E2, Ch 18: Forecasting, Demand Planning Flashcards

1
Q

customer demand →

A

forecasting → planning → scheduling

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2
Q

forecasts are based on __________ data if we have it; if not, ___________ methods are used.

A

historical
qualitative

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3
Q

DAWGS Steps (5)

A
  1. data collection
  2. analyze
  3. work w/ stakeholders
  4. generate and gauge
  5. start again
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4
Q

step 1: data collection
the key is…

A

key is QUALITY of data; how trustworthy is the data in MRP system?
source of data = within company as well as suppliers, clients, etc.
finally, validation of data critical

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5
Q

step 2: analyze

A

conduct analysis, develop forecast

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6
Q

step 3: work w/ stakeholders

A

moving across organization at this point to meet with marketing/other stakeholders for additional insight

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7
Q

step 4: generate and gauge

A

putting info in a software system and modifying as we deem necessary; then, moving forward to schedule production

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8
Q

forecasting

A

mathematical model used to examine past experiences to gain insights into future

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9
Q

forecasting as a basis of business decisions, we look at… (4)

A

production
personnel
finance
marketing

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10
Q

forecasting as a basis of business decisions, we look at: production

A

scheduling inventory, aggregate planning

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11
Q

forecasting as a basis of business decisions, we look at: personnel

A

workforce planning, hiring, layoffs

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12
Q

forecasting as a basis of business decisions, we look at: finance

A

PPE investment, budgeting

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13
Q

forecasting as a basis of business decisions, we look at: marketing

A

sales force allocation, promotions, new product introduction

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14
Q

stages of forecast development (5)

A
  1. determine objectives
  2. developing and testing a model
  3. applying models
  4. real-world constraints
  5. revising and evaluating forecast
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15
Q

forecast development stage 1: determine objectives

A

what is the purpose of the forecast? what variables should be considered?

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16
Q

forecast development stage 2: developing and testing a model

A

considering qualitative vs quantitative models

17
Q

forecast development stage 3: applying model

after model is tested….

A

after model is tested, historical data collected and applied

18
Q

forecast development stage 4: real-world constraints

A

what real-world variables should be considered

19
Q

forecast development stage 5: revising, evaluating forecast

A

technical forecast should be tempered w/ human judgement

20
Q

qualitative methods

A

new products/technology; intuition, experience

21
Q

quantitative methods

A

used when situation is ‘stable’ and historical data exists; usually 3-6 mo. of sales; mathematical techniques

22
Q

forecasting

A

diff b/w forecast and actual sales units

23
Q

sources of error (2)

A

bias: consistent mistake is made
random: errors not explained by model being used

24
Q

measures of error (3)

A

mean absolute deviation
mean absolute percent error
tracking signal

25
Q

qualitative methods: buildup methods

A

smaller segments of demand are estimated first, and then aggregated to get the total forecast

ex. a baker adding up day-by-day estimates to get total demand for next week

26
Q

qualitative methods: bottom up***

A

start at bottom of org working way to top. ex. car and home sales

27
Q

qualitative methods: survey method

A

using questionnaires, phone interviews, or internet to solicit interview

28
Q

qualitative methods: test markets

A

conducting trial run w/ product in a market region

29
Q

qualitative methods: panel of experts

A

Delphi Technique; soliciting info from experts on subject
challenge: very subjective

30
Q

when it comes to things like housing a cars, there are variables that drastically impact………………

A

quantitative data (usually govt-related, like interest rates). Therefore, we use qualitative methods rather than solely relying on quantitative.

31
Q

quantitative methods: simple moving average

A

add up sum of X time and divide by whole

32
Q

quantitative methods: weighted moving average

A

average but while assigning diff weights to each period, usually driven by season trend/index