This document discusses forecasting methods used at Ross Products. It outlines different types of forecasting including quantitative, naive, time series, causal/econometric, judgmental, and artificial intelligence forecasting. Regression analysis is described as part of causal/econometric forecasting. The document also discusses strategic business planning, sales and operations planning, and master production scheduling and control forecasting approaches. It provides an overview of Ross Products and their forecasting procedure using the Log*plus program.

1. FORECASTING AT ROSS
PRODUCTS
By: Ravi Kanudawala (3905139)
Mayur Somaiya (3905128)
Ajay Raval (3905225)

2. FORECASTING
 Forecasting is the process of making statements about events whose
actual outcomes (typically) have not yet been observed.
For example, it might be estimation for some variable of interest at
some specified value date.
 Forecasting is used in the practice of Customer Demand Planning in
every day business forecasting for manufacturing companies.

3. TYPES OF FORECASTING
 Quantitative forecasting
 Naïve forecasting Approach
Time Series Forecasting methods
 Causal / econometric forecasting methods
Judgmental forecasting methods
Artificial Intelligence forecasting methods

4. REGRESSION ANALYSIS
 The Regression Analysis is part of Causal / econometric forecasting
methods.
It includes a large group of methods that can be used to predict future
values of a variable using information about other variables.

5. STRATEGIC BUSINESS PLANNING
 Level of aggregation
 Total sales or output volume
 Top Management involvement
 intensive
 Forecast frequency
 Annual or less
 Length of forecast
 Year by years or quarters
 Usual techniques
 Management judgment, regression.

6. SALES AND OPERATIONS PLANNING
 Level of aggregation
 Product family units
 Top Management involvement
 When reconciling functional plans or moderate
 Forecast frequency
 Monthly to quarterly
 Length of forecast
 Several months to a year by months
 Usual techniques
 Aggregation of detailed forecasts, customer plans

7. MASTER PRODUCTION SCHEDULING AND
CONTROL
 Level of aggregation
 Individual finished goods or components
 Top Management involvement
 Very little or Minimal
 Forecast frequency
 Constantly
 Length of forecast
 A few days to weeks
 Usual techniques
 Projection techniques (smoothing, moving average)

8. INTRODUCTION
 The Ross Products is division of Abbott laboratories and is situated in
Columbus , Ohio.
 It produces a variety of nutritional products including adult medical
nutrition supplements, pediatric infant formulas, as well as ancillary
equipment.
 For example, pump which supplies nutritional liquids to the stomach.
 Mainly there are four manufacturing facilities in US.
 Ross markets its products in United States and Overseas.
 They using log*plus program to perform demand management activities.
Log*plus produces forecasts from nation inputs and monitors actual
demands against these forecasts.

9. PROCEDURE
Marketing and sales
forecasts by products
groups
Vendor-managed
inventory
EDI
Demand Management
Other Customers
Orders
Breakout of national
forecast by plant
International Forecast
Forecast consolidation
and conversion ( to SKU
by plant)
Meeting for revising the
forecast
Forecast available for
manufacturing Planning
Meeting for
forecast review

10. Values of Dependent Variable
Actual
observation
Deviation
Deviation
Deviation
Deviation
Deviation
Deviation
Deviation
ˆ
Y
a bx
Time
Point on
regression
line

11. LINEAR TREND PROJECTION
 Used for forecasting linear trend line
Yi
a
bX i
 Assumes relationship between response variable, Y, and time, X, is a
linear function

12. LINEAR REGRESSION EQUATIONS
Equation:
ˆ
Yi a bxi
n
Slope:
b
x i yi
i 1
n
i 1
Y-Intercept:
a
x i2
y bx
nx y
nx 2