Many businesses, economic and social questions are not amenable to a simple YES or No answer. Every business needs some clarification or discussion. Solutions can be presented and every criterion can be either accepted or rejected. To consider the arguments and indeed the facts presented, the completeness of current information and the requirements for new information need to be assessed.
Decision maker not only need the DATA but also need to evaluate the quality of the data. One Dictionary definition of data is ‘things known and from which inferences may be deduced’.
Data refers to information or facts usually collected as the result of experience, observation or experiment, or processes within a computer system, or premises. Data may consist of numbers, words, or images, particularly as measurements or observations of a set of variables. Data are often viewed as a lowest level of abstraction from which information and knowledge are derived.
Data in business means numerical values such as size of a business, its profitability, its product range, the features of the workforce and host of other factor. However numbers alone cannot give clear understanding of the business problems therefore it is important to consider the entire factor that affects the business during its existence such as legal, economic, culture and etc.
In general business, require a multi disciplinary approach.
The completeness of data is always a problem for the decision maker. Collection of data is always vast, but it depends on the decision maker to decide whether the current data is enough or more additional has to be collected.
Collection data is a tedious job and costly also. The main issue for the decision maker is that whether the data has some quality information or no. Data that has bias or is misleading can damage any effective decision making process which can further affect the profit in future.
Data can be collected by different sources and most people underestimate the number of sources and the amount of data within each of these data:
- Paper based sourced: It is books, journals, periodicals, abstract, indexes, directories, research reports, conference papers, markets reports, annual reports, internal record, magazines, newspaper.
- Electronic based sources: CD-ROMs, online database, Internet, videos and broadcast.
Pre-collection activity is the most crucial steps in the collection of data. There is always a formal need of checking the data collected so as to ensures that the data collected defined and accurate and the finding in the collection of data are valid and not bias.
In this Globalization century it is important to be abreast with the updated information and data so as to have a competitive edge.
1. Company Overview:
My research is based on Dominos:
Starting in business with his brother James in 1960, Tom Monaghan brought a pizza store named DomiNicks in Ypsilanti, Michigan. A year later, James traded his interest in the store for a Volkswagen. Tom formed another partnership and, during the next three years, continued to open stores in Mt Pleasant, Ann Arbor and Ypsilanti. In 1965 that partnership was dissolved, leaving Tom with one store in Ann Arbor and two in Ypsilanti.
When Tom was searching for the name for his new corporation, a driver suggested the name ‘Dominos’. The name was adopted and Tom helped create the now familiar red and white three-dot logo.
Through hard work and dedicated team, Dominos grew into international leader in the pizza delivery industry, with over 8,000 stores in 50+ markets.
December 1998, saw a change in ownership for Dominos pizza when Bain Capital, a Boston based private equity investment firm, purchased Domino’s from Mr. Monaghan.
The new leadership has brought an even stronger focus to operational quality and growth, as well as renewed commitment to recruiting and developing exceptional people.
To forward the goals, David A Brandon was named Chairman and Chief Executive Officer of Domino’s Pizza, LLC in March, 1999.
1. Sources of Data Collection:
Nowadays data collection is become very important in this Economic world .When there are many business ,economic, and social question they are not amendable by a simple yes or no, So here to consider the argument and indeed the ‘facts’ presented, the completeness of current information and the requirement for new information need to be assessed. According to Jon Curwin and Roger Slater, Third edition 1991, stated that one dictionary definition of data is ‘things known and from which inferences may be induced’
Appraisal and market studies use two types of data- Primary data and Secondary Data. All the data collected should be current, relevant, accurate and conceptually correct. Primary data and Secondary data are defined in The Dictionary of Real Estate Appraisal as follow:
Information that a researcher gathers first hand is primary data.
Information from secondary sources i.e. not directly complied by the analyst may include published and unpublished work based on research that relies on primary sources of any material other than primary sources used to be prepare a written work.
