The Logistic Principles for Fast Flexible Strategy Design of the Company in Crisis Time

The article deals with design of the logistic principles enabling an enterprise to create a strategy flexible in terms of business and marketing and stable and steady in terms of manufacturing. In order to create a strategy model the following principles can be applied: shortening the period of capacity planning combined with flexible planning, SYNCRO – MRP (Material Required Planning) principle, the application of forecasting in capacity planning, creation with partners of one of the cooperation forms such as supply chain, demand chain, lean supply chain, agile supply chain, leagile supply chain, and using the DBR (Drum Buffer Rope), APS (Advanced Planning System) and SCP (Supply Chain Planning) systems. The article describes application of this principle for model design of the flexible strategy for Chemosvit fólie a. s. company, and the results of this application in the crisis time 2009–2011.SYANCRO-MRP, capacity planning, forecasting, supply chain, demand chain

A Neural Network for Collaborative Forecasting

As the supply chain activities’ backbone, demand forecasting must be accurate. This paper proposes an artificial neural network forecasting model, which integrates and synchronizes shared information, such as sales or consumption rate among different partners, to improve the forecasting’s accuracy. This information sharing is part of the collaborative planning, forecasting and replenishment (CPFR) model, which is a supply chain model aiming to enhance the supply chain’s efficiency by jointly planning and forecasting between two or more supply chain partners that will be used as the base for production and replenishment activities. The model is validated using a tuna product sales data, and the combination of individual forecasts resulted in better demand forecasting accuracy for the supply chain. This improvement will lead to reduced costs associated with the forecast’s overestimation or underestimation

Specific Aspects of Land Use Planning and Forecasting For Effective Supply Chain Management

The paper describes specific aspects of land use planning and forecasting for effective supply chain management. Close attention is paid to the territorial planning projects having been implemented in the United States, England, Germany, the former Soviet Union and Russia. Land is characterized as an object for planning and forecasting as well as the basis for food security. There is a real need for area development planning and forecasting to provide management of agri-food supply chains. The paper reveals the nature and the relationship of territorial forecasting, planning and land use schemes to develop logistics. Russia has long experience in land reforms, land use planning and forecasting for further social and economic development of territories as well as effective management of supply chains in them

PENGURANGAN BULLWHIP EFFECT DALAM RANTAI PASOK DENGAN METODE COLLABORATIVE PLANNING, FORECASTING AND REPLENISHMENT (CPFR

Abstract The supply chain is a network system of several interconnected organizations with the same goal of distributing production goods and services to their customers. PT. Samudera Gemilang Plastindo (PT SGP) is a company engaged in the processing of plastic seeds, one of the products produced is HDPE T-Shirt Bag. The supply chain system studied at PT. SGP consists of a Manufacturing (Vendor) and 3 Sales Offices (SIM Jember, Depo Bali and 3S Bogor) because they often experience inaccuracies in forecasting data which causes the Bullwhip Effect phenomenon or information distortion to meet customer needs. Initially, forecasting was carried out at each level of the supply chain using different forecasting methods and inventory planning was carried out separately and not coordinated with each other. Therefore, we need an equation in choosing a forecasting method to synchronize the forecasting results and the implementation of production in each supply chain actor. This study uses the Collaborative Planning and Replenishment (CPFR) method, which is a method that combines production planning, forecasting and inventory control. The results of testing several forecasting methods, the method chosen is the Winter's Method because it has the smallest error value. Inventory control is done by calculating the optimal lot, namely Economic Order Quantity (EOQ). The results of demand forecasting and determining the optimal lot are used to calculate the value of the Bullwhip Effect that occurs after the use of the CPFR approach in the supply chain at the vendor level (PT SGP) has changed from 1.285 to 0.729, while in the three Sales Offices there has been a change from 1.321 to 0.528 in SIM Jember sales office, 1.266 to 0.602 at Bali Depo sales office, 1.377 to 0.412 at 3S Bogor sales office

Crown Paints Kenya Limited: Supply Chain Value Analysis in Manufacturing Firms

The critical value chain areas addressed in this case includes: i) forecasting and planning; ii) procurement; iii) material handling; iv) production and v) warehousing distribution and customer service. The methodology used in understanding and finally analysing and providing useful recommendations for the company’s supply value chain involved both qualitative and quantitative research paradigms. This included: discussions with the organisations management staff; discussions with the organisations suppliers and customers; an analysis of the organisations supply chain; and benchmarking with leading local best-practise organisations. Six years down the line after the implementation of the researcher’s recommendations, the company tripled its gross earnings from Ksh. 1 billion by end of 2006 to Ksh. 3 billion by the end of 2011. The findings on forecasting and planning aspects of the supply value chain included: lack of formal supply planning process and insurance premium on excess stocks. The recommendation therefore was to formalise/ structure supply planning process. The findings on procurement were: large supplier base with no long term contracts with chosen few suppliers; high stock levels; make or buy decisions; stock outs; lack of clear specifications. The full paper presents other findings and recommendations reached on all the facets of the supply value analysis investigated. Key words: value analysis, supply chain management, supply network

TECHNOLOGICAL TOOLS AND THE IMPACT OF DIGITALISATION ON THE SUPPLY CHAIN

The supply chain has undergone a significant and innovative transformation in recent years with the introduction of new intelligent and digital technologies aimed at streamlining various supply chain activities from demand forecasting, manufacturing of goods, inventory management, and transport planning to delivery to customers. The digitisation of the transport and shipping industry incorporates advanced technologies such as cloud computing, the Internet of Things (IoT), artificial intelligence (AI), blockchain, and big data. These digital innovations are streamlining routes, forecasting demand, tracking shipments, and above all reacting quickly to changes, resulting in overall supply chain efficiency. This paper provides a comprehensive review of the issues that highlight the birth and construction of this transformation, as well as identifying the technological tools impacting the supply chain, in order to analyse the real impact of digitalisation on the development of relative supply chain strategies JEL: L91, O33, L23, C88, M11, L81  Article visualizations

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

The Design of Agents Oriented Collaboration in SCM

In today\u27s global marketplace, individual firms no longer compete as independent entities but rather as integral part of supply chain links. In order to cater for the increasing demand on collaboration between supply chain partners, the technology of intelligent agent has gained increased interest in supply chain management. However fewer researches have clearly investigated the mechanism about agent applications in this area. In this paper we are to study the way how to incorporate intelligent agents into supply chain management from the perspective of agent-oriented system analysis and design. A multi-agent framework for collaborative planning, forecasting and replenishment in supply chain management is developed, in which supply chain collaboration models are composed from software components that represent types of supply chain agent, their constituent control elements, and their interaction protocols

Book Review: Exploring the Supply Chain: Theory and Practice

This book looks at the basic concepts of Supply Chain Management and provides a comprehensive coverage of the methodology and key strategies drivers in the different processes involved in operating and designing a Supply Chain. It describes the behavioral differences and explains the different tools that have been designed for effective supply chain management. This book is not an academic treatise, though it provides the most comprehensive coverage of the different facets of supply chain management. The authors have made sure that all chapters begin with a small case study that illustrates the specific concepts that are illustrated within the chapter. The book explains the evolution of Supply Chain Management, its concept and philosophy. It also looks at the different elements that go into the design of the Supply Chain and the purchasing functions from the supply chain perspective. The book not only deals with the planning function of SCM, it also covers the fundamentals concepts of forecasting and demand management, planning and control, including the aggregate plan, the different types of inventory models and their classification, work-in-progress and finished goods inventory and quality as a new and major component of Supply Chain Management