Demand Forecasting

Demand ForecastingForecast:It is a statement / an estimate about the future.It helps managers by reducing some of the uncertainties &

enables them to develop meaningful plans.It helps managers to determine in the present what course of

action they will take in future Forecasting :It is an art & science of predicting /estimating future events.It is not a mere guess or prediction about the future without

any rational basis.It may involve taking historical data & projecting them in to

the future.It may include a managers good judgment or a intuitive

prediction in the absence of historical data

Demand Forecasting: contd Any business organization can not afford to avoid forecasting &

just wait to see what happens & then take its chances.Effective planning in both short & long run depends on forecast

of demand for the companys products. Uses of forecasts: Helps in planning the productive system involving i) Long range

& ii) Short & intermediate plans.i) Long range plans relate to a) what products & services to

offer, b) what facilities & equipments to have, c) where to locate them,

ii) Short & intermediate plans involves a) Planning inventories & workforce levels, b) Planning purchasing, c) Production, scheduling & budgeting

Demand Forecasting: contdForecasts are also used to predict Profits, revenue, costs. prices

productivity changes, availability of energy, raw materials interest rates, movements of key economic indicators e.g. GNP, inflation etc, prices of stocks & bonds.

Forecasting is necessary in Production & operations management for the followings:

i) New facilities planning:a) Designing & Building new facility (Factory)b) Designing & implementing new production process-These may take as long as 5-years or even more.-These strategic activities are based on long-range forecast of demand for existing & new products to allow needed time for production & operations managers for plant location, plant layout, installation of machinery & equipments to produce products & services to meet the demand.

Demand Forecasting: contdii) Production Planning:Rate of producing the products must be matched with the

demand which may be fluctuating over the time period in the future.

Since it may take several months to change the rate of output ofproduction processes, production managers need medium otintermediate range demand forecasts to enable them to arrange for the production capacities to meet the monthly demands which are varying.

iii) Workforce Scheduling:The forecasts of monthly demand may further be broken down

to weekly demands, & the workforce may have to be adjusted to meet these weekly demands.

This may have to be done through reassignment of jobs to workforce allowing overtime, layoffs or hiring in order to match the weekly production rate to the weekly demands.

Hence, short range forecasts are needed to enable the managers to have the necessary lead time to fine tune the workforce changes to meet the weekly production demands.

Demand Forecasting: contdiv) Financial Planning:

Sales forecasts are the driving force in budgeting. -These provide timing the timing of cash inflows (Sales revenues) & also provide a basis for budgeting the requirements of cash outflows for purchasing materials, payments to employees & to meet other expenses of power & utilities etc.Thus, sales forecasts help finance manager to prepare budgets taking in to consideration the cash inflows & cash outflows.

Demand Forecasting: contdType & characteristics of forecasts based on time horizon.

Exploration of trends, judgment, Exponential Smoothing

May be at item level for planning of activity level, should be at item level for purchasing & inventory control

Short run adjustment of production & personnel levels, purchasing, job scheduling, capacity changes by over time, lay offs etc

Short range (! week to

3- months)

Collective opinion , Time series / regression analysis, judgment

Numerical, not necessarily at the item level. Estimate of reliability needed

Aggregate planning, cash & capital budget s planning for Production & inventory

Medium or intermediate range(3-months to 3-years)

Technological, economic, Demographic, marketing studies, judgmental.

Broad, general, often only qualitative

Planning for business, product, capital, facility, location

Long range (3-5 years or more)

Forecast MethodsCharacteristicsApplicationForecast Horizon

Demand Forecasting: contdTypes of forecasts:1 Technological forecastsConcerned with rates of technological progress. -

These provide companies with new products & materials to offer for sale. -Product remaining unchanged, a new process for producing the products can be developed with new or improved technology using new machinery & equipment.

2 Economic forecasts These are the statements of expected future business

conditions published by government agencies. -These address the business cycle by predicting inflation rates, money supplies, housing starts & other economic indicators e.g. tax revenues, levels of employment, GNP etc .-These give ideas about long & intermediate range business growth to business organisations.