Decision makers not only data but also the quality of the data because Data that are bias or misleading can damage any effective decision-making process. Whenever we look at data or consider data collection we need to ask ‘what is the problem?’ or ‘what is the question?’Basically there are two types of sources of data 1) Primary Data and 2) Secondary Data.
A) PRIMARY DATA:
Primary data is facts and information collected specifically for the purpose of the investigation at hand. Primary data is collected specifically to address the problem in question and is conducted by the decision maker, marketing firm, a university and etc. Primary data cannot found elsewhere. Primary data may be collected through surveys, focus groups or in depth interviews, or through experiments such as taste tests.
According to Jon Curwin and Roger Slater, Third edition 1991, stated that a statistical enquiry may require the collection of new data, referred to as primary data, or be able to use existing data, Primary data is its collection for a specific project.
- Basic data are included in primary data collection.
- It is unbiased information
- It is the information that is collected originally.
- Data collected is large in volume
- It is time consuming
- Direct and personal intervention has to be there to collect the data
- The data collected is raw.
A distribution census, taken every five years, dealing with retail data
Ø Population census which has been carried out in the U.K in every 10years since 1801 ,this exercise gives highly detailed information and reflect data from all part of the population
Metro Newspaper, Thursday, May 14, 2009.
BANKS are slowing down Britain’s economic recovery by not lending, it was claimed yesterday. The Banks- some of which have been propped up with billions from the taxpayer- are displaying an ‘extreme level of risk aversion’ when lending to businesses and households, Banks of England governor Mervyn King said. The warning came as the Bank predicted the economy would shrink by 4.5 per cent at the peak of the recession in the summer. Consumer price inflation currently at 2.9 per cent target this year. However, a weak pound, the impact of 0.5 per cent interest rates and government spending offered hope of recovery, Mr King added in his quarterly inflation report.
B) TYPES OF METHODS OF COLLECTING PRIMARY DATA:
- Focus Group Interviews
Questionnaire are a popular means of collecting data, but are difficult to design and often require many rewrites before an acceptable questionnaire produced. Questionnaire is the series of question to be asked to an individual so as to obtain statistically useful information about any given task. It became a vital instrument if it is constructed and responsibly administered. It is frequently used in quantitative marketing research and social research. They are valuable method of collecting a wide range of information from large number of individuals, often they are referred to as respondents. Good questionnaire construction is important for the success of a survey. Inappropriate question, incorrect order of question, incorrect scaling, and bad format can make the questionnaire worthless. In order to have a successful questionnaire it is important to have the subset of target respondent to be tested first.
- It can be used as a method in its own right or as a basis for interviewing or a telephone survey.
- It can be posted, emailed or faxed.
- It can be used for large volume of people or organization
- It has wide geographic coverage.
- It is relatively cheaper
- No prior arrangements are needed.
- It avoids embarrassment on the part of the respondent.
- Respondent can consider responses.
- There is a possibility of respondent being anonymous
- There is no Interviews bias.
- Designing the questionnaire is a problem
- Questions have to be relatively simple.
- It has low response rate.
- It is time consuming whilst waiting for the response to be returned.
- It requires return deadline.
- Several remainders are required while conducting the questionnaire.
- It assumes no literacy problems.
- There is no control over who completes the questionnaire.
- It is not possible to give assistant if required.
- There is a problem with incomplete questionnaire.
- The replies are not spontaneous and independent of each other.
- Respondent can read all questions beforehand and then decide whether to complete or not may be because it is too long complex, uninteresting, or too personal
1.1 SUCCESSFUL QUESTIONNAIRE DESIGN:
To be successful, a questionnaire needs both a logical structure and well thought out questions. The structure of the questionnaire should have a flow from question to question and from topic to topic, just like the conversation between two people. Any radical jump between questions or topic would create a problem or confusion to the respondent. It is often suggested that a successful and useful technique is to move from general to specific questions on any particular issue.
