Research and Decision Making – CoffeeTime

In this paper, a variety of statistical research and decision-making methods will be reviewed based on the University of Phoenix Managing Research Design simulation (2008). CoffeeTime is currently a successful coffee bar chain in North America and Europe. With South Asia’s booming economy, CoffeeTime has decided possibly to enter the Indian coffee market. Before a final decision is made on where to place new coffee shops, research had to be done. Team A reviewed this research to identify (i) knowable, unknowable and researchable Data; (ii) limitations of the data, (iii) further data, (iv) further business strategy in India, and (v) research limitations. This paper will show that this information is paramount to the decision-making process.

Knowable, Unknowable and Researchable DataFrom Brad’s diary it can be seen that “India is one of the most powerful economies in South Asia” (University of Phoenix, 2008, p. 1). The cities chosen to study were selected to have the highest degree of affluence and the most modern cultural outlook. The cities chosen are Ahmedabad, Bangalore, Chennai, Delhi, Mumbai and Pune. Secondary data consists of general demographic information for each of the cities considered by CoffeeTime. Some of this is readily available from public sources, but specific secondary data is available for purchase from research companies that specialize in collecting and providing focused data on each city for a fee. The demographics data selected are population by age, gender division, education and monthly income. Leisure and lifestyle date include average daily visitors to a mall, number of malls and number of restaurants per square kilometer. Competitive data include number of coffee chains, market size for coffee powder and number of restaurant chains.

The initial secondary data shows some interesting trends as shown in Figure 1.

Figure 1Two cities seem to stand out to the competition. These...