Recognising a reinvented constitution

The text of the Indian Constitution remains largely unchanged; it is the context that has changed. Liberalisation, globalisation and the expanded connotations given to 'terrorism' have altered the conception of human rights. They have also set rights in conflict. And a lexical prioritising of rights has come into being. This lexical priority is propositioned on malleable concepts that include: --the interests of national security --public purpose --the public interest and, increasingly, the market.This conference was supported by the generosity of the Japan Foundation Asia Centre, AusAID, the Daiwa Foundation for Asia and Oceania, the Myer Foundation and The Australian National University's National Institute for Asia and the Pacific and the Humanities Research Centre

Analysing the role of information exchange for demand forecasting in collaborative supply chains

It is now widely recognized that supply chains, not individual organisations, are responsible for the success or failure of businesses. This has necessitated close coordination among supply chain partners. In the past few decades, in an attempt to improve the overall efficiency of the supply chain, many companies have engaged in collaboration with other supply chain members. Consequently, several supply chain management initiatives such as Vendor Managed Inventory, Efficient Consumer Response, Continuous Replenishment and Accurate Response have been proposed in the literature to improve the flow of materials as well as information among supply chain partners. In this line, Collaborative Planning Forecasting and Replenishment (CPFR) is a relatively new initiative that combines the intelligence of multiple trading partners in planning and fulfilment of customer demand by linking sales and marketing best practices. The role of CPFR has been widely studied in the US retail industry, but it has not been researched much in the UK and also in Asian countries. Hence, this research focuses on the adoption of CPFR in the UK and India. Levels of collaboration and information sharing differ to a great extent across the supply chains based on the needs of individual businesses. Accordingly, the importance of CPFR varies in different supply chains. The study reported in this research explores the operations of CPFR and highlights the corresponding benefits in different firms using case studies of Indian (4 cases) and British (2 cases) companies operating in Make-To-Stock (MTS) and Make-To-Order (MTO) environments. In this research, information exchange among collaborating partners is analysed with a focus on its role in demand forecasting and timely replenishment. In order to identify potential benefits of CPFR, this research has adopted a four stage approach. In the first stage, interviews with top and middle managers in the case companies helped to develop a clear understanding of the collaborative arrangements in each company. In stage two, a conceptual model called the Reference Demand Model (RDM) was developed. RDM is a specific model representing the dependency of demand projection on information from different supply chain members involved in supply chain processes. When fully developed, the RDM will serve as a decision tool for the companies involved in collaboration to decide on the level of collaboration and the type of information exchange in order to improve supply chain planning and forecasting. Further, to explore how demand information collected through RDM can help improve forecasts accuracy, a quantitative approach is employed in the next two stages. Therefore, stages 3 and 4 were studied only for the cases with detailed sales data. In stage 3, structural equation models were developed to establish the underlying relationships among demand factors that were identified using RDM. In stage 4, regression forecast models of sales were developed using the demand factors identified through RDM. The forecast models showed an improved accuracy and thus this research suggested the case company (Soft Drink Co.) to use the demand information (identified from RDM) in the demand forecasts. The results strongly support CPFR in a MTS environment with promotional sales, and exchanging the detailed sales information from downstream to upstream supply chain members may improve the accuracy of demand forecasts. Information exchange is also required to ensure timely replenishment for MTS products. However, in a MTO environment, there is less need for collaboration with downstream supply chain partners for the purpose of short term demand forecasting

Social media and successful retail operations in the hyper-customisation era

It's possible to increase both customer satisfaction and profitability, but careful planning is needed, write Usha Ramanathan, Nachiappan (Nachi) Subramanian and Guy Parrot

Analysing the role of information exchange for demand forecasting in collaborative supply chains

