Importance of Forecasting

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Chapter 6Need and Importance of

Forecasting


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Need and Importance of Forecasting

1. Introduction2. Concept of forecasting

3. Need of forecasting in POM

4. General steps in the forecasting5. Importance and application of

forecast in POM


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Forecasting

Predict the next number in the pattern:

a) 3.7, 3.7, 3.7, 3.7, 3.7, ?

b) 2.5, 4.5, 6.5, 8.5, 10.5, ?

c) 5.0, 7.5, 6.0, 4.5, 7.0, 5.5, 4.0, 6.5, ?


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Forecasting

Predict the next number in the pattern:

a) 3.7, 3.7, 3.7, 3.7, 3.7,

b) 2.5, 4.5, 6.5, 8.5, 10.5,

c) 5.0, 7.5, 6.0, 4.5, 7.0, 5.5, 4.0, 6.5,

3.7

12.5

5.0

+2.5 -1.5 -1.5 +2.5 -1.5 -1.5 +2.5 -1.5


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Concept of Forecast

Forecasting1. The process of estimating a future event by

casting forward past data.

2. Past data is systematically combined in

predetermined way to obtain the estimate offuture.

3. Forecast is an estimate of future values of

certain specific indicators relating to decision /

planning situation.4. Single or multiple indicators are essential for

forecasting.

5. Number of indicators and degree of detail

depends upon the intended use of forecast.



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Accounting Cost/profit estimates

Finance Cash flow and funding

Human Resources Hiring/recruiting/training

Marketing Pricing, promotion, strategy

MIS IT/MIS systems, services

Operations Schedules, MRP, workloads

Product/service design New products and services

Forecasts rarely perfect because of randomness

Forecasts more accurate for groups vs. individualsForecast accuracy decreases as time horizon increases


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Elements of Good Forecasting

Timely

AccurateReliable

Written


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Strategic decision (1-5 year)Product design & mix

Facility location & capacityProcess design &

Technology

Concept of Forecast

Aggregate planning (3-12

months horizon)Workforce size work shifts.Aggregate production,

Planning over time,subcontracting, demand

modification

Short term planning (1-90days horizon)

Personnel scheduling andsequencing, Material

purchasing


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Need of Forecast in POM

1. Purpose2. Time

Purpose

1. Future conditions offer a Purpose / Target to be

achieved.2. Purpose is to take advantage of or to minimize

the impact of future conditions (If adverse)

Example: Plan to set up additional plant to

increase production capacity.a). Estimate the future demand supply gap.

b). Calculate the production target to take advantage of future demand

supply.

c). Prepare action plan and implement

4. Time factor is important.



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Need of Forecast in OM1. Purpose 2. Time

Time

1. Time is a resource2. Organize resources to implement plan

3. Planning and implementation is requiredINTIME.



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Need of Forecast in OM1. Purpose 2. Time

Example: (Take advantage of future demand supply gap)

1. T1= Time taken to finalize the alternative as

set up and additional plant

2. T2= Location of additional plant chosen3. T3= Technology negotiation, Finance provision,

land purchase activities, Legal obligations

consideration,

4. T4= Construction, erecting testing, commercialproduction

5. T (Minimum time to plan and implement)=

T1+T2+T3+T4


G l t i th f ti


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General steps in the forecasting process.

Application Indicators Time span

New plant for

production

expansion

Long term demand, longterm production capacity

of all producers.

5 or more years orsome time less

Step 1 Determine purpose of forecast

Step 2 Establish a time horizon

Step 3 Select the indicator relevant to the need

Step 4 Select the forecast modelStep 5 Data collection

Step 7 Monitor the forecast

The forecastThe forecast

Step 6 Prepare forecast


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Step-1: Identify the general need. (Purpose) Unfulfilled demand

Need to expand production

Decision required as how much and when?

Step:2 Establish the time horizon

Time estimate to erecting of new plant

Forecast cover a period of 5 years including

the erection period of 3 years.



