Slides 5 3 project sales or production levels using the roll

Terminal Learning Objective• Task: Project Sales or Production Levels Using the Rolling Average • Condition: You are training to become an ACE with access to ICAM course handouts, read

Project Sales or Production

Levels Using the Rolling Average

What if?

You planned

for 10 but…

© 2011

Terminal Learning Objective

• Task: Project Sales or Production Levels Using the

Rolling Average

• Condition: You are training to become an ACE

with access to ICAM course handouts, readings, and spreadsheet tools and awareness of

Operational Environment (OE)/Contemporary

Operational Environment (COE) variables and

actors

• Standard: with at least 80% accuracy

• Demonstrate understanding of Trend Projection

concepts

Predicting the Future

What is Trend Projection?

• Uses historical data about past demand to

make estimates of future demand

• Relies on systematic methodologies and

assumptions

• Cannot predict the future or anticipate

catastrophic events

Three Methods

• Regression

• Represents a straight line with the least

squared error from actual

Regression Analysis

• Plots a linear relationship between multiple data points

• Minimizes the “squared errors”

• Square difference between mean and actual to eliminate negative values

• Uses the format y = mx + b where:

Regression Exercise

• Use spreadsheet to predict the 8th, 9th, and

10th event burger demand if the first six

demands were:

• 8 10 9 12 13 15

Spreadsheet Exercise

The spreadsheet returns the equation:

y = 1.4x + 6.2667 Enter the values in the equation to project future demand

Demand for:

Period 8 = 17

Period 9 = 19

Period 10 = 20

Regression Analysis

Example: Using Regression to Estimate

Fixed and Variable Costs

• Consider four quarters of data

Regression Analysis

Notice that four very different sets of data all have very similar regression lines

The x-axis in these graphs represents time periods in series

Regression Strengths and Weaknesses

• Can be calculated very precisely

• But cumbersome to do by hand(use spreadsheet!)

• May be precisely wrong

• Can be used to identify trends

• But by definition cannot predict downturns or

upturns

• Assumes relationship is linear and will remain

linear

• Key assumption for predictions:

• Assumes that the average will be maintained

• Example: Average of Periods 2, 3 & 4 will equal average of periods 1, 2 & 3

Rolling Average Calculation

• The demand for our last twelve periods has

been:

• Task: Calculate the 3-month rolling average

for periods 3-12

Rolling Average Calculation

• The 3-month rolling average is the average

value for the most recent 3 months

Per1 + Per2 + Per3

Rolling Average Calculation

Period

1 not enough data

2 not enough data

Rolling Average Calculation

Rolling Average Calculation

Rolling Average Calculation

Rolling Average Calculation

Period

Graph of Rolling Average

This is a time series X-axis represents sequential time periods

Graph of Rolling Average

This is a time series X-axis represents sequential time periods

Rolling Average vs Regression

This is a time series X-axis represents sequential time periods

Using Rolling Average to Project Future

Using Rolling Average to Project Future

Using Rolling Average to Project Future

What would regression

analysis project?

Which is “right”?

Rolling Average vs Regression

changed the trend

Regression picks up the long term downward trend, predicting another decrease

Rolling Average Strengths and Weaknesses

• Can be calculated very precisely

• But may be precisely wrong

• Simple to calculate

• The main strength of rolling averages is that they

dampen the effect of short term changes

• This helps decision makers avoid knee jerk responses to changes in demand that may not be significant

• Decision makers are often looking for inflection points

• An inflection point in a six month rolling average carries a

lot of weight

Planning Factors

• Assume some cause and effect relationship

• If we suspect that demand for education

counseling decreases when a unit deploys

• We could study the history of that relationship

and determine a planning factor (or ratio) of

sessions per soldier as “a”

• We could then use that factor to plan for the drop

in session demand when X soldiers deploy as

• New demand = a*X

Planning Factor Example

• Given the recent history

determine the planning

factor relating sessions

Planning Factor Example

• Given the recent history

determine the planning

factor relating sessions

Leading Indicators

• Leading indicators are similar to planning

factors with a couple differences

• Leading indicators often have a weaker cause and effect relationship

• Changes in consumer confidence index may foreshadow an increase in sales at the post exchange

• There is a period of time before the effect is seen

(i.e that’s why they are called leading indicators)

Learning Check

• What are planning factors?

• How are planning factors generally expressed?

Practical Exercise