It is now widely recognized that supply chains, not individual organisations, are responsible for the success or failure of businesses. This has necessitated close coordination among supply chain partners. In the past few decades, in an attempt to improve the overall efficiency of the supply chain, many companies have engaged in collaboration with other supply chain members. Consequently, several supply chain management initiatives such as Vendor Managed Inventory, Efficient Consumer Response, Continuous Replenishment and Accurate Response have been proposed in the literature to improve the flow of materials as well as information among supply chain partners. In this line, Collaborative Planning Forecasting and Replenishment (CPFR) is a relatively new initiative that combines the intelligence of multiple trading partners in planning and fulfilment of customer demand by linking sales and marketing best practices. The role of CPFR has been widely studied in the US retail industry, but it has not been researched much in the UK and also in Asian countries. Hence, this research focuses on the adoption of CPFR in the UK and India. Levels of collaboration and information sharing differ to a great extent across the supply chains based on the needs of individual businesses. Accordingly, the importance of CPFR varies in different supply chains. The study reported in this research explores the operations of CPFR and highlights the corresponding benefits in different firms using case studies of Indian (4 cases) and British (2 cases) companies operating in Make-To-Stock (MTS) and Make-To-Order (MTO) environments. In this research, information exchange among collaborating partners is analysed with a focus on its role in demand forecasting and timely replenishment. In order to identify potential benefits of CPFR, this research has adopted a four stage approach. In the first stage, interviews with top and middle managers in the case companies helped to develop a clear understanding of the collaborative arrangements in each company. In stage two, a conceptual model called the Reference Demand Model (RDM) was developed. RDM is a specific model representing the dependency of demand projection on information from different supply chain members involved in supply chain processes. When fully developed, the RDM will serve as a decision tool for the companies involved in collaboration to decide on the level of collaboration and the type of information exchange in order to improve supply chain planning and forecasting. Further, to explore how demand information collected through RDM can help improve forecasts accuracy, a quantitative approach is employed in the next two stages. Therefore, stages 3 and 4 were studied only for the cases with detailed sales data. In stage 3, structural equation models were developed to establish the underlying relationships among demand factors that were identified using RDM. In stage 4, regression forecast models of sales were developed using the demand factors identified through RDM. The forecast models showed an improved accuracy and thus this research suggested the case company (Soft Drink Co.) to use the demand information (identified from RDM) in the demand forecasts. The results strongly support CPFR in a MTS environment with promotional sales, and exchanging the detailed sales information from downstream to upstream supply chain members may improve the accuracy of demand forecasts. Information exchange is also required to ensure timely replenishment for MTS products. However, in a MTO environment, there is less need for collaboration with downstream supply chain partners for the purpose of short term demand forecasting

Supply chain resilience and business responses to disruptions of the Covid-19 pandemic

Purpose: At its peak, the Covid-19 pandemic has created disruption to food supply chains in the UK and for the entire world. Although societal changes created some resilience within the supply chains, high volatility in demand creates supply, logistics and distribution issues. This is reflected in the economic instability of businesses and SMEs. In this paper, we explore factors behind this initial disruption in the supply chains and offer suggestions to businesses based on the established practices and theories. Design: We use mixed methods research. First, we conducted an exploratory study by collecting data from published online sources. Then we analysed possible scenarios from the available information using regression. We then conducted two interviews with UK retail sector representatives. These scenarios have been compared and contrasted to provide decision making points to businesses and supply chain players to tackle current and any future potential disruptions. Findings: Our findings from the current exploratory study inform the volatility of supply chains. We suggested some possible responses from businesses, during and after the pandemic. Value: Our regression model provides a decision-making approach to help supply chain businesses during the pandemic outbreak. Once a complete data set of Covid-19 is available, we can create a resilience model that can help businesses and supply chains

A Case Study of Human Milk Banking with Focus on the Role of IoT Sensor Technology

Human milk is the biological norm for newborn nutrition, with breast milk from the mother being recognized as the best nutritious source for infant health. When the milk is unavailable, donor human milk is the best alternative for infants with low birthweights. Growing recognition of the benefits of donor human milk has led to increasing global interest in monitoring and controlling human milk’s quality to fulfil the need for donor human milk. In response to this need, the REAMIT project proposed to adapt and apply existing innovative technology to continuously monitor and record human milk quality and signal potential milk quality issues. IoT sensors and a Big Data technology have been used to monitor conditions that may increase spoilage (such as temperature and humidity) in the transportation stage. The sensors were installed in the insulated bags used to transport the milk from the donor’s home/hospital to the human milk bank and vice versa. The temperature and humidity were collected every 30 minutes, whilst the GPS locator sent data every 2 minutes. The data are collected in the cloud using GPRS/CAT-M1 technology. An algorithm has been designed to send alerts when the milk temperature is above the pre-specified threshold specified by the organisation, i.e. above - 20°C. The experience showed evidence that IoT sensors can efficiently be used to monitor and maintain quality in supply chains of high-quality human milk. This rare product needs a high level of quality control which is possible with the support of smart technologies. The IoT technology is helping the human milk supply chain in five different aspects, namely reducing waste, assuring quality, improving availability, reducing cost and improving sustainability. This system could be extended to various supply chains of rare and precious commodities, including further medical supplies such as human blood and organs to completely avoid waste and ensure total quality in supply chains

