Effective forecasting for supply-chain planning: an empirical evaluation and strategies for improvement

Demand forecasting is a crucial aspect of the planning process in supply-chain companies. The most common approach to forecasting demand in these companies involves the use of a simple univariate statistical method to produce a forecast and the subsequent judgmental adjustment of this by the company's demand planners to take into account market intelligence relating to any exceptional circumstances expected over the planning horizon. Based on four company case studies, which included collecting more than 12,000 forecasts and outcomes, this paper examines: i) the extent to which the judgmental adjustments led to improvements in accuracy, ii) the extent to which the adjustments were biased and inefficient, iii) the circumstances where adjustments were detrimental or beneficial, and iv) methods that could lead to greater levels of accuracy. It was found that the judgmentally adjusted forecasts were both biased and inefficient. In particular, market intelligence that was expected to have a positive impact on demand was used far less effectively than intelligence suggesting a negative impact. The paper goes on to propose a set of improvements that could be applied to the forecasting processes in the companies and to the forecasting software that is used in these processes

Emerging Disparities among Self-Pay Trauma Patients

Preliminary results from a study of trauma patients in Southern Nevada are yielding some unexpected findings with implications for both trauma centers and the growing Hispanic population. Hispanic patients are more likely to be self pay irrespective of income level and employment status when compared to non-Hispanic patient groups. Further, self pay Hispanics, unlike their non-Hispanic, self pay counterparts, tend to be employed, have families, and report stable living conditions. The implication is that the financial and social cost of traumatic injury may place a significant burden on trauma centers, patients, their families and the community

Formative research to develop a school-based, community-linked physical activity role model programme for girls: CHoosing Active Role Models to INspire Girls (CHARMING)

Background: Physical inactivity is a persistent challenge among girls. School-based physical activity (PA) interventions have shown mixed effects on girl's activity levels, with multi-component approaches involving both school and community links appearing more effective for sustainable change. The purpose of the current research was to gather views from preadolescent girls, parents, teachers and stakeholders in order to co-produce a multi-component school-based, community linked PA intervention programme. Methods: Focus groups were conducted in two primary schools with 34 girls aged 9-11 years and 11 parents (10 female, 1 male). In-depth interviews were conducted with four female teachers (including two head teachers). Focus groups and interviews focused on programme design (structure, content and delivery) and potential factors affecting intervention uptake and continued PA participation. A series of stakeholder engagement events occurred throughout the study period. All data were transcribed verbatim and thematically analysed in NVivo 11. Results: Girls reported that fun taster sessions delivered by role models would encourage them to participate in a school-based role model programme, with tailored taster sessions each week to enhance continued PA participation. Parents and teachers identified a number of barriers to uptake and continued PA participation, and active involvement of stakeholders facilitated the development of intervention strategies. Strategies included; single-sex after-school sessions, use of female role models, low-cost activity options and mapping community provision. Analyses revealed the importance of tailoring the programme to align with local needs, demands and provision. Conclusions: Data show numerous barriers to intervention uptake and continued PA participation when designing a school-based, community-linked intervention. Adopting a co-production approach, this formative work highlights a number of potential strategies for overcoming these barriers. Findings from the research directed the development and implementation of the CHARMING role model intervention and informed the creation of an intervention logic model

The acceptability and feasibility of using a 3D body size scale to initiate conversations about weight in toddlerhood: a mixed-methods study

Background: Health Care Professionals struggle to initiate conversations about overweight in toddlerhood. A novel 3D body size scale (3D BSS) may facilitate engagement with this topic during pediatric appointments. Objectives: To explore barriers and facilitators to using the 3D BSS through a mixedmethods design. Methods: For the qualitative phase, parents of toddlers (n = 38) participated in semistructured interviews introducing the 3D BSS of 4–5-year-old children. For the quantitative phase, pre- and post-interview questionnaires were administered to ascertain the acceptability of the 3D BSS. Results: Parents rated the 3D BSS as “very” (n = 20, 52.6%) to “moderately” (n = 12, 31.6%) acceptable. Thematic analysis revealed four barriers to acceptability: i) the sensitive nature of child weight, ii) the belief that weight does not determine health, iii) the visual normalisation of overweight and iv) the need to account for individual variation in growth patterns. However, these barriers could be overcome through three facilitators: i) the provision of expert guidance ii) the value of simple tools, and iii) tailoring conversations to familial needs. Conclusions: Parents considered the 3D BSS an acceptable visual resource to discuss child weight during routine appointments. However, the acceptability of the tool was conditional on a sensitive, collaborative, and tailored delivery approach