The Gallup organization has suggested that there are five possible objectives for a question:
- To find if the respondent is aware of the issue
- To get general feelings on an issue
- To get answer on specific parts of the issue
- To get reasons for a respondent’s views
- To find how strongly these views are held
1.2 DESIGN OF POSTAL QUESTIONNAIRE:
Theme and covering letter:
The general theme of the questionnaire should be explicit in a covering letter. You should state who you are, why the data is required, give if necessary, an assurance of confidentially and/or anonymity and contact number and address or telephone number. This ensures that what respondent is known what they are committing. If possible, you should offer estimate time for completion. Instruction for return should be included with the return date made obvious.
Instruction for completion:
You need to provide clear and unambiguous instruction for completion. There should be a general instruction for particular question structure. The response method should be indicated (circle, tick, cross and etc). Even example can be given to make question clearer.
Appearance is the first thing which the recipient reacts. A neat and professional look will encourage further consideration of request, increasing your response. To improve the questionnaire appearance:
- Liberal spacing makes the reading easier.
- Photo reduction can produce more space without reducing content.
- Consistent positioning of response boxes, usually to the right speeds up completion.
- Choose the font style to maximize legibility
- Differentiate between instruction and question.
The length of the questionnaire should not be that long because this could affect the completion of it and respondent may be uninterested to complete.
The most important and crucial stage in questionnaire is the beginning. Once the respondents have started to complete the question they will normally finish provided if it not too long or difficult.
It is advisable non numerical responses when designing the questionnaire rather than trying to code the responses when they are returned.
Respondents to questionnaire rarely benefits personally from their efforts and the least the researcher can do is to thank them. Even though the covering letter will express appreciation for the help given, but it is always advisable to thank the respondent at the end of the questionnaire.
Question asked should be short, simple and to the point avoid any unnecessary words. It shouldn’t confuse the respondent as it could affect the completion of questionnaire.
Types of Questions:
- Contingency question: A question that is answered only if the respondent gives a particular response to a previous question. This avoids asking questions of people that do not apply to them.
- Matrix question: Identical response categories to multiple questions. The question are placed one under the other, forming a matrix with response categories along the top and a list of question down the side. This is efficient use of page space and respondents’ time.
- Close ended question: Respondents’ answers are very limited to a fixed set of responses. Other types of closed ended question include:
Yes or No question: The respondent answer with a ‘yes’ or a ‘no’.
Multiple choices: The respondents are given with several options from which to choose.
Scaled question: Responses are graded on a scale for e.g. rate the food quality scale from 1 to 10, with 1 being the least preferred and with 10 being most preferred.
- Open ended question: No option or predefined categories are suggested. The respondent gives their own answer without being constrained by fixed set of possible responses.
Interviewing is a technique that is primarily used to gain an understanding of the underlying reasons and motivation for people attitudes, preferences or behavior. Interviews can be undertaken one to one basis or in group. There different types of interview that can be conducted such as personal interview and telephone interview. Interviews can be structured, semi structured and unstructured.
A personal interview has a serious approach by respondent resulting in accurate information. It has good response rate with completed and immediate. Interviewer can also give help to the interviewee if in case it requires some help.
There is need to the setup interviews. It is time consuming and expensive. Interviewer can even ask some personal question which could be embarrassing for the respondent.
Telephone interview is an alternative form of interview to the personal, face to face interview. It is relatively cheaper, quick and has wider coverage. It has high rate of spontaneous response.
Telephone interview is often connected with selling. It often requires questionnaire. Time is wasted if lines get disconnected and if call backs are given it could make the respondent irritate. A strong telephone manner is needed to handle the question raised by the respondent.
3) Focus Group interview:
A focus group is an interview conducted by a trained moderator with a small group of respondent. The moderator starts the discussion and then leads the same. The main purpose of the focus groups is to get the insight or complete knowledge by listening to a group of people from the targeted market about the specific issues of interest.
All methods of data collection can supply quantitative data or qualitative data. When using secondary research, one must be caution when using dated information from the past. Secondary data is facts and information gathered not for the immediate study at hand but for the purpose. Secondary data is data which has been collected by individuals or agencies for purposes other those of our particular research study. Common sources of secondary data for social science include censuses, large surveys and organizational records. Secondary data is a data which is collected from primary data to create new research. A secondary data source is a summary of a book or set of records. Secondary data, Sources of primary data include observation, group discussions and the use of questionnaires.
