Business Analysis & Forecasting

1. Business Analysis & Forecasting

2. Business Analysis

3. Business Analysis • Purpose: • Identify where the business stands in relation to rivals, etc. • Collect and use data to inform business decision making • Identify strengths and weaknesses in the business • Use information to inform strategic planning

4. Business Analysis • Method: • Collection of data from a range of sources: • Market research • Past sales data • Market growth data • Specialist analyst data • Secondary data, e.g. Mintel

5. Data

6. Analysis • Range of methods used to analyse data: • Trends • Growth rates • Nominal • Average • Mean • Median • Mode • Variance • Standard deviation • Range • Time series analysis • Scatter graphs • Correlation

7. Trends • Looking for patterns in data collections • Frequency and reliability of trends • Impact of external factors, e.g. seasonal variation, random events, cyclical trends

8. Averages • Averages are a measure of central tendency – the most likely or common item in a data series • Calculated through 3 measures: • Mean • Median • Mode

9. Averages • Mean = Sum of items in the series/number of items X = Σx x • Median = middle number in a data series – 0.5 (n+1) • Mode = the most frequently occurring value in a data series

10. Variance • Averages have limitations – measures of data spread used to assess width • Range – difference between the highest and the lowest value • Standard Deviation – used to measure the variance of the data set from the mean – can highlight how reliable the mean is as being representative of the data set

11. The Standard Deviation Σ (xi – x )2 S = n

12. Correlation • The degree to which there is a relationship between two or more random variables • The closer the relationship the higher the degree of correlation • Perfect correlation would be where r = 1

13. Time-Series Analysis • Used to analyse movements of a variable over a time period – usually years, quarters, months, etc. • Importance of assessing the: • Trend • Seasonality • Key moments • Magnitude

14. Presentation • Graphs • Charts • Tables • Index numbers – Method of showing average changes in large amounts of data • Laspeyres – Uses a base period weighting measurement • Paasche – Uses a current price weighting measurement

15. Forecasting

16. Qualitative • Focus groups - a group of individuals selected and assembled by researchers to discuss and comment on, from personal experience, a topic, issue or product • User groups – similar to focus groups but consisting of those who have experience in the use of a product, system, service, etc. • Panel surveys – repeated measurements from the same sample of people over a period of time • Delphi method – calls on the expertise and insights of a panel of experts to help with forecasting – seen as being more reliable than data analysis only • Could be drawn together from around the world as there is no need to have people together at the same time • In-house judgements – Use the expertise and judgements of those involved in the business in aiding and making judgements

17. Quantitative • Makes use of all the statistical data collected by the firm and by other firms/organisations to help inform decision making • Surveys • Sales data • Impact on sales • Primary data – collected by the firm themselves • Data collected by others and used by the firm, e.g. Office of National Statistics (ONS), Gallup, Mori, Mintel

18. Forecasting • Advantages and disadvantages: • Data from several years can give accurate guides to future performance • Statistical techniques can make the data informative and useful • All depends on the quality of the data and the accuracy of the techniques used to analyse the data