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Step-3: Select indicator relevant to the need.Indicators identified as per product and process

Industry sales

Competitors present and projected capacity

Population projection

Income level

Economic development


Step:4 Select the forecast model to be used.Model must be reliable and selection depends

upon the type of data.


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Step-5: Data Collection Data relevant to various indicators from

appropriate source.

Relevant data must be accurate.

Data availability must be in time.

Data must be sufficient.

Step-6: Prepare Forecast

Apply model using the data collected andcalculate the value of the forecast.



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Step-7: Monitor the forecast and Evaluate All models have methods of calculating upper

and lower value in which the given forecast is

expected to remain with certain level of

probability.

Evaluation can also be performed from

logical point of view whether the value

obtained is logically feasible?



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Importance and Application of forecasting in OM.

Forecast enables Op manager to take betteraction regarding future.

Enables Op manager to discharge their

function more effectively.Op Manager is better informed to set up

objective more clearly.

Thinking, alternative generation and selection

becomes more focused.Organize and implement his action with time

line.



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Importance and Application of forecasting in

OM.For smaller error we have to use most

sophisticated model of forecasting.

Cost of model development, forecasting and

maintaining trends are high.

There must be trade off between choice of

model and the cost.



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Importance and Application of forecasting in OM.

Forecast Importance directly proportional to

(Result of action based on forecast)(Result

of an action for the same situation without any

forecast)

If the difference is positive and large thenimportance is more otherwise not important.

Forecast Error = (value forecast-value actually

happened)For smaller error we have to use mostsophisticated model of forecasting.


N d d I t f F ti


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Importance &Application of forecasting in OM.Need and Importance of Forecasting

Application Indicators Time span

New plant forproduction expansion Long term demand, long termproduction capacity of allproducers.

5 or more years orsome time less

Seasonal production

planning

Demand cycle from one to

other peak

6 months or pre

defined.

Capital Planning Long term money markettrends, interest rate trends

One or more years

Intermediate Op

Planning

Intermediate demand and shift

in preferences

Upto about two

years

Short term production

adjustment

Short term demand and short

term material/input

About six weeks

Scheduling production Order position, emergency

orders

One week

Product development Long term sales trend

technological development inrelated fields

Two years or more


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Methods of Forecasting

All forecasting methods can be divided into two broad

categories:

Qualitative

Quantitative.

Division of forecasting methods into qualitative andquantitative categories is based on the availability of

historical time series data.

Many forecasting techniques use past or historical

data in the form of time series.A time series is simply a set of observations measured

at successive points in time or over successive periods

of time.


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Methods of Forecasting

All forecasting methods can be divided into two broad

categories:Qualitative

A key advantage of these procedures is that they canbe applied in situations where historical data are

simply not available. And if historical data areavailable, significant changes in environmentalconditions affecting the relevant time series may makethe use of past data irrelevant and questionable in

forecasting future values of the time series.


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Qualitative Forecasting Methods

Qualitative

Forecasting

Models

MarketResearch/

Survey

SalesForce

Composite

ExecutiveJudgement

DelphiMethod


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Briefly, the qualitative methods are:Executive Judgment: Opinion of a group of high level expertsor managers is pooled.

Sales Force Composite: Each regional salesperson provides

his/her sales estimates. Those forecasts are then reviewed tomake sure they are realistic. All regional forecasts are thenpooled at the district and national levels to obtain an overallforecast.

Market Research/Survey: Solicit input from customerspertaining to their future purchasing plans. It involves the use ofquestionnaires, consumer panels and tests of new products andservices.

Qualitative Methods


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Delphi Method: As opposed to regular panels where theindividuals involved are in direct communication, this methodeliminates the effects of group potential dominance of the mostvocal members. The group involves individuals from inside as wellas outside the organization.