Demand Forecasting: contd3 Demand forecasts:

-These are projection of expected level of demand for the cos product or services throughout some future period & usually provide the basis for the cos planning & control decisions.

-These drive a companys production capacity & scheduling systems & serve as inputs to financial, marketing & Human Resource planning.

Economic & technological forecasts are specialised techniques which fall out side the scope of production & operation managers functions.

Features common to all forecasts:- These generally assume that same underlying reasons that

existed in the past will continue to exist in the future -These are rarely perfect. Actual demand, differs from forecasted

demand. Allowances should be made for inaccuracies.- Forecasts for group of items tend to be more accurate than

forecasts for individual items.- Forecast accuracies decreases as the time period for the

forecast (forecasting time horizon) increases.

Demand Forecasting: contdSteps in forecasting process: Involves 7-basic steps1)Determine the purpose / objectives of the forecast. Questions like what

are the objectives & when is the forecast needed determine the level of details required in the forecast, the amount of resources e.g. man power, computer time, Rs etc, that can be justified & the level of accuracy needed.

2) Select the item requiring forecasts, determine if it is for a single product or group of products (product line)

3) Determine time horizon for the forecast i.e. short / medium / long-term & whether weekly, monthly, quarterly or yearly.

4) Select the forecasting model i.e. quantitative or qualitative. Former is statistical & the later is judgmental.

5) Gather & analyse the data needed for the forecast. Identify the assumptions that are made in conjunction with preparing & using the forecast.

6) Prepare the forecast using the selected method.7) Monitor the forecast whether it is performing satisfactorily. If not,

review the method, assumptions, validity of data & modify data if needed & prepare a revised forecast.

Demand Forecasting: contdElements / requirements of a good forecast:A forecast should be - Timely i.e. the forecasting horizon must have the time

necessary to implement possible changes in production capacity, financial needs etc.

- Accurate & the degree of accuracy should known- Reliable i.e. consistent in accuracy- Expressed in meaningful units e.g. Rs, units of products

machines & skills needed.- Written form to permit an objective basis for evaluating the

forecast once the actual results are known.- The technique should be simple to understand & use

(comfortable for users)

Demand Forecasting: contdObjectives of demand forecasting i) Short range objectives- ii) medium or long range a) Formulation of production strategy & policy: to bridge the

gap between demand & supply & to ensure- estimating the material requirement on regular basis- Optimum utilisation of plants & equipments - Planning the availability of labour on the regular basis

b) Formulation of pricing policy- Demand forecasting enables management to formulate suitable mechanism for fixing the prices for products to be sold.

c) Planning & control of sales- Demand forecasting facilitate territory design & determination of quotas to be assigned to sales people.

Demand Forecasting: contdii) Medium or Long-range objectives:a) Long-range planning for production capacity:

The installed capacity of the plant is usually based on long-term demand forecasts.

b) Labour requirements (Employment levels)-These are based on reliable medium/long term demand forecasts so as to optimise the cost of production over the long-term planning horizon.

c) Restructuring the capital structure-Long-term forecasts facilitate planning for long-term finance requirements at reasonable financial costa & other terms & conditions for obtaining finance from financial institutions as well as planning for internal financial resources to meet long-term financial needs.

Demand Forecasting: contdClassification of demand forecasting methods:i) Qualitative - These consist mainly of subjective inputs, often of

non-numerical description & ii) Quantitative These involve either projection of historical data

or the development of association models which attempt to use casual variables to arrive at the forecast.

Overview of qualitative methods:1) Jury of executive opinion- In this the opinions of a small group

of high-level executives (managers) are taken, based on which a group estimate of demand is obtained as the forecast.Advantage- i) uses experience & knowledge of two or more managers to arrive at a single forecast .ii) Can be used for technological forecasting iii) Can be used for forecasting for new products. iv) Can be used to modify an existing forecast to account for unusual circumstances.

