Đang chuẩn bị liên kết để tải về tài liệu:
Lecture Introduction to operations management - Chapter 11: Forecasting

Đang chuẩn bị nút TẢI XUỐNG, xin hãy chờ

In this chapter we will discuss: A forecasting framework, qualitative forecasting methods, time-series forecasting, moving average, exponential smoothing, forecasting errors, advanced time-series forecasting, causal forecasting methods, selecting a forecasting method. | Operations Management Contemporary Concepts and Cases Chapter Eleven Forecasting Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Chapter Outline A Forecasting Framework Qualitative Forecasting Methods Time-Series Forecasting Moving Average Exponential Smoothing Forecasting Errors Advanced Time-Series Forecasting Causal Forecasting Methods Selecting a Forecasting Method Collaborative Planning, Forecasting, and Replenishment A Forecasting Framework Focus of chapter is on forecasting demand for output from the operations function Demand may differ from sales Difference between forecasting and planning Forecasting: what we think will happen Planning: what we think should happen Forecasting application in various decision areas of operations (capacity planning, inventory management, others) Forecasting uses and methods (See Table 11.1) Use of Forecasting: Operations Decisions 11- Use of Forecasting: Marketing, Finance & HR 11- ‘Qualitative’ Forecasting Methods Based on managerial judgment when there is a lack of data. No specific model. Major methods: Delphi Technique Market Surveys Life-cycles Analogy Informed Judgment (naïve models) Time-Series Forecasting Components of time-series data: Average level Trend—general direction (up or down) Seasonality—short term recurring cycles Cycle—long term business cycle Error (random or irregular component) “Decomposition” of time-series Data are decomposed into four components Moving averages Exponential smoothing Assumes no trend, seasonal or cyclical components Simple Moving Average: Weighted Moving Average: Moving Average Moving Average Period Actual Demand Forecast 1 10 2 18 3 29 4 - 19 (10+18+29)/3 = 19 Period 5 forecast will be (18+29+actual for period 4)/3 Compute three period moving average (number of periods is the decision of the forecaster) Figure 11.2: Time-Series Data Note: The more periods, the smoother the forecast. The new average is computed from the old | Operations Management Contemporary Concepts and Cases Chapter Eleven Forecasting Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Chapter Outline A Forecasting Framework Qualitative Forecasting Methods Time-Series Forecasting Moving Average Exponential Smoothing Forecasting Errors Advanced Time-Series Forecasting Causal Forecasting Methods Selecting a Forecasting Method Collaborative Planning, Forecasting, and Replenishment A Forecasting Framework Focus of chapter is on forecasting demand for output from the operations function Demand may differ from sales Difference between forecasting and planning Forecasting: what we think will happen Planning: what we think should happen Forecasting application in various decision areas of operations (capacity planning, inventory management, others) Forecasting uses and methods (See Table 11.1) Use of Forecasting: Operations Decisions 11- Use of Forecasting: Marketing, Finance & HR 11- .

TAILIEUCHUNG - Chia sẻ tài liệu không giới hạn
Địa chỉ : 444 Hoang Hoa Tham, Hanoi, Viet Nam
Website : tailieuchung.com
Email : tailieuchung20@gmail.com
Tailieuchung.com là thư viện tài liệu trực tuyến, nơi chia sẽ trao đổi hàng triệu tài liệu như luận văn đồ án, sách, giáo trình, đề thi.
Chúng tôi không chịu trách nhiệm liên quan đến các vấn đề bản quyền nội dung tài liệu được thành viên tự nguyện đăng tải lên, nếu phát hiện thấy tài liệu xấu hoặc tài liệu có bản quyền xin hãy email cho chúng tôi.
Đã phát hiện trình chặn quảng cáo AdBlock
Trang web này phụ thuộc vào doanh thu từ số lần hiển thị quảng cáo để tồn tại. Vui lòng tắt trình chặn quảng cáo của bạn hoặc tạm dừng tính năng chặn quảng cáo cho trang web này.