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Business Decision Making1

Wednesday, 14 September 2011

Lesson Outcomes

Identify the various types of data

Identify the sources of secondary data

Be aware of the advantages / disadvantages of types of survey

Be able to design questionnaires


What is Data?

Data is simply a scientific term for facts, figures, information and measurements

Data is raw. It simply exists and has no significance beyond its existence. It can exist in any form, usable or not.

Data can be qualitative or quantitative.


Discrete(whole units)

Continuous(all values)

Qualitative(attributes)

Quantitative(variables)

data


Data Sources

Data collected by an organisation may be: Internal (from the organisation itself)

eg. Sales, financial, employee, transport, stock etc

External (from outside the organisation). eg. Government, institutions, market

research companies, media etc.


In order to make decisions

Primary; Secondary; Tertiary

Data needs to be collected.


Primary Data

Information which is collected first hand, and especially for the purpose of whatever survey is being conducted.

For example, a pop poll interview on a street, commissioned by an organisation, intended to gain specific market share data.


Primary Data

Primary data is captured using a variety of processes, for example:

Surveys; Interviews; Focus groups; Questionnaires; Audits.


Secondary Data

Already available, and collected by someone other than the user.

Examples of secondary data sources: Journals; Books; Census data; Newspaper articles; Biographies


Attributes

A quality, property or feature belonging to or representing a person or thing.

Something an object has/has not got A specific value on a variable


Variables

Something which can be measured. e.g. height

Can be classified as discrete (a finite or countable number of values within a given range), or continuous (may take on any value, measured rather than counted)


Internal Data

Relate to activities or transactions performed within the organisation.

Examples: Administrative tasks such as correspondence or payroll calculation, the production of products and services, or the sales of those products.


Internal Data

Internal sources of data can be classified according to the department of the organisation to which it relates:

e.g. Purchasing, Production, Sales, Marketing etc.


Gathering internal data/information from inside the organisation involves: Establishing a system for collecting or

measuring data . As to what data is collected, how frequently, by whom and by what method

Relying to some extent on the informal communication lines between managers and staff eg, word of mouth, conservations at meetings, email etc.


External Data Organisations need to collect data relating to

the outside world or the environment of the organisation

Data relating to the environment of an organisation might be classified under:

Political Economic Social Technological Competitive


3 main types of Data Collection

Census Sample Survey Administrative by-product data


Census This refers to data collection about

everyone or everything in a group or population.

e.g. if you collected the age of everyone in your department, it would be regarded as a department census.

High degree of accuracy Costly and time consuming


Sample Survey In this type of data collection only part of the

total population is approached for data.

e.g. If you have collected the age of 10 people in a department of 50, it would be a sample survey of the department rather a census.

Surveys cost less than census and results are obtained at a greater speed.

Depending on sample size there can be inaccuracies, and information in small populations may not be obtainable


Administrative by-product data

Collected as a by-product of an organisations day to day operations.

e.g. Include data on births, deaths, marriages, divorces, airport arrivals and motor vehicle registrations.

Advantage high degree of accuracy as data is collected on everyone associated with the service

Data is on-going so trends can be observed Lack of flexibility


Methods of obtaining sample data

Observation Experimentation Questionnaires Qualitative techniques Consumer panels Trade audits or retail audits


Primary & Secondary Research

To generate the data/information requirements you need to define and report the following:

Scope: means the boundaries of what you are doing

Focus: means what you are collecting data about

Contexts: means the factors in the immediate environment of the problem area.


Quantitative Research Quantitative research is used to measure how

many people feel, think or act in a particular way.

These surveys tend to include large samples - anything from 50 to any number of interviews.

Structured questionnaires are usually used incorporating mainly closed questions - questions with set responses.

There are various vehicles used for collecting quantitative information but the most common are on-street or telephone interviews.


Qualitative Research Qualitative research seeks out the

why, not the how of its topic through the analysis of unstructured information

things like interview transcripts and recordings, emails, notes, feedback forms, photos and videos.

It doesnt just rely on statistics or numbers, which are the domain of quantitative researchers.


Qualitative Research Qualitative research is used to gain

insight into people's attitudes, behaviours, value systems, concerns, motivations, aspirations, culture or lifestyles.

It is used to inform business decisions, policy formation, communication and research.

Focus groups, in-depth interviews, content analysis and semiotics are among the many formal approaches.


Qualitative Research Collecting and analysing this

unstructured information can be messy and time consuming using manual methods.

When faced with transcripts, emails, pictures, diaries and audio or video material - finding themes and extracting meaning can be a daunting task.


Data Manipulation

After editing, data may be manipulated by computer to produce the desired output.

Some typical ways that software can manipulate data:

Spreadsheets Databases Charts


Spreadsheets

These are used to create formulas that automatically add columns or rows of figures, calculate means and perform statistical analyses.

They can be used to create financial worksheets such as budgets or expenditure forecasts, balance accounts and analyse costs.


Databases

These are electronic filing cabinets. They are used to systematically store

data for easy access to produce summaries, stock takes or reports.

A database program should be able to able to store, retrieve, sort and analyse data.


Charts

These can be created from a table of numbers and displayed in a number of ways, to show the significance of a selection of data.

Bar, line, pie and other types of charts can be generated and manipulated to advantage.


Sampling

Sampling involves selecting a sample of items from a population.

It is subject to quantitative methods. In most practical situations the

population will be too large to carry out a complete survey and only a sample will be examined.


Methods of Sampling

Random sampling Quasi-random sampling Non-random sampling


Random Sampling A random sample is a sample selected in such

a way that every item in the population has an equal chance of being included.

Example: if you wanted to take a random sample of library books, it would not be good enough to pick them off the shelves, even if you picked at random.

This is because the books which were out on loan would not stand a chance of being chosen. The library catalogue can be used for this purpose.


Quasi-random sampling This sampling provides a good

approximation to random sampling, necessitates the existence of a sample frame.

The main methods of quasi-random sampling are:

Systematic sampling Stratified sampling Multistage sampling


Non-random sampling There are two main methods of non-

random sampling, used when a sampling frame cannot be established.

Quota sampling Cluster sampling


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