- It is easily accessible and saves time that would otherwise be required for collecting data.
- The cost to access secondary data is little or no cost to acquire.
- Secondary data helps to clarify the research focus or question.
- Quality of research is questionable because the secondary data is originated from primary data research which is collected and controlled by the marketer itself.
- In many cases, secondary data is not well presented in a form that exactly meets the researcher’s needs.
- In secondary research, much information is incomplete because the researcher may not get the full version of the research to gain the full value of the study. This is because many researcher suppliers offers free portions of their research and then charge expensive fees for their full reports.
- Data collected by the hotels or the organization through its history system.
- Data supplied by a marketing organization
- Annual company reports
- Government statistics
Secondary Data Analysis:
Secondary data analysis is commonly known as second hand analysis. It is simply analysis of pre-existed data in a different way to answer a different question than originally needed. It analysis the data that was collected by someone else and uses it in for further study that is intended to complete.
Secondary data can be gathered by internal and external source of data collection. Where internal sources includes sales data, reports data, financial data,
Transport data, storage data and external sources includes government statistics, trade association, and commercial services
There are common sources of collecting secondary data such as from Bureau of the census, the Bureau of Labor Statistics and various other agencies.
U.S Bureau of the census has kept track of the census of the population for over two hundred years. Moreover, the census includes housing, the labor force, manufacturers, business, agriculture and so on. Census data can be used for various research questions. Anyone has access to the large amount of information nearly one hundred surveys, by visiting their website at (http://www.census.gov).
Bureau of Labor Statistics collects information or data on employment, industrial relations, prices, earning, living condition, technology and productivity. Report is out every month in this bureau and they can be viewed at (http://stats.bls.gov )
International Data Sources is a strong source for comparative researchers and can deal with economic aspects, including political events across many other nations. In Europe, a Euro barometer Survey Series is used to publish reports on social and political events in the country.
The Design and purpose of research:
Secondary data analysis means collecting the data which is collected by some other person and using the same data for understanding the current issue or problem face by the researcher. It is important to have a well defined research type which in turn would help the research to be successful. In order to use the secondary data three steps must be completed:
- Locate the data
- Evaluate the data
- Verify the data
Collecting data is easy online but to verify the data whether they care up-to-date or current is important. Therefore it is important to be alert and cautious while using the online sources while collecting the data
Ethnicity, discrimination and health outcomes: a secondary analysis of hospital data from Victoria, Australia
In this study, secondary data was used in the form of hospital discharge abstract for the state of Victoria in Australia. The variables that were looked at were a person’s country of birth and the quality of care they received in a universal health care system. It was secondary data because it had already been collected by the hospital in the way of their charts and discharge abstracts. The researchers were simply looking at the data and the relationship between the listed country of birth and what type of care was listed. The goal of the research was to explore the relationship between a person ethnic background and the amount of care they received from the hospital. The researchers were interested in developing a preliminary set of data that would allow them to develop methods to study the issue further.
The discharge abstract contained demographic and clinical information about each patient. From the abstract the researcher separated the patient into three groups. The first being Australian or English patients. The second group consisted of patients who did not visibly appear to be minority e.g. people from Europe, South and Central American. The third group contained people that were visible minorities e.g. Middle Easterners, Asians, Africans and Pacific Islanders.
Dominos strives to excel in customer’s satisfaction. Its major competitors are Perfect Pizza with over 200 outlets, Pizza Hut with over 170 restaurants and also small pizza delivery business; it is believed that there are as many as 4,000 pizza delivery companies in UK.
It is important to have updated knowledge about the market so as to survive the recession. Dominos store in UK conducted the questionnaire to have clear idea about the market needs and customer expectation.
315 Chiswick High Road, London W4 4HH
Telephone: 020 8995 4555
|Q1) Do you use fast food service in the area?
Q2) Which fast food services do you use (if any)?
Q3) What type of fast food do you prefer?
