Studied by 4 people
quantitative sales forecasting
statistical technique which uses historical smoothed out data to make predictions about the future
4 components that can skew data
random fluctuations, trends, seasonal fluctuations, cyclical fluctuations
ways to show trends
calculations of time series analysis, scatter graphs, extrapolation of past data- look for the trend and extend the line
moving averages
calculating the most recent 3 or 4 periods to create an average
sales figures collected at consistent time intervals
time series data
centring
find the average at 2 four quater moving averages and you place the result against the 3rd period (month / year) of the first moving average
time series analysis
only shows what is happening to data
casual modelling
tries to explain data by showing a link or relationship between sets of data. this can be shown through a scatter graph comparing two variables
extrapolation
trends in the past sales data can be continued in the future to forecast sales
SWOT factors
Strengths, Weaknesses, Opportunities, Threats
PESTLE C Factors
Political, Environmental, Social, Technology, Legal, Economical, Competition
Quantitative Sales Factors limitations
products with a short lifespan may find extrapolation misleading
Note 
Flashcard (68)