Adapting Digital Technologies to Reduce Food Waste and Improve Operational Efficiency of a Frozen Food Company—The Case of Yumchop Foods in the UK

Cold storage is an essential operation for many food products in cold supply chains. The main objective of this kind of storage is to preserve the food products for a certain period of time. However, often due to a lack of accurate technology, humidity and temperature in food storge are not monitored in real-time, which will affect the food quality. At present, the Internet of Things (IoT) has become a very popular choice for businesses in food supply chains. This is mainly because of the easy availability of internet, which helps monitor and control the quality of food in storage and transport. In this paper, the experiences of adapting and testing IoT sensors and Big Data technology for reducing food waste in a frozen food manufacturer in the UK are presented. The temperature and humidity monitoring within the operations of this ready-to-eat frozen meal company are also expected to maintain food quality and adhere to legal food safety requirements. Our reflection of experience gained in the installation of the sensors, collecting the data to a cloud server, and conducting data analytics with the data are also described. During the implementation of the technology, the company was able to identify optimal and non-optimal storage conditions for their food products and pre-processed ingredients. This allowed the further development of an alert system and corrective action protocol assisted using the technology installed. Results of the case study evidenced and reported a thorough real-time monitoring system that was able to reduce food waste and assure product quality, which could be applied in different stages of the food supply chain. This case can influence several food businesses to start adapting technology in their routine operations to ensure food quality and safety

Collaborative closed-loop supply chain framework for sustainable manufacturing: Evidence from the Indian packaging industry

Businesses reeling from the impact of COVID are struggling to achieve sustainability, amidst many other challenges, including finance and capacity shortfalls. One of the pathways to achieving 3BL in businesses is to create closed-loop supply chains (CLSC) covering the entire lifecycle of products. CLSC have proven to be important for sustainable supply chain (SC) operations, given the shortage of materials and labour globally following the COVID-19 pandemic. While it is widely acknowledged that the success of CLSC depends on successful collaboration between SC members, factors for successful CLSC collaboration are not sufficiently understood from the literature. Employing an observation-based case study and a survey of SC members, we develop our contribution in the context of an Indian packaging company, to delineate and verify a collaborative CLSC framework. The results confirm that the success of CLSC collaboration lies in the involvement and commitment of SC members. Collaboration for forward and reverse SC operations also facilitate the involvement of SC members in CLSC collaborations. Our research suggests that SC collaborations are enhanced by explicit incentive-sharing schemes and having the same SC members for both forward and reverse SC operations

Evaluation of an Intermittent Six-month Regimen in New Pulmonary Tuberculosis Patients with Diabetes Mellitus

Background: The treatment of tuberculosis (TB) with category I regimen of the Revised National Tuberculosis Control Programme (RNTCP) for patients with diabetes mellitus (DM) needs evaluation. Objective: To assess the cure and relapse rates in 3 years, among the new smear-positive TB patients with Type-2 DM (DMTB) treated with CAT-I regimen (2E3H3R3Z3/4R3H3) of RNTCP. Methodology: TB suspects attending the diabetology units and the TB research centre (TRC) Chennai, were investigated. Eligible DMTB cases were enrolled. Baseline estimation of cardiac, renal, liver function tests and glycosylated-HBA1c were undertaken. All patients received 2E3H3R3Z3/4R3H3 under supervision at TRC. Clinical and sputum (smear and culture) examinations and monitoring of diabetic status were undertaken every month up to 24 months, then once in 3 months up to 36 months. Results: Of 100 patients admitted, 7 were excluded for various reasons from analysis. Of 93 patients, 87 (94%) had a favourable response at the end of treatment. Pre and post treatment mean glycosylated-HBA1c were 9.7% and 8.4 %.(>7% poor control). During follow-up period, 6 died and one lost to follow-up. Of the remaining, four relapsed. Conclusion: Category-I regimen, recommended for all the new smear-positive patients in the Indian TB programme, is effective in the treatment of DMTB patients, despite poor control of diabetes