability students did better. Girls did better than boys. Regarding observed implementation quality, some factors were high and others low. Few implementation variables correlated with attainment gain.Conclusions: Paired Reading tutoring does lead to better reading attainment compared with students not participating. This is true in the long term (macro-evaluation) for cross-age tutoring, and in the short term (micro-evaluation) for both cross-age and same-age tutoring. Tutors and tutees benefited. Intensity had no effect but dual tutoring did have an effect. Low-socio-economic status, low-ability and female students did better. The results of the different forms of evaluation were indeed different. There are implications for practice and for future research. © 2012 Copyright Taylor and Francis Group, LLC.

Advanced Business Simulations-Incorporating business and process execution data

Key Performance Indicators (KPIs) and their predictions are widely used by the enterprises for informed decision making. Nevertheless , a very important factor, which is generally overlooked, is that the top level strategic KPIs are actually driven by the operational level business processes. These two domains are, however, mostly segregated and analysed in silos with different Business Intelligence solutions. In this paper, we are proposing an approach for advanced Business Simulations, which converges the two domains by utilising process execution & business data, and concepts from Business Dynamics (BD) and Business Ontologies, to promote better system understanding and detailed KPI predictions. Our approach incorporates the automated creation of Causal Loop Diagrams, thus empowering the analyst to critically examine the complex dependencies hidden in the massive amounts of available enterprise data. We have further evaluated our proposed approach in the context of a retail use-case that involved verification of the automatically generated causal models by a domain expert.

Identifying the Impact of Incomplete Datasets on Process Cycle Time Prediction in an Aerospace Assembly Line

Supply Chain Simulation (SCS) is applied to acquire information to support outsourcing decisions but obtaining enough detail in key parameters can often be a barrier to making well informed decisions.
One aspect of SCS that has been relatively unexplored is the impact of inaccurate data around delays within the SC. The impact of the magnitude and variability of process cycle time on typical performance indicators in a SC context is studied.
System cycle time, WIP levels and throughput are more sensitive to the magnitude of deterministic deviations in process cycle time than variable deviations. Manufacturing costs are not very sensitive to these deviations.
Future opportunities include investigating the impact of process failure or product defects, including logistics and transportation between SC members and using alternative costing methodologies.

An Innovative Approach to Evaluating Organisational Change

This paper addresses the difficult problem of how to improve the process of evaluating organisational change. Given that the data emergent from an evaluative exercise will strongly influence the subsequent strategic and operational decisions taken by organisational managers, it is critical that the evaluation approach itself is capable of delivering high quality, accurate and timely data. The aim of this paper is to examine the role of the IT-based Optionfinder Technology used in conjunction with focus groups, in generating management decision-making data, and reflecting the changes in key performance indicators in a utility organisation. The case study research evaluates the innovative integrative approach adopted by the utility organisation and concludes that the proposed approach contributes to improvements in the decision-making capability of managers.

Robust food supply supply chains:An integrated framework for vulnerability assessment and disturbance management

