A collaborative demand forecasting process with event-based fuzzy judgements

Mathematical forecasting approaches can lead to reliable demand forecast in some environments by extrapolating regular patterns in time-series. However, unpredictable events that do not appear in historical data can reduce the usefulness of mathematical forecasts for demand planning purposes. Since forecasters have partial knowledge of the context and of future events, grouping and structuring the fragmented implicit knowledge, in order to be easily and fully integrated in final demand forecasts is the objective of this work. This paper presents a judgemental collaborative approach for demand forecasting in which the mathematical forecasts, considered as the basis, are adjusted by the structured and combined knowledge from different forecasters. The approach is based on the identification and classification of four types of particular events. Factors corresponding to these events are evaluated through a fuzzy inference system to ensure the coherence of the results. To validate the approach, two case studies were developed with forecasters from a plastic bag manufacturer and a distributor belonging to the food retailing industry. The results show that by structuring and combining the judgements of different forecasters to identify and assess future events, companies can experience a high improvement in demand forecast accuracy

Regression Based Sales Data Forecasting for Predicting the Business Performance

Business plays a vital role in day-to-day life to bring the goods and services to the people. The profit ofa business highly depends on the sales. Forecasting thesales in business is essential since the sales forecast predicts the business performance.Moreover, sales forecasting is an estimation of futuresales in a business based on the past sales data. This forecasting to make better managerial decisions allows in business for improving the performance of the business. Furthermore, the sales forecasting helps to increase the revenue, reduce the operating cost, improve the working capital use, and increase the shareholder�s values. Therefore, this paper presents a sales data forecasting to predict the business performance

EmC-ICDSST 2019: 5th International Conference on Decision Support System Technology - ICDSST 2019 & EURO Mini Conference 2019 on "Decision Support Systems: Main Developments & Future Trends"

info:eu-repo/semantics/publishedVersio

New product development resource forecasting

Forecasting resource requirements for new product development (NPD) projects is essential for both strategic and tactical planning. Sophisticated, elegant planning tools to present data and inform decision-making do exist. However, in NPD, such tools run on unreliable, estimation-based resource information derived through undefined processes. This paper establishes that existing methods do not provide transparent, consistent, timely or accurate resource planning information, highlighting the need for a new approach to resource forecasting, specifically in the field of NPD. The gap between the practical issues and available methods highlights the possibility of developing a novel design of experiments approach to create resource forecasting models

Limousine Service Management: Capacity Planning with Predictive Analytics and Optimization

The limousine service in luxury hotels is an integral component of the whole customer journey in the hospitality industry. One of the largest hotels in Singapore manages a fleet of both in-house and outsourced vehicles around the clock, serving 9000 trips per month on average. The need for vehicles may scale up rapidly, especially during special events and festive periods in the country. The excess demand is met by having additional outsourced vehicles on standby, incurring millions of dollars of additional expenses per year for the hotel. Determining the required number of limousines by hour of the day is a challenging service capacity planning problem. In this paper, a recent transformational journey to manage this problem in the hotel is introduced, driving up to S\$3.2 million of savings per year with improved service level. The approach builds on widely available open-source statistical and spreadsheet optimization tools, along with robotic process automation, to optimize the schedule of its fleet of limousines and drivers, and to support decision-making for planners/controllers to drive sustained business value

Scenario of the organic food market in Europe

Scenario analysis is a qualitative tool for strategic policy analysis that enables researchers and policymakers to support decision making, and a systemic analysis of the main determinants of a business or sector. In this study, a scenario analysis is developed regarding the future development of the market of organic food products in Europe. The scenario follows a participatory approach, exploiting potential interactions among the relevant driving forces, as selected by experts. Network analysis is used to identify the roles of driving forces in the different scenarios, and the results are discussed in comparison with the main findings from existing scenarios on the future development of the organic sector

Toward a relational concept of uncertainty: about knowing too little, knowing too differently, and accepting not to know

Uncertainty of late has become an increasingly important and controversial topic in water resource management, and natural resources management in general. Diverse managing goals, changing environmental conditions, conflicting interests, and lack of predictability are some of the characteristics that decision makers have to face. This has resulted in the application and development of strategies such as adaptive management, which proposes flexibility and capability to adapt to unknown conditions as a way of dealing with uncertainties. However, this shift in ideas about managing has not always been accompanied by a general shift in the way uncertainties are understood and handled. To improve this situation, we believe it is necessary to recontextualize uncertainty in a broader way¿relative to its role, meaning, and relationship with participants in decision making¿because it is from this understanding that problems and solutions emerge. Under this view, solutions do not exclusively consist of eliminating or reducing uncertainty, but of reframing the problems as such so that they convey a different meaning. To this end, we propose a relational approach to uncertainty analysis. Here, we elaborate on this new conceptualization of uncertainty, and indicate some implications of this view for strategies for dealing with uncertainty in water management. We present an example as an illustration of these concepts. Key words: adaptive management; ambiguity; frames; framing; knowledge relationship; multiple knowledge frames; natural resource management; negotiation; participation; social learning; uncertainty; water managemen

In Search of Complementarity: Insights from an Exercise in Quantifying Qualitative Energy Futures

In this study, we considered a bridging strategy between qualitative and quantitative research with the aim of achieving complementarity. A pilot case study using the Sheffield Elicitation Framework “SHELF” to estimate appropriate inputs for a quantitative energy systems model (based on a qualitative energy future scenario) was used to gain insights. Of novelty are the ethnographic insights of an example translation procedure as well as the methodological approach of the translation procedure itself. This paper reports the findings from this exercise concerning the practicalities of applying such a technique and the observations from the expert elicitation process itself. Based on this pilot, we make two recommendations. The first is the importance of devising a strategy in projects, and research programmes, where bridging between qualitative and quantitative research activities would be most effective. The second is that observations of discussions during the expert elicitation process provide value in the provenance of the estimates for quantitative modelling purposes and provide considerations for further development of qualitative future scenario