BUSINESS ANALYSIS AND FINANCIAL POLICY

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BUSINESS ANALYSIS AND FINANCIAL POLICY

• UPSA LEVEL 300
• Mr. Charles Barnor, Mr. Danaa Nantogmah and Mr.
  K. Fosu-Boateng

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Week 1Introduction to Business Analysis and
Financial Policy

• INTRODUCTION Week 1
• BUSINESS STRATEGY ANALYSIS Week 23
• INVESTIGATION TECHNIQUES Week 4-5
• CONSIDER PERSPECTIVES Week 6
• ANALYSE NEEDS Week 7
•  CASE STUDY PRESENTATIONS Week 8
•  INTERIM ASSESSMENTS Week 9
•  EVALUATE OPTIONS Week 10
• CORPORATE FINANCIAL POLICY DECISIONS Week 11
•  DEFINE REQUIREMENTS Week 12
• REVISION Week 13

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Topic 1Introduction to Business Analysis and
Financial Policy

• The rationale for business analysis
• The development of business analysis
• The scope of business analysis
• The responsibilities of a business analyst
• The Business Analysis Maturity Model
• The competencies of a business analyst

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Introduction

• Business analysis is the set of task and
  techniques use to work as a liaison among
  stakeholders in order to understand the
  structure, policies and operations of an
  organization, and recommend solutions that will
  enable an organization to achieve its goals
  (International institute of business analysis,
  2008).
• The development of business analysis as a
  professional discipline has extended the role and
  responsibilities of the business analyst (BA).
  Business analysts investigate ideas and problems,
  formulate options for a way forward and produce
  business cases setting out their conclusions and
  recommendations.

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The development of business analysis

• Business analysts have responsibility for the
  following areas
• Identifying the tactical options that will
  address a given situation and will support the
  delivery of the business strategy
• Defining the tactics that will enable the
  organization to achieve its strategy
• Supporting the implementation and operation of
  those tactics
• Redefining the tactics after implementation to
  take account of business changes and to ensure
  continuing alignment with business objectives

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There is a chain of reasoning that leads from the
statement of a problem to the implementation of
solutions
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Chain Of Reasoning
Stakeholders

• Change Requirements must be assumed to be wrong
  until they are proved to be right

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Fundamental Components of Business Analysis
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All the Links in the Chain Of Reasoning
Description
Driver
The problems / opportunities that the business
face
Addressed as measured by
The measures and targets that will enable us to
declare the change project has been successful
business Objective
Delivered by
Definitions of what changes are required that
will affect the measures of success (objectives)
sufficiently for the business to be declared
successful
Change Requirement
Enforces
What rules must be implemented by the changes
specified in the requirements
Business Rule
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Business Analysis
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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

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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

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Data
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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

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Trends

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

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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

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Averages

• Mean Sum of items in the series/number of
  items
• X Sx
• x
• Median middle number in a data series 0.5
  (n1)
• Mode the most frequently occurring value in a
  data series

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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

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The Standard Deviation
S (xi x )2
S
n
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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

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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

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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

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Forecasting
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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

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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

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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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• Q A
• THANK YOU