Increasing Sales Revenue for Books R Us
The underlying premise as to how sales revenues should grow
In the case of Books R Us sales revenue is stated per week starting on January 19th – 23rd 2004 up to May 3rd – 7th 2004.
As stated clearly in the information provided by Bob, our company’s president the sales revenue consists of:
Book sales from actual activity by telemarketers
Services rendered by the company to its clients other than selling books
Charges levied by the company for items not inclusive of a) and b)
This brief background information provides the basic framework for our construct.
The underlying premise as to how sales revenue should grow is based on the following;
Sales revenue is influenced by the actual sales activity of telemarketers and as such for sales revenue to increase the sales productivity of telemarketers needs to increase
Sales revenue is influenced by business activities outside its core operations and as such for sales revenue to increase then the scope and revenue generated from these non-core business activities needs to increase
The validity and veracity of this sales revenue construct shall be proven in the operationalization of the research process and the conclusions thereafter. (Williams, 2008)
Ways through which we can operationalize the research process for data analysis purposes
Operationalization in research basically involves two phases;
Clearly distinguishing the premise provided in the construct by ascertaining the variables inherent in the premise
Clearly showing how the variables can be measured and empirical observations made from them
As per the construct which is based on the data given the variables inherent in the first construct are;
Packet sold per time period t
Sales revenue per time period t
No. of telemarketers in time period t
Time period t
Time period t refers to a one week period
The variables inherent in the second construct are;
Books sales revenue in time period t
Services revenue in time period t
Charges revenue in time period t
Time period t
Time period t also refers to a one week period in the second construct.
Since we have already distinguished the variables we now need to know how will measure the said variables and obtain observations from them that are statistically sound and add value to the epistemology of the research work.
I have chosen to use moving averages as the measuring tool of the data provided. Moving averages will bring out focus on the direction the business is taking i.e. in terms of the variables measured. Moving averages are able to smooth out fluctuations in volume and price i.e. statistical noise that usually clouds up interpretation. (Williams, 2008)
Use a two day moving average. It is a much stronger indicator of momentum and turbulence in the variables measured.
The additional factors to consider are the type and quality of data in the moving average and their responsiveness to changes in the market conditions. Since moving averages can be a strong indicator of fluctuations it is necessary that the fluctuations measured are not extremely alarmist leading to erratic decisