WEEK 4 Flashcards

1
Q

art and science of predicting future events.

A

Forecasting

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2
Q

Elements of a Good Forecast:

A

▪ The forecast should be timely.
▪ The forecast should be accurate
▪ The forecast should be reliable.
▪ The forecast should be expressed in meaningful units.
▪ The forecast should be in writing.
▪ The forecast technique should be simple to understand and use.
▪ The forecast should be cost effective. (The benefits should
outweigh the costs.

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3
Q

CLASSIFICATION OF FORECAST:

A
  • Short Range Forecast
  • Medium-range Forecast (Intermediate)
  • Long-range Forecast
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4
Q
  • It has a time span of three months up to one year
  • It is used for planning, purchasing, job scheduling, workforce levels, job
    assignments and production levels.
A

Short Range Forecast

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5
Q
  • It generally spans from one year to 3 years.
  • It is useful in sales planning, production planning and budgeting, cash
    budgeting and analyzing various operating plans.
A

Medium-range Forecast (Intermediate)

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6
Q
  • It is generally 3 years or more
  • It is used in planning for new products, capital expenditures, facility location or
    expansion, and research and development
A

Long Range Forecast

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7
Q

TYPES OF FORECASTS:

A
  • Economic Forecast
  • Technological Forecast
  • Demand Forecasts (Sales Forecasts)
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8
Q

It addresses the business cycle by predicting inflation rates, money
supplies, housing starts, and other planning indicators.

A

Economic Forecast

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9
Q

It is concerned with rates of technological progress, which can result in
the birth of new products, requiring new plants and equipment.

A

Technological Forecasts

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10
Q

It is the projections of demand for a company’s products and services.

A

Demand Forecasts (Sales Forecasts)

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11
Q

Steps in the Forecasting Process:

A
  1. Determine the purpose of the forecast.
  2. Establish the time horizon.
  3. Obtain, clean and analyze appropriate data.
  4. Select a forecasting technique.
  5. Make the forecast.
  6. Monitor the forecast errors.
  7. Repeat 3 and 6 as new data become available.
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12
Q

STRATEGIC IMPORTANCE OF FORECASTING:

A
  1. Human Resources
  2. Capacity
  3. Supply-Chain Management
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13
Q

➢Hiring, training and laying-off workers all depend on anticipated demand.

A

Human Resources

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14
Q

➢When capacity is inadequate, the resulting shortages can mean undependable delivery,
or loss of customers, and loss of market share.

A

Capacity

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15
Q

➢Good supplier relations and the ensuing price advantages for materials and parts
depend on accurate forecasts

A

Supply Chain Management

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16
Q

FORECASTING APPROACHES:
Qualitative Forecasts

A
  1. Jury of Executive Opinion
  2. Sales Force Composite
  3. Delphi Method
17
Q

FORECASTING APPROACHES:
Quantitative Forecasts

A
  • Time-Series Models
    1. Naïve Approach
    2. Moving Averages
    a. Simple Moving Average
    b. Weighted Moving Average
    3. Exponential Smoothing (First Order
    Smoothing)
    4. Exponential Smoothing with Trend
    Adjustment (Second Order or Double
    Smoothing)
    5. Trend Projections
  • Associative Models or Causal Models
  • Linear Regression Analysis
18
Q

intuition, emotions, personal
experiences, and value system in reaching a forecast.

A

Qualitative Forecast

19
Q

forecasting technique that takes the opinion of a small group of high-level managers

A

Jury of Executive Opinion

20
Q

forecasting technique based upon salesperson’s estimates of
expected sales.

A

Sales Force Composite

21
Q

forecasting technique using a group process that allows experts to make forecasts.

A

Delphi Method

22
Q

a group of 5 to 10 experts

A

Decision Makers

23
Q
  • It is a group of people, often located in different places, whose judgments are valued.
A

Respondents

24
Q

inputs from customers or potential customers
regarding future purchasing plans.

A

Consumer Market Survey

25
Q

It predicts on the assumptions that the future is a function of the past.

A

Time Series Models

26
Q

It has four components: Time Series Models

A
  1. Trend
  2. Seasonality
  3. Cycles
  4. Random Variations
27
Q

gradual upward or downward movement

A

Trend

28
Q

repeats itself after a period of days, weeks,
months or quarters.

A

Seasonality

29
Q

patterns in the data that occur every several years. * It is usually tied into the business cycle

A

Cycles

30
Q

These are “blips” in the data caused by chance and unusual situations.
* They follow no discernible pattern, so they cannot be predicted

A

Random Variations