Docsity
Docsity

Prepare for your exams
Prepare for your exams

Study with the several resources on Docsity


Earn points to download
Earn points to download

Earn points by helping other students or get them with a premium plan


Guidelines and tips
Guidelines and tips

SCM Chapter 2 chapter 1,2,3,4,5,6, Summaries of Supply Management

01 DEMAND FORECASTING 02 AGGREGATE PLANNING IN A SUPPLY CHAIN 03 PLANNING SUPPLY AND DEMAND IN A SUPPLY CHAIN

Typology: Summaries

2021/2022

Uploaded on 04/23/2022

vy-truong-thoai
vy-truong-thoai 🇺🇸

2 documents

1 / 31

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
Planning and forecasting in SCM NGUYNTHBÍCH TRÂM, PHD
TRAM.NTB@OU.EDU.VN
pf3
pf4
pf5
pf8
pf9
pfa
pfd
pfe
pff
pf12
pf13
pf14
pf15
pf16
pf17
pf18
pf19
pf1a
pf1b
pf1c
pf1d
pf1e
pf1f

Partial preview of the text

Download SCM Chapter 2 chapter 1,2,3,4,5,6 and more Summaries Supply Management in PDF only on Docsity!

Planning and forecasting in SCM

N G U Y Ễ N T H Ị B Í C H T R Â M , P H D T R A M. N T B @ O U. E D U. V N

Main contents

DEMAND

FORECASTING

01

AGGREGATE

PLANNING IN A

SUPPLY CHAIN

02

PLANNING

SUPPLY AND

DEMAND IN A

SUPPLY CHAIN

03

Demand pattern

The role of forecasting Forecasting provides an estimate of future demand, the basis for planning and sound business decisions. Accurate demand forecasts Purchasing department to order the right amount of products Operations department to produce the right amount of products Logistics department to deliver the right amount of products

Forecasting techniques

  • Qualitative forecasting methods are:
    • Based on intuition or judgmental evaluation
    • Generally used when data are limited,

unavailable, or not currently relevant

  • Quantitative forecasting models use

mathematical techniques that are based on

historical data and can include causal

variables to forecast demand.

Qualitative methods Jury of executive opinion Delphi method Sales force composite Consumer survey

Time series forecasting models Naïve forecast Simple moving average Weighted moving average Exponential smoothing Linear trend forecast

Weighted moving average (See Example 5.2)

Linear Trend Forecasting A linear trend forecast can be estimated using simple linear regression to fit a line to a series of data occurring over time. This model is also referred to as the simple trend model. The trend line is determined using the least squares method, which minimizes the sum of the squared deviations to determine the characteristics of the linear equation. The trend line equation is expressed as: Ŷ = b 0 + b 1 x Where Ŷ = forecast or dependent variable; x = time variable; b 0 = intercept of the vertical axis; b 1 = slope of the trend line. (See Example 5.4)

Quantitative methods (cont.) Cause-and-effect forecasting assumes that one or more factors (independent variables) are related to demand and, therefore, can be used to predict future demand. ◦ Simple linear regression forecast ◦ Multiple regression forecast

Multiple regression forecast When several explanatory variables are used to predict the dependent variable, a multiple regression forecast is applicable. Multiple regression analysis works well when the relationships between demand (dependent variable) and several other factors (independent or explanatory variables) impacting demand are strong and stable over time. The multiple regression equation is expressed as: Ŷ = b 0 + b 1 x 1 + b 2 x 2 + … + bkxk Where Ŷ = forecast or dependent variable; xk = k th explanatory or independent variable; b 0 = constant; bk = regression coefficient of the independent variable xk.

2. Aggregate

planning in a

supply chain

Operational parameters in aggregate planning

  • Production Rate: the number of units to be completed per unit time (such as per week or per month)
  • Workforce: the number of workers/units of capacity needed for production
  • Overtime: the amount of overtime production planned
  • Machine Capacity Level: the number of units of machine capacity needed for production
  • Subcontracting: the subcontracted capacity required over the planning horizon
  • Backlog: demand not satisfied in the period in which it arises but carried over to future periods
  • Inventory on Hand: the planned inventory carried over the various periods in the planning horizon

Trade-off in aggregate planning CAPACITY (REGULAR TIME, OVERTIME, SUBCONTRACTED) INVENTORY BACKLOG/LOST SALES BECAUSE OF DELAY