Demand Forecasting: contdJury of executive opinion- contdDisadvantages- i) It can be costly because it takes valuable

executive time. ii) some times gets out of control or gets delayed. iii) difficult to get consensus opinion of several experts.

2) Salesforce composite method - Also known as Pooled salesforce estimate method.

In this each sales person estimates what sales will be in his / her territory.

These estimates are then reviewed to ensure that they are realistic.

Then they are combined at the district or national level to arrive at the overall forecast.

Demand Forecasting: contd2) Salesforce composite method-contd:Advantages- i) The sales force is the group closest to the

customers. They are most likely to know which product or services, customers will be buying in the near future & in what quantities. ii) Sales territories are divided in to districts or regions & forecasts for district or regions will be useful in inventory management, distribution & sales staffing.

Disadvantages- i) Individual bias of sales people may affect the sales forecast (Some are optimistic & some pessimistic) ii) Sales people may be unable to distinguish between what customers would like to do & what they actually will do. iii) some sales people may be overly influenced by their recent experience. iv) If the firm uses sales persons estimate as a performance measure , sales people may deliberately under estimate their forecast so that their performance will look goodwhen they exceed their quotas which are fixed based on their estimates

Demand Forecasting: contd3) Market Research method:

A sample of consumers survey is the systematic approach to determine their interest in a product or service. This method may be used to forecast demand for short, medium or long term. Advantage: i) Consumers opinion regarding their future purchasing plans are better than executive opinion because it isthe consumers who determine demand. Also this is first hand & direct information obtained by consumer survey. Disadvantages: i) As opinions are obtained from a sample of customers, it may lead to forecast error if the sample size is inadequate. ii) Survey require considerable knowledge & skills to handle correctly. iii) Survey can be expensive & time consuming. iv) Response rate of mailed questionnaire may be poor. v) The survey results may not reflect the opinion of the market.

Demand Forecasting: contd4) Delphi Method: It is also a judgemental method.- In this method opinions are solicited from a number of other

managers & staff personnel.-The decision makers consist of 5-10 experts who will be

making actual forecast. -The staff personnel assist decision makers by preparing,

distributing, collecting & summarising a series of questionnaires & survey results.

-The managers whose judgements are valid are the respondents. This group provides inputs to the decision makers before forecast is made.Responses of each respondent are kept anonymous which tends to encourage honest responses.

- Each new questionnaire is developed using the information extracted from the previous one, thus enlarging the scope of information on which participants base their judgements. The goal is to achieve consensus forecast.

Demand Forecasting: contdDelphi Method: contdAdvantages:i) This method can be used to develop long-range forecasts

of product demand & sales projections for new productsii) A panel of experts may be used as participants

(respondents)Disadvantages:i) The process can take a long time ii) Responses may be less meaningful because respondents

are not accountable due to anonymity.iii) High accuracy may not be possible. iv) Poorly designed questionnaire will result in ambiguous or

false conclusions

Demand Forecasting: contdOverview of quantitative methods: 5-methods, under 2-catagorie

They all use historical data.1- a) Nave approach (lacking experience or judgement)

b) Moving averages method c) Exponential smoothing method These are time series models

2- a) Trend projection ] These are b) Linear regression analysis ] Causal models

Time series models: -Predict on assumption that the future is a projection of past.-They look at what has happened over a period of time & use a series

of past data to make a forecast for the future.Causal (or association) models: eg linear regression incorporate the

variables or factors that might influence the quantity being forecast. The demand or sales forecast is a dependent variable & other factors that affect demand are independent variables ( causal variables)

In linear regression the dependent variable (Demand) is related to one or more independent variables by a linear equation

Demand Forecasting: contdTime series forecasting methods:-A Time series is a time-ordered sequence of observations

taken at regular intervals over a period of time (hourly, daily, weekly, monthly, quarterly or annually)

-Data may be measurement of demand, earnings, profits, outputs, productivity, consumer price index etc.