The operation of supply chains (SCs) has for many years been focused on efficiency, leanness and responsiveness. This has resulted in reduced slack in operations, compressed cycle times, increased productivity and minimised inventory levels along the SC. Combined with tight tolerance settings for the realisation of logistics and production processes, this has led to SC performances that are frequently not robust. SCs are becoming increasingly vulnerable to disturbances, which can decrease the competitive power of the entire chain in the market. Moreover, in the case of food SCs non-robust performances may ultimately result in empty shelves in grocery stores and supermarkets.
The overall objective of this research is to contribute to Supply Chain Management (SCM) theory by developing a structured approach to assess SC vulnerability, so that robust performances of food SCs can be assured. We also aim to help companies in the food industry to evaluate their current state of vulnerability, and to improve their performance robustness through a better understanding of vulnerability issues. The following research questions (RQs) stem from these objectives:
RQ1: What are the main research challenges related to (food) SC robustness?
RQ2: What are the main elements that have to be considered in the design of robust SCs and what are the relationships between these elements?
RQ3: What is the relationship between the contextual factors of food SCs and the use of disturbance management principles?
RQ4: How to systematically assess the impact of disturbances in (food) SC processes on the robustness of (food) SC performances?
To answer these RQs we used different methodologies, both qualitative and quantitative. For each question, we conducted a literature survey to identify gaps in existing research and define the state of the art of knowledge on the related topics. For the second and third RQ, we conducted both exploration and testing on selected case studies. Finally, to obtain more detailed answers to the fourth question, we used simulation modelling and scenario analysis for vulnerability assessment.
Main findings are summarised as follows.
Based on an extensive literature review, we answered RQ1. The main research challenges were related to the need to define SC robustness more precisely, to identify and classify disturbances and their causes in the context of the specific characteristics of SCs and to make a systematic overview of (re)design strategies that may improve SC robustness. Also, we found that it is useful to be able to discriminate between varying degrees of SC vulnerability and to find a measure that quantifies the extent to which a company or SC shows robust performances when exposed to disturbances.
To address RQ2, we define SC robustness as the degree to which a SC shows an acceptable performance in (each of) its Key Performance Indicators (KPIs) during and after an unexpected event that caused a disturbance in one or more logistics processes. Based on the SCM literature we identified the main elements needed to achieve robust performances and structured them together to form a conceptual framework for the design of robust SCs. We then explained the logic of the framework and elaborate on each of its main elements: the SC scenario, SC disturbances, SC performance, sources of food SC vulnerability, and redesign principles and strategies.
Based on three case studies, we answered RQ3. Our major findings show that the contextual factors have a consistent relationship to Disturbance Management Principles (DMPs). The product and SC environment characteristics are contextual factors that are hard to change and these characteristics initiate the use of specific DMPs as well as constrain the use of potential response actions. The process and the SC network characteristics are contextual factors that are easier to change, and they are affected by the use of the DMPs. We also found a notable relationship between the type of DMP likely to be used and the particular combination of contextual factors present in the observed SC.
To address RQ4, we presented a new method for vulnerability assessments, the VULA method. The VULA method helps to identify how much a company is underperforming on a specific Key Performance Indicator (KPI) in the case of a disturbance, how often this would happen and how long it would last. It ultimately informs the decision maker about whether process redesign is needed and what kind of redesign strategies should be used in order to increase the SC’s robustness. The VULA method is demonstrated in the context of a meat SC using discrete-event simulation. The case findings show that performance robustness can be assessed for any KPI using the VULA method.
To sum-up the project, all findings were incorporated within an integrated framework for designing robust SCs. The integrated framework consists of the following steps: 1) Description of the SC scenario and identification of its specific contextual factors; 2) Identification of disturbances that may affect KPIs; 3) Definition of the relevant KPIs and identification of the main disturbances through assessment of the SC performance robustness (i.e. application of the VULA method); 4) Identification of the sources of vulnerability that may (strongly) affect the robustness of performances and eventually increase the vulnerability of the SC; 5) Identification of appropriate preventive or disturbance impact reductive redesign strategies; 6) Alteration of SC scenario elements as required by the selected redesign strategies and repeat VULA method for KPIs, as defined in Step 3.
Contributions of this research are listed as follows. First, we have identified emerging research areas - SC robustness, and its counterpart, vulnerability. Second, we have developed a definition of SC robustness, operationalized it, and identified and structured the relevant elements for the design of robust SCs in the form of a research framework. With this research framework, we contribute to a better understanding of the concepts of vulnerability and robustness and related issues in food SCs. Third, we identified the relationship between contextual factors of food SCs and specific DMPs used to maintain robust SC performances: characteristics of the product and the SC environment influence the selection and use of DMPs; processes and SC networks are influenced by DMPs. Fourth, we developed specific metrics for vulnerability assessments, which serve as a basis of a VULA method. The VULA method investigates different measures of the variability of both the duration of impacts from disturbances and the fluctuations in their magnitude.
With this project, we also hope to have delivered practical insights into food SC vulnerability. First, the integrated framework for the design of robust SCs can be used to guide food companies in successful disturbance management. Second, empirical findings from case studies lead to the identification of changeable characteristics of SCs that can serve as a basis for assessing where to focus efforts to manage disturbances. Third, the VULA method can help top management to get more reliable information about the “health” of the company.
The two most important research opportunities are: First, there is a need to extend and validate our findings related to the research framework and contextual factors through further case studies related to other types of (food) products and other types of SCs. Second, there is a need to further develop and test the VULA method, e.g.: to use other indicators and statistical measures for disturbance detection and SC improvement; to define the most appropriate KPI to represent the robustness of a complete SC. We hope this thesis invites other researchers to pick up these challenges and help us further improve the robustness of (food) SCs.

Food web indicators under the Marine Strategy Framework Directive: From complexity to simplicity?

The Marine Strategy Framework Directive (MSFD) requires that European Union Member States achieve "Good Environmental Status" (GES) in respect of 11 Descriptors of the marine environment by 2020. Of those, Descriptor 4, which focuses on marine food webs, is perhaps the most challenging to implement since the identification of simple indicators able to assess the health of highly dynamic and complex interactions is difficult. Here, we present the proposed food web criteria/indicators and analyse their theoretical background and applicability in order to highlight both the current knowledge gaps and the difficulties associated with the assessment of GES. We conclude that the existing suite of indicators gives variable focus to the three important food web properties: structure, functioning and dynamics, and more emphasis should be given to the latter two and the general principles that relate these three properties. The development of food web indicators should be directed towards more integrative and process-based indicators with an emphasis on their responsiveness to multiple anthropogenic pressures. (C) 2013 Elsevier Ltd. All rights reserved.

The role of trust in relationship development and performance improvement

The importance of inter-organizational trust to project success has been increasingly highlighted in the construction industry. This study aims to explore the role of trust between project parties. It adopts a combination of quantitative and qualitative methodologies. Based on the analysis of the responses of a questionnaire survey, trust is demonstrated to have a significant contribution to the development of cooperative or collaborative relationships; fostering trust proves to have a major influence on the improvement of project performance; and some relationship and performance indicators are found to have closer associations with trust than others so that trust is more important to
the development of relationship and the improvement of performance in these aspects. The analysis of questionnaire responses also provides significant evidence for the reduction in monitoring and control following the increase of mutual trust. The questionnaire survey is followed by a series of expert interviews, both of which contribute to the establishment of a model that links trust with relationship and performance and distinguishes the new approach that is based on trust from the traditional mechanism that relies on monitoring and control.