Sales Forecasting

    Cards (35)

    • what is sales forecasting?
      the process of trying to predict or estimate future sales

      On the basis of this information a business can estimate and therefore plan:
      -The quantity of raw materials needed
      -Their future workforce size
      -Their financial needs
      -Production levels and costs.
    • sales forecasting; reliability
      There are so many variables that influence the actual outcome of the future that it is often very difficult to predict anything with any degree of confidence.

      Firms often use the past as an indication of what they expect to happen in the future. This is known as extrapolation.

      Forecasts are also heavily reliant upon market research data and therefore the more accurate this is, the more reliable the prediction of the future.
    • influences on sales forecasts
      -economic environment

      -actions of competitors

      -reliability of market research

      -stability of the market
    • quantitative sales forecasting

      Quantitative sales forecasting methods make use of numerical data to forecast future sales values for a business.

      They are heavily reliant upon the data and therefore the accuracy of this data is critical for the success of a forecast.
    • quantitative forecasting techniques
      -3 point moving averages

      -trends and extrapolation

      -time series analysis

      -correlation analysis

      -use of market research data
    • moving averages
      "Smooths" out the raw data, evens out fluctuations.

      The process of removing fluctuations is known as 'smoothing'.

      Smoothing mathematically removes any seasonal variations from a data series.

      Allows the underlying trend to be seen more clearly.
    • time series analysis
      Time-series analysis uses evidence from past sales records to predict future sales patterns.
    • methods of time series analysis- seasonal analysis
      sales are measured on a monthly or weekly basis to examine the seasonality of demand.

      For example, the sales of ice cream will be higher in the warmer seasons and lower in the colder seasons or according to daily weather changes.
    • methods of time series analysis- trend analysis
      this focuses on long-term data, which has been collected over a number of years.

      The objective is to determine the general tendency of sales - rising, falling or stagnant.
    • methods of time series analysis- cyclical analysis
      as with trend analysis, long-term figures are used but now the objective is to examine the relationship between demand levels and economic activity.

      For example, by asking the question 'what is the relationship between demand for the product or products and the stage in the economic or business cycle?'.
    • methods of time series analysis- random factor analysis
      this method of analysis attempts to explain how unusual or extreme sales figures occur.

      For example, if sales of ice cream double for a two-week period, then could this be explained by weather conditions, rather than an effective advertising campaign? Random factor analysis therefore attempts to provide explanations for unusual or abnormal sales activity.
    • correlation analysis
      Correlation analysis is a measurement of the strength of the relationship between two variables e.g. the sale of ice cream and the temperature outside.

      Businesses can use of this information to identify key influences on demand to try to maximise their sales and profits.
    • scatter graphs
      Scatter graphs are used to plot data in order to study the relationship between two variables.
    • types of correlation
      strong positive- as one variable increases so doe the other

      negative- we find that there is a downward sloping line of data showing that as one variable increases the other declines.

      no correlation- This means that changes in one factor will not hold any statistically significant impact on the
      demand of another. (there is no relationships between the variables)
    • line of best fit
      The line of best fit is drawn through the middle of all the data points on a scatter graph, so that the points are evenly distributed on each side of the line.
    • extrapolating the line of best fit
      Extrapolating the line of best fit forward enables a firm to predict future sales by simply extending the line.
    • extrapolating the trend
      Extrapolating involves making use of the trend line to predict the future sales.

      This is achieved through projecting the trend line forward.

      It is important that the previous pattern of the trend line is continued so that any forecast accurately follows what has happened in the past.
    • advantages of extrapolation
      -quick and cheap to use

      -requires limited volumes of data

      -easy to do
    • disadvantages of extrapolation
      -ignores qualitative factors

      -assumes past trends will continue

      -ignores external environmental changes

      -is the data reliable?
    • benefits of time series analysis
      Helps businesses to plan

      Assists with the management of HRM, finance and production needs.

      Allows a firm to identify any seasonal variations in their sales

      Reduces risk of unexpected events
    • drawbacks of time series analysis

      The future is uncertain

      Historical data does not provide an accurate reflection of the future.

      Forecasts are never 100% accurate

      The further into the future the forecast the greater the degree of risk
    • qualitative forecasting
      Qualitative forecasting methods are mainly used when there is a lack of historical data available for a business to conduct quantitative analysis techniques.

      Qualitative methods are largely based upon personal opinion and are therefore highly subjective which presents the opportunity for bias in the results.
    • methods of qualitative forecasting
      The Delphi method

      Brainstorming

      Intuition

      Expert Opinion
    • the delphi method
      This is a forecasting method that relies upon a panel of experts chosen by the business.

      The Delphi method is based on the principle that forecasts from a structured group of experts are more accurate

      The experts answer questions sent to them by the business in the form of a questionnaire.

      After each round, the facilitator provides an anonymous summary of the expert's forecasts and their reasons for reaching these forecasts.

      A new questionnaire is then issued and the experts are encouraged to revise their answers in light of the results.

      After several rounds of this approach, the aim is that the range of answers provided gets smaller as there is growing consensus about the 'correct' answer.
    • benefits of the delphi method

      The focus is on "ideas" rather than "individuals".

      Anonymity makes contributions of ideas a safe activity for participants.

      Opportunities for participants to reconsider their ideas.

      Can be applied to a range of complex problems.
    • drawbacks of the delphi method
      The process is time consuming and difficult to coordinate and manage.

      Monetary payments to experts might lead to bias.

      It assumes that a consensus can be reached.

      The more rounds the more difficult it is to maintain expert enthusiasm for the process.
    • brainstorming
      During a brainstorm the collective ideas of a group of people are considered to try and reach agreement about a problem.
      All ideas are welcome and none are initially dismissed or any judgements made.
      All members of the groups are encouraged to contributeand to be creative in their ideas.
      This method works best with groups of varied participants from different areas of a business who can all provide a fresh insight into how to best solve a particular issue or problem.
    • benefits of brainstorming
      Encourages creativity

      All ideas are heard

      All ideas are accepted and considered equally valid

      Lots of ideas are quickly generated.
    • drawbacks of brainstorming
      Not everyone may have something to say

      Dominant individuals might overwhelm the group dynamic

      Without clear leadership the group might lack focus.

      Groups might be too large
    • intuition
      This is when a manager or business leader uses their own 'gut feeling' as to how they predict the future will turn out.

      Ideally, the manager will hold previous experience of similar products or markets.

      Intuition is often attributed to entrepreneurs who sometimes use hunches to launch a product onto the market.

      This technique often requires luck in combination with experience and insight.
    • benefits of intuition
      Cheap

      Fast

      No need for data collection

      Can draw on personal experiences of managers or business owners.
    • drawbacks of intuition
      High risk

      Additional market research should be carried out.

      Other opinions should also be sought.
    • expert opinion
      Specialist consultants are asked for their opinions and insight.

      There is a huge variety of expert opinion available on individual markets.

      This is also the case for general business issues which may also be considered by businesses trying to forecast the future.
    • benefits of expert opinion

      Specialised insights into likely future patterns and trends

      Industry specific insights can be gathered
    • drawbacks of expert opinion
      The use of expert opinion does not provide any guarantee of success.

      Consultants will all have their own opinions which are influenced by their own individual experiences.

      Expert opinion should be used in combination with other forms of research to minimise exposure to risk.
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