3.3.1 Quantitative sales forecasting

Question 1

Correlation:

Answer 1

-a statistical technique used to establish strength of relationship between 2 variables

• stronger = closer line of best fit (regression line)
• scatter diagram

Question 2

dependant variable

Answer 2

y-axis

-being influenced

Question 3

independant varibale

Answer 3

x-axis

-one causing other to change

Question 4

Line of best fit/regression line

Answer 4

• forecast sales & identify factors influencing demand

- strong correlation = relationship used to make marketing predictions/decisions

Question 5

positive correlation

Answer 5

• direct relationship
• close to 1
• as one increases so does other

e.g. sales & advertising or income & sales

Question 6

negative correlation

Answer 6

• inverse relationship
• close to -1
• as one variable increases other decreases

e.g. price and demand or as interest rate rises there is a fall in demand for new house

Question 7

4 Pros of using correlation to forecast sales:

Answer 7

1-predict sales & demand factor
2-link = influenced for benefit of business
3-simple & useful tactical thinking
4-regularly = chance correlation exists

Question 8

3 Cons of using correlation to forecast sales:

Answer 8

1-uncertainty
2-past wont repeat
3-cause & effect or causal link (other factors?) coincidental ?

Question 9

Extrapolation

Answer 9

• extending line of best fit (dotted line)
• predict future levels such as sales
• analysing trends in past data

Question 10

3 Affects to extrapolation

Answer 10

1-new competitor
2-increase price
3-external factors

Question 11

3 Pros of extrapolation to forecast sales:

Answer 11

1-quick and easy to implement & simple & cheap
2-accurate = based on past sales trends (static)
3-quantitative target to predict future sales

Question 12

5 Cons of extrapolation to forecast sales:

Answer 12

1-doesn’t account external factors/qualitative (trends)
2-assumes past repeats -not likely (comp bus env)
3-some markets (dynamic) (fast move consumer goods)
4-not statistically valid (unreliable significant fluctuations)
5-ignoring significant outliers

Question 13

Moving averages

Answer 13

• time series analysis
• statistical calculation of an underlying trend in data

3 period: (add 3 together divide by 3)

Question 14

5 reasons why a moving average is useful:

Answer 14

1-dealing with erratic/personal data
2-average of multiple time periods
3-minimise effect extreme value - take average
4-emphasise direction of a trend
5-reduce ‘noise’ = confuse interpretation

Question 15

Analysing markets

Answer 15

-several periods at time & averages out the data

• iron out all peaks/troughs in demand
• more accurate figure = whether sales have risen/fallen in market over time

Question 16

variation

Answer 16

sales in a specific time period - moving average sales

Question 17

4 ways a sales forecast useful

4 things it creates?

Answer 17

1. cash flow forecast = predict receipts and repayments
2. revenue budgets = predict budgeted revenue and cost data
3. ops plan = used for production/operations plan = predict scale of production = stock requirements and likely C.U
4. HR plan = predict staffing levels required

Question 18

3 key factors affecting sales forecasts:

Answer 18

1. consumer trends
   - demand changes tastes/fashion
   - MS existing competitors
2. economic variable
   - sensitive change in variable (ER, IR, tax)
   - strength of economy GDP growth = important
3. competitor actions
   - cant predict
   - significant reason sale forecast = over-optimistic

Question 19

6 situations where sales forecasts are likely to be inaccurate

Answer 19

1-new business (start-up = difficult to forecast)
2-mkt subjective - disruption from tech change
3-demand = sensitive-change price/income
4-product is fashion item
5-significant changes in mkt share (new entrants)
6-management= poor sale forecast ability in past

Question 20

3 things that makes quantitative techniques more effective in forecasting sales

Answer 20

1. business mature (lots past data = see trends)
2. industry mature (rapid change = less likely)
3. stable external environment (econ, tech ,comp, and legislation less likely to change)