'Forecast error' diaporamas de présentation

Demand Management and FORECASTING

Demand Management and FORECASTING. Operations Management Dr. Ron Lembke. Demand Management. Coordinate sources of demand for supply chain to run efficiently, deliver on time Independent Demand Things demanded by end users Dependent Demand Demand known, once demand for end items is known.

765 views • 63 slides

765 views • 61 slides

Operations Management

928 views • 60 slides

VOLATILITY

VOLATILITY Chapters 4-8 Richard H. Thaler Advances in Behavioral Science Part II - Volatility Do Stock Prices Move Too Much to Be Justified by Subsequent Changes in Dividends? What Moves Stock Prices? Does the Stock Market Rationally Reflect Fundamental Values?

1.03k views • 44 slides

Forecasting

Forecasting. BUS255. Goals. By the end of this chapter, you should know: Importance of Forecasting Various Forecasting Techniques Choosing a Forecasting Method. Forecasting. Forecasts are done to predict future events for planning

847 views • 42 slides

Background Error Covariance Modeling

583 views • 40 slides

Martingales

825 views • 37 slides

Demand Management and Forecasting

Demand Management and Forecasting. Chapter 15. Learning Objectives. Understand the role of forecasting as a basis for supply chain planning. Compare the differences between independent and dependent demand.

757 views • 34 slides

Supply Chain Management Managing Material Waiting Time

Supply Chain Management Managing Material Waiting Time. Outline. A key to matching supply and demand Levers for improved matching of supply and demand The bullwhip effect: Barilla The impact of aggregation. The Procurement or supply system. The Operating System. The Distribution System.

540 views • 33 slides

Managing Flow Variability: Safety Inventory

403 views • 33 slides

ARIMA Modelling and Forecasting

ARIMA Modelling and Forecasting. Introduction. Describe the stationarity of the AR process Determine the mean and variance of the AR process Assess the importance of Box-Jenkins methodology Describe the various types of forecasts Evaluate the measures of forecast importance.

695 views • 30 slides

International Finance

International Finance. Forecasting Exchange Rates. Why Firms Forecast XRs. Hedging decisions Hedging payables and receivables Short-term financing decisions Which currency to borrow in Low rate, weakening currency. Why Firms Forecast XRs. Short-term investment decisions

395 views • 22 slides

Variational data assimilation and forecast error statistics

358 views • 21 slides

PRESIDENTIAL DECISION 2 FEB 2010

NPOESS Preparatory Project - Joint Polar-orbiting Satellite System Program Overview John Furgerson ( john.furgerson@noaa.gov , (240) 684-0966) NOAA JPSS Program Office 17 May 2011. PRESIDENTIAL DECISION 2 FEB 2010. NPOESS Program Terminated 30 Sep 2010

328 views • 19 slides

Natural Gas Prices and Industrial Sector Consumption Responses: An Experimental Module for STIFS

Natural Gas Prices and Industrial Sector Consumption Responses: An Experimental Module for STIFS Frederick L. Joutz, Associate Professor Department of Economics The George Washington University Washington, Dc 20052 (202) 994-4899 [e-mail bmark@gwu.edu ] Dave Costello

498 views • 18 slides

Observation impact in East Asia and western North Pacific regions using WRF-FSO system

298 views • 15 slides

PNM Wind Resource Integration Study

Electric Services. Transmission Operations. PNM Wind Resource Integration Study. Preliminary Results. Abraham Ellis Public Service Company of New Mexico. PNM Balancing Authority. Small, not much flexibility 2500 MW summer peak, 1200 MW spring off-peak

280 views • 11 slides

Lower Colorado Basin: Salt/Gila/Little Colorado and Virgin

166 views • 9 slides

Problem 5-24

Problem 5-24. Sales of industrial vacuum cleaners at R. Lowenthal Supply Co. over the past 13 months are as follows:. (a) Moving average with three periods, determine the demand for vacuum cleaners for next February. (b) Using a weighted moving average with three periods,

6.28k views • 8 slides

DIAMET wp C.2/C.3

DIAMET wp C.2/C.3. Ross Bannister General New postdocs (Laura Baker and Ali Rudd). Renewed proposal for MONSooN computer time. C.2: Sources of forecast error (leader Stefano Migliorini )

102 views • 2 slides