# Copyright 2006 – Biz/ed Business Analysis.

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http://www.bized.co.uk Copyright 2006 – Biz/ed Business Analysis

http://www.bized.co.uk Copyright 2006 – Biz/ed Business Analysis

http://www.bized.co.uk Copyright 2006 – Biz/ed 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

http://www.bized.co.uk Copyright 2006 – Biz/ed 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

http://www.bized.co.uk Copyright 2006 – Biz/ed Data

http://www.bized.co.uk Copyright 2006 – Biz/ed 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

http://www.bized.co.uk Copyright 2006 – Biz/ed Trends Looking for patterns in data collections Frequency and reliability of trends Impact of external factors, e.g. seasonal variation, random events, cyclical trends

http://www.bized.co.uk Copyright 2006 – Biz/ed 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

http://www.bized.co.uk Copyright 2006 – Biz/ed 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

http://www.bized.co.uk Copyright 2006 – Biz/ed 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

http://www.bized.co.uk Copyright 2006 – Biz/ed The Standard Deviation S = Σ (x i – x ) 2 n

http://www.bized.co.uk Copyright 2006 – Biz/ed 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

http://www.bized.co.uk Copyright 2006 – Biz/ed 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

http://www.bized.co.uk Copyright 2006 – Biz/ed 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

http://www.bized.co.uk Copyright 2006 – Biz/ed Forecasting

http://www.bized.co.uk Copyright 2006 – Biz/ed 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

http://www.bized.co.uk Copyright 2006 – Biz/ed 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

http://www.bized.co.uk Copyright 2006 – Biz/ed 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

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