business decision making

Topics: Standard deviation, Arithmetic mean, Sales Pages: 12 (2140 words) Published: October 20, 2014

Table of Contents

1.1 plan for the collection of primary and secondary data

In order to understand the response or view of the customers about the store, primary and secondary data needed for Shark Spin are as follows: Primary Data:
In order to do whatever survey needs to be conducted is known as primary data (Bpp, 2004, p7). Survey can be done to investigate Customer’s response information. What customers expect from the firm.

What they think needs to be improved can be surveyed.
Then the average income and expenditure, profit margin(before 10years and at present) Rivalry among existing firm can be surveyed.
How many days a week they eat fish or seafood.
Secondary Data:
Despite being used earlier, the data which is used for survey is known as secondary data (Bpp, 2004, p7). Secondary data that are used here are as follows: Range: This indicates the range of areas to cover. In order to do that we can take help from Google. Through online searching we can know about the range of areas needs to be covered. Pricing: Price of the product is the most important. Here we can take help from Internet. Moreover, from the data of the price in national markets set by the other companies can be found in the Internet and on some research papers. Customer Service: We can set a strong customer service through getting help from any published journal on the sector of customer service. Local Competitive Set: This can be found on articles, journals, local magazines, research papers indicating the competition in the seafood field.

1.1.1 Presenting Survey Methodology and Sampling frame used

The survey methodology is presented below:
Random sampling
The selection of a random sample, each element of the population has an equal chance of been selected. In general we do not assume that the underlying data follows a normal distribution, but in order to calculate bounds and confidence intervals from single samples it may be useful to assume that the estimates follow a normal distribution. This assumption will be appropriate for large sample sizes but will be problematic for small sample sizes drawn from highly skewed data. Example:

At first, we assume that there are 30 companies in 3 markets. Moreover, the first market has 12 companies, second and third has 9 companies respectively. If we take 12 companies to investigate then we need to calculate the percentage of each group. Calculate market share:

First, % of companies that are in the first market are {(12/30)*100} = 40%. So the rest two markets’ percentage will be 30% for each.
Now, our sample companies will be distributed in the 3 markets in the following way: First market: {(40*12)/100} = around 5 companies. So, second and third market will get 4 and 3 companies respectively. Now, we can choose 5 companies from first market, 4 from second market and 3 from third market to conduct our survey methods.

Then we need to choose companies based on our requirement. As The Shark Spin survey on reduction in sales, the companies which have increased their sales in this sector must be selected. Thus we can conduct a survey on the selected companies (Black, 2009). 1.2 Designing a Questionnaire for a given business problem

Our next task is to design a questionnaire. Precise information can be found through questionnaire. In order to do so, targeting respondent should be identified. Our focus should be on the causes of decrease in sales and profit forecasting. So, we need to know about the cost structure, profit margin, and quality, market price, sales offer, sale service, complain of customers, probability of dissatisfaction etc. Through this questionnaire we are going to find out about the causes in decrease of sales in firm. Normally some of the questions are MCQ types and some are open ended types. In this case, we should follow MCQ and open ended questions as well. So, MCQs will be asked very precisely to get the targeted response...

References: 1. Cagan, M 2008, Inspired: How To Create Products Customers Love, 1st edn, Silicon Valley Business Journals, South Market Street, San Jose
2. Haines, S 2008, The Product Manager 's Desk Reference, 1st edn, McGraw-Hill, New York
3. Peppers, D & Rogers, M 2008, Rules to Break and Laws to Follow, Wiley Publication, New York
4. Selden, P H 1998, Sales Process Engineering: An Emerging Quality Application, 1st edn, Quality Progress
5. Groebner, F D, Shannon, W P, Fry, C P, & Smith, D K 2010, Business Statistics, 8th edn, Prentice Hall Publication, New Jersey
6. Hamilton, C L 2012, Statistics with Stata, 12th edn, Cengage & Learning, Stanford
7. Black, K 2009, Business Statistics: Contemporary Decision Making, 6th edn, Wiley Publication, New York
8. Koop, G 2006, Analysis of Financial Data, 1st edn, Wiley Publication, New York
9. Anderson, R D, Sweeney, J D, & Williams, A T, 2010, Statistics for Business and Economics, 11th edn, South-Western College Publication, Los Angeles
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