The Social context of motorcycle riding and the key determinants influencing rider behavior: A qualitative investigation

Objective: Given the increasing popularity of motorcycle riding and heightened risk of injury or death associated with being a rider, this study explored rider behaviour as a determinant of rider safety and, in particular, key beliefs and motivations which influence such behaviour. To enhance the effectiveness of future education and training interventions, it is important to understand riders’ own views about what influences how they ride. Specifically, this study sought to identify key determinants of riders’ behaviour in relation to the social context of riding including social and identity-related influences relating to the group (group norms and group identity) as well as the self (moral/personal norm and self-identity). ----- ----- Method: Qualitative research was undertaken via group discussions with motorcycle riders (n = 41). Results: The findings revealed that those in the group with which one rides represent an important source of social influence. Also, the motorcyclist (group) identity was associated with a range of beliefs, expectations, and behaviours considered to be normative. Exploration of the construct of personal norm revealed that riders were most cognizant of the “wrong things to do” when riding; among those issues raised was the importance of protective clothing (albeit for the protection of others and, in particular, pillion passengers). Finally, self-identity as a motorcyclist appeared to be important to a rider’s self-concept and was likely to influence their on-road behaviour. ----- ----- Conclusion: Overall, the insight provided by the current study may facilitate the development of interventions including rider training as well as public education and mass media messages. The findings suggest that these interventions should incorporate factors associated with the social nature of riding in order to best align it with some of the key beliefs and motivations underpinning riders’ on-road behaviours

The role of interleukin-1β as a predictive biomarker and potential therapeutic target during clinical ex vivo lung perfusion

BACKGROUND: Extended criteria donor lungs deemed unsuitable for immediate transplantation can be reconditioned using ex vivo lung perfusion (EVLP). Objective identification of which donor lungs can be successfully reconditioned and will function well post-operatively has not been established. This study assessed the predictive value of markers of inflammation and tissue injury in donor lungs undergoing EVLP as part of the DEVELOP-UK study. METHODS: Longitudinal samples of perfusate, bronchoalveolar lavage, and tissue from 42 human donor lungs undergoing clinical EVLP assessments were analyzed for markers of inflammation and tissue injury. Levels were compared according to EVLP success and post-transplant outcomes. Neutrophil adhesion to human pulmonary microvascular endothelial cells (HPMECs) conditioned with perfusates from EVLP assessments was investigated on a microfluidic platform. RESULTS: The most effective markers to differentiate between in-hospital survival and non-survival post-transplant were perfusate interleukin (IL)-1β (area under the curve = 1.00, p = 0.002) and tumor necrosis factor-α (area under the curve = 0.95, p = 0.006) after 30 minutes of EVLP. IL-1β levels in perfusate correlated with upregulation of intracellular adhesion molecule-1 in donor lung vasculature (R(2) = 0.68, p < 0.001) and to a lesser degree upregulation of intracellular adhesion molecule-1 (R(2) = 0.30, p = 0.001) and E-selectin (R(2) = 0.29, p = 0.001) in conditioned HPMECs and neutrophil adhesion to conditioned HPMECs (R(2) = 0.33, p < 0.001). Neutralization of IL-1β in perfusate effectively inhibited neutrophil adhesion to conditioned HPMECs (91% reduction, p = 0.002). CONCLUSIONS: Donor lungs develop a detectable and discriminatory pro-inflammatory signature in perfusate during EVLP. Blocking the IL-1β pathway during EVLP may reduce endothelial activation and subsequent neutrophil adhesion on reperfusion; this requires further investigation in vivo

Golden Rule of Forecasting: Be Conservative

This article proposes a unifying theory, or the Golden Rule, or forecasting. The Golden Rule of Forecasting is to be conservative. A conservative forecast is consistent with cumulative knowledge about the present and the past. To be conservative, forecasters must seek out and use all knowledge relevant to the problem, including knowledge of methods validated for the situation. Twenty-eight guidelines are logically deduced from the Golden Rule. A review of evidence identified 105 papers with experimental comparisons; 102 support the guidelines. Ignoring a single guideline increased forecast error by more than two-fifths on average. Ignoring the Golden Rule is likely to harm accuracy most when the situation is uncertain and complex, and when bias is likely. Non-experts who use the Golden Rule can identify dubious forecasts quickly and inexpensively. To date, ignorance of research findings, bias, sophisticated statistical procedures, and the proliferation of big data, have led forecasters to violate the Golden Rule. As a result, despite major advances in evidence-based forecasting methods, forecasting practice in many fields has failed to improve over the past half-century