How to Use the Scientific Method in Business

Business Tools & Methods

Business tools and methods

Q1 Hypothesis for a local business: High employee turnover

High employee turnover is caused by the large number of part-time teenagers employed by the company who have school commitments that compete with work.

To test the hypothesis the company could determine if rates of employee attrition tended to increase at times when students tended to have other commitments (such as at the end of summer break or before midterms, finals, and the SATs). Or did attrition have a correlation with other factors, such as the opening of a new business nearby that paid better wages? Did rates spike at the end of the training period (which might highlight a problem with orientation or hiring)? It could compare the rates of attrition of teenagers compared with other employees at the company. It could also compare the rates of part-time vs. full-time workers' attrition. It could be that in general workers who are employed part-time are more likely to leave the company, because they have less of a personal investment in the company in terms of the commitment they have made to it. If available, the company could compare the rates of turnover with rivals, to see if this was a problem particular to its organization or other, similar businesses had high rates of attrition.

To see if another problem was the reason for the high rates of turnover, the company could survey its former employees via questionnaires. Regardless, the hypothesis is testable and can be answered based upon available data. The data can also suggest whether the hypothesis is better than its rivals or not -- for example, it may be that teenagers do indeed have high rates of attrition, especially around very busy time periods for them, but all part-time workers have higher rates of attrition than full-time workers. This might highlight the need to hire more full-time workers with benefits to ensure that employees have a strong commitment to the organization and the costs of paying workers benefits outweighs the costs of worker attrition from training and recruiting new workers.

Q2. One of the problems with the formulation of the research question is that although all restaurants might have seen a downturn of beef consumption, this does not mean that fears of E.coli contamination are to blame. For example, the revelation about the E.coli could correlate with warmer weather, which might make people more apt to seek out chicken and fish. Or, it could be that people are concerned about cholesterol and calories and red meat tends to be associated with higher-cholesterol, higher-calorie diets (Davis 2011). It could even be that certain fish and chicken dinners (or even vegetarian dinners) have become trendier, such as salmon.

To determine if it is E.coli contamination that caused the downturn, the demand for beef should be compared immediately before and after the revelation. Other environmental factors which also changed around this time period should also be assessed (such as a change in temperature or other news articles about common food consumption trends). Last year's figures should be compared to see if there was a downturn around this same time during the season, which would indicate that other factors might impact the decision-making of customers.

Economics could also be a factor. If there is a downturn in the economy, people might be ordering cheaper meals and avoiding more expensive beef. If less expensive meals like pasta and sandwiches had gone up while expensive menu items (not just beef) had gone down, along with economic signs of 'softening' in macroeconomic figures released by the government, this would suggest an alternative explanation.