Decomposition of time-series:-Analysis of time-series data requires the analyst to identify

the underlying behaviour of the series. This can be done by plotting the data with time on X-axis,

& data on Y-axis & visually examining the plot. One or more patterns might appear. They are- trends, seasonal variations, cycles & random or irregular variations ( errors)

Demand Forecasting: contdTrend- refers to gradual, long term, upward or downward

movement in data over time. Changes in income, population, age, distribution or cultural views may account for such movements.

Seasonality- refers to short term, fairly regular variations related to factors such as weather, holidays, vacation etc. Seasonal variations can be daily, weekly or monthly.

Cycles- are wave like variations of more than one year duration or which occur every several years. They are usually tied with business cycle related to a variety of economic , political, or agricultural conditions.

Random Variations are residual variations which are blips in the data caused by chance & unusual situations, which cannot be predicted (eg war, earthquake, flood etc)

Demand Forecasting: contdTechniques of averaging-Historical data contain a certain amount of random variation, or

noise which tends to observe systematic movement in data. It is desirable to completely remove any randomness from the data& leave only real variation such as change in demand.

Averaging technique smooth fluctuations in a time series so thatthe forecast can be based on average, to exhibit less variability than the usual data. Averaging techniques generate forecasts to reflect recent values of a time series.

3-Techniques of averaging are- a) Nave approach b) moving averages (simple & weighted) & c) Exponential smoothing.

i) Nave approach: It is the simplest way to forecast & it assumes that demand in the next period is equal to actual demand in the most recent period i.e the current period. example- if actual sales of a product in March 2011 is 300 units, the forecast demand in April 2011 will also be 300 units.

Demand Forecasting: contdii) Moving averages method- It uses a no. of most recent

historical actual data values to generate a forecastThe moving average for n number of periods in the

moving average is calculated as:Moving average= [ demand in previous periods] n

n may be 3,4,5,or 6 for 3,4,5,or 6 period moving averageSimple moving average method:- Used to estimate the average of a demand time series &

remove the effects of random fluctuations.-Most useful when demand has no pronounced trend or

seasonal fluctuations.-** In this we use n period moving average. The average

demand of the n most recent time periods is calculated & used as forecast for the next time period

Demand Forecasting: contd (Simple Moving Average)

[d1+d2+d3] 3 Forecast for 4th month[d2+d3+d4] 3 Forecast for 5th month[d3+d4+d5] 3 Forecast for 6th month

Arithmetic mean values

d1d2d3d4d5d6

123456

Forecast based on simple moving average

Actual Demand

Month(period)

Weighted moving average Decreasing values of weights Forecast for 4th month : such that w = 1[w1d1+w2d2+w3d3] {w1+w2+w3} w3 w2 w1Forecast for 5th month :[w2d2+w3d3+w4d4] {w2+w3+w4} w4 w3 w2Forecast for 6th month :[w3d3+w4d4+w5d6] {w3+w4+w5} w5 w4 w3

Demand Forecasting: contdiii) Exponential smoothing method:

-It is a sophisticated weighted moving average method-Relatively easy to understand & use.-Requires only three items of data: a) this periods forecast, b) actual demand of this period & c) , a greek alphabet called alpha, which is referred to as smoothing constant & having a value between 0 &1.

The formula used is-Next Periods forecast = This Periods forecast + { This periods actual

demand - This Periods forecast }Or Ft = F t -1 + [ A t -1 F t -1 ] Ft = Forecast for period (t),= smoothing constant ] Ft -1 = Forecast for period (t -1)

value between 0 &1] A t -1= Actual demand for period (t -1)Commonly used value of ranges between 0.05 to 0.5

Demand Forecasting: contdFactors to be considered in selection of a forecasting method

are: i) Cost & accuracy, ii) Data available, iii) Time span, iv) Nature of products & services v) Impulse response & noise dampening.

i) Cost & accuracy- A trade-off may result between cost & accuracy. High forecast accuracy can be obtained- at a high cost- will require more data which are difficult to obtain & models are difficult to design, implement & operate.Delphi, market research, jury of executive opinion, statistical models based on historical data are of low or moderate cost.

ii) Data available: Relevant data availability is important in the choice of forecasting method. Example