Typically, the procedure consists of the following steps:

Each expert in the group makes his/her own forecasts in formof statements

The coordinator collects all group statements and summarizesthemThe coordinator provides this summary and gives another set ofquestions to each group member including feedback as to theinput of other experts.

The above steps are repeated until a consensus is reached.

Qualitative Methods


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Quantitative Forecasting Methods

Quantitative

Forecasting

Regression

Models

2. Moving

Average1. Naive

Time Series

Models

3. Exponential

Smoothinga) simple

b) weighteda) level

b) trend

c) seasonality

Q i i h d f i


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Quantitative Methods of Forecasting

Time Series Models:

Naive Approach Moving Average

Exponential Smoothing

Naive Approach A forecasting technique that assumes

demand in the next period is equal to the

demand in the most recent period.

Cost effective- efficient forecasting model

but is just starting point to follow most

sophisticated model.

Q i i M h d f F i


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Native Approach

Example-1;

The sale of a product is 100 units in Nov-13.

What is the sales forecast of this productin Dec-13?

Solution;

The sales forecast for the month of Dec-13

will be 100 units of product.

Q tit ti M th d f F ti


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Moving Average

To generate a forecast number ofhistorical actual data values are used.

It is based upon the assumption that the

market demand will stay fairly steady overtime.

Moving Average=

Sum of demand in previous n periods

n i.e. ( no of period in moving average.



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Moving Average : Example-2:

Calculate the forecast for Jan-11 on 3 months moving average?

Month Actual Sales 3 months Moving AverageJan-10 10

Feb-10 12

Mar-10 13

Apr-10 16 (10+12+13)/3= 11.66

May-10 19

Jun-10 23

Jul-10 26

Aug-10 30

Sep-10 28

Oct-10 18

Nov-10 16

Dec-10 14



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Moving Average : Example-2:

Calculate the forecast for Jan-11 on 3 months moving average?

Month Actual Sales 3 months Moving AverageJan-10 10

Feb-10 12

Mar-10 13

Apr-10 16 (10+12+13)/3= 11.66

May-10 19 (12+13+16)/3= 13.66

Jun-10 23 (13+16+19)/3= 16

Jul-10 26 (16+19+23)/3= 19.33

Aug-10 30 (19+23+26)/3= 22.66

Sep-10 28 (23+26+30)/3= 26.33

Oct-10 18 (26+30+28)/3= 28

Nov-10 16 (30+28+18)/3= 25.33

Dec-10 14 (28+18+16)/3= 20.66



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Moving Average :Weighted Moving Average:

Example:

Consider the actual sales of past example with the

weight applied as given below

Weight Applied Period3 Last month

2 Two months ago

1 Three months ago________

6

Forecast = (3x sales of last month + 2x sales 2 months

ago+1x sales 3 months ago)/ 6 i.e Sum of weight



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Quantitative Methods of ForecastingMoving Average :Weighted Moving average: Example-3: Find the forecast if the wightage is 3 for most

recent month, 2 for one month before most recent month and 1 for two month

before most recent month.

Month Actual Sales 3 months weighted Moving Average

Jan-10 10

Feb-10 12

Mar-10 13Apr-10 16 (3x13+2x12+10x1)/6= 12.16

May-10 19 (3x16+2x13+1x12)/6= 14.33

Jun-10 23

Jul-10 26

Aug-10 30

Sep-10 28

Oct-10 18

Nov-10 16

Dec-10 14 (3x16+2x18+1x28)/6= 18.66



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Quantitative Methods of ForecastingSeasonal Variation Data

Example 4:Calculate the quarterly seasonal forecast as per given data

Quarter Salesestimate in $

Quarterly seasonalindices

Seasonal forecast in $

1 100000 1.3 1.3*100000=1300002 120000 0.9 0.9*120000=108000

3 140000 0.7 0.7*140000=98000

4 160000 1.15 1.15*160000=184000

Consider Example-5 for forecasting based upon seasonal

variation data and Example-6 Trend projection data


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Importance of Forecasting