Q4) What else do you buy when purchasing fast food?
Q5) What time do you use fast food service?
Q6) How often do you use fast food services?
Q7) How much are you prepared to pay for the fast food?
|Thank you for your help!|
TECHNIQUES TO ANALYSE DATA:
Data which is collected needs to be analyzed and then interpreted or technique to presented in the form that is self explanatory and easily understandable. Therefore, it is important to know the process that is included in process of analyzing the data.
Data analysis is the process of gathering, modeling, and transforming data with the goal of highlighting useful information, suggesting conclusion and supporting decision making. Data analysis has multiple ways, approaches and technique.
The main task is to interpret the information or the data that is collected. There are various ways to interpret the data in a simple for easy understanding. Interpretation of data is important for making a decision for the business. There are different ways or methods how a data can be interpreted, that is:
Mean, Median and Mode
Quartile, percentile and Standard deviation.
The easiest way to present the data is through graphs and diagrams. There are different graphical presentations that are used for interpreting the data or presenting the data. To show the relationship between two variables we use graphs and diagrams.
Using graph can have quick and direct understanding. It highlights the most important facts. It gives easy understanding of the data and can have a long lasting impression.
Graph can be used when the data is dispersed, few or numerous and has little or no variation.
Below is the detail for the local garage which is facing the fierce competition and wants to compete in the market with the reasonable prices.
Histogram is the popular graphing tool. It is used to explain discrete or continuous data that are measured on an interval scale. It is often used to present the distribution of data that is collected for the purpose. It divides the range of values in the data set into group classes. Histogram is more similar to vertical bar graph but when the data are continuous, there are no gaps between the bars. When the variables are discrete, gaps should be left the between the bars.
In histogram, frequency is measured by the area of the column and in a vertical bar graph; frequency is measured by the height of the bar.
Histogram graphically shows:
- Center (i.e. the location) of the data
- Spread (i.e. the scale) of the data
- skewness of the data
- presence of outliers and
- Presence of multiple modes in the data.
The most common form of the histogram is taken by dividing the range of data into equal classes. That is,
Vertical axis: frequency
Horizontal axis: Response variable
The histogram is a popular graphing tool used in the presentation of the data. It is used to summaries discrete or continuous data that are measured on an interval scale. It is often used to represent the major features of the distribution of the data in an easy form.
The October costs of the garage.
In the data the costs of the servicing may be grouped into classes as follow:
|October costs Frequency Tally|
|200-300 |||| |||| |||| |||| |||| 25|
|300-400 |||| |||| |||| 15|
|400-500 |||| |||| |||| 14|
Tabulated (grouped) continuous data
Mean, Median and Mode are the most commonly used forms of average for the most business data. Each has its own characteristics, and whilst it will be possible to use them interchangeably with some data sets, for others there will be a single average which will be most appropriate. One consideration will be the type of the data with which we are dealing is it categorical, ordinal or cardinal; secondly we must ask if the data is discrete or continuous.
The arithmetic mean is the name used for the simple average which you can already calculate. Almost everyone understands this average and thus it will succeed in communicating the concepts of the location of the data to a wide range of people. It does not apply to the apply to the categorical data and its interpretation when used with ordinal data is to open to considerable doubt. When used with discrete data it may give an answer which cannot occur, for example fractional number of people.
This is the most commonly used average. The mean is calculated by adding the given values and then dividing the sum by the number of addends.
- If you have a large number of small values with a few very large values in your sample, mean averages get skewed: the mean is nearer to the bigger values even though the small values there are smaller numbers. If you have a few small values and a few large values, the mean average can get skewed this way too.
- If you have one, or more, outlying values that do not follow the general trend of the numbers in a sample, the mean average can be affected more dramatically than intended.
There are different ways of calculating Mean in different Data:
2.1.a) Untabulated data:
Suppose that there are number of people were 7, 5, 6, 7 and 8.
To calculate the mean, we would add all the numbers together to find the total number of people taken, and then divide by the number of values included. Here, the mean would be:
That is, / 5