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Foreacasting
Notes on Business Forecasting
13
Business
Undergraduate 1
02/05/2013

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Term
Forecasting
Definition
Process of predicting future events
Term
Types of Forecasts by Time Horizon
Definition
Short Range- Usually less than one year. used to schedule jobs and worker assignments
Medium Range_ between 1-3 years. involves the planning or sales and productions as well as budgeting

Long Term forecast- Over 3 years. usually used to plan new products or expansion of large assets such as facility location or opening a new branch
Term
Principles of Forecasting
Definition
Forecasts are rarely perfect
The shorter the period the more accurate the forecast will be
forecasts for individual items are less accurate than forecasts for grouped data
Term
Importance of Forecasting
Definition
It is the only estimate of demand before the actual demand is derived.
It impacts human resources, capacity and supply chain management
Term
Forecasting Models
Definition
Qualitative Methods: Educated guesses or generated subjectively by the forecaster

Quantitative methods: Generated through mathematical means
Term
Qualitative Methods
Definition
  1. Executive Opinion: Managers meet and create a forescast. Usually good for strategic or forecasting a new product. one persons opinion can dominate it, causing a weakness in the forecast
  2. Market Research: utilises surverys, interviews and questionnaires to gather cprefrences of consumers. but developing these questionnaires can be difficult.
  3. Delphi Method: Develops concensus among experts. great for forecasting long term product demand but it can be time consuming
Term
Quantitative Methods
Definition
  1. Time Series Model: Assumes the future will follow the same pattern as the past. Information needed is contained in a time series of data 
  2. Casual/ Associative Model: Explores cause and effect relationships. Also uses leading indicators to predict
Term
Time Series Patterns
Definition
  1. Level or Horizontal Pattern: data follows a horizontal pattern around the mean
  2. Trend Pattern: Data is progressively increasing or decreasing
  3. Seasonal Pattern: Data displays a regular repeating pattern
  4. cycle- data increases then decreases over time 
Term
Selecting the right forecast model
Definition
1.The amount & type of available data: Some methods require more data than others
2.Degree of accuracy required:Increasing accuracy means more data
3.Length of forecast horizon: Different models for 3 month vs. 10 years
4.Presence of data patterns: Match the forecasting model to the time series pattern. (trend, seasonal, cyclical, random)
Term
Forecasting Across the Organization
Definition

Forecasting is critical to all functions of a business :

  1. Marketing: forecasting allows them to predict deman as well as future sales 
  2. Finance: forecasts stock prices, potential financial performance and capital investment needs 
  3. Human Resources: forecasts future hiring requirments 
Term
Forecasting Calculations using Exponential Smoothing 
Definition

Next Period Forecast= (Smoothing Constant* Actual)+( Remaining Smoothing Constant* Previous Forecasted amount)

 

Smoothing Constant+ Remaining Smoothing Constant= 1


Absolute Error= difference between the forecasted amount and the actual amount 


Time

 

Forecast

Actual

Absolute

Error

Calculations for the next periods Forecast

Jan

250

261

 

Smoothing Constant has to equal one ie .7 remaining .3

Feb

255

253

2

 

Mar

248

257

9

Next Fore = (SC*Actual) + (RSC * Previous Forecast)

Apr

255.2

 

 

  255.2      =  .8  *   257     +    .2    *    248

May

 

 

 

 

June

 

 

 

 

 

 

 

 

 

Term
Forecasting Calculations using Moving Average 
Definition

 

(For example a 2 month moving average was used, you can use any amount of months for moving average) 

 


Calculations start in march because you have 2 months worth of information.

To calculate, find the average or the actual of the two months previous of the month that is being forecasted.

 

April Forecast= March Actual + February Actual   / 2


Time

Forecast

Actual

Absolute Error

Calculations for the next periods Forecast

Jan

250

261

11

 

Feb

255

253

2

 

Mar

248

257

9

Next Forecast         March Actual     +   February Actual   / 2

Apr

255

 

 

                                      257           +            253                / 2 = 255

May

 

 

 

 

June

 

 

 

 

 

 

 

 

 

Term
Forecasting Calculations using Weighted Moving Average 
Definition

Method is similar to moving average but a weight is put on each time period (month)

 

Period  1 = . 5

Period  2 = . 3

Period  3=  . 2

 

(NB: Period 1 would be the month closest to the one being forecasted and period 3 being the furthest away: uning a 3 month weighted average) 


Time

Forecast

Actual

Absolute Error

Calculations for the next periods Forecast

Jan

250

261

11

 

Feb

255

253

2

 

Mar

248

257

9

Next Fore        (March * .5) +   (February  *.3) +   ( January    *.2)

Apr

256.6

 

 

                              257   *. 5  +       253         * .3 +          261       * .2 = 256.6

May

 

 

 

 

June

 

 

 

 

 

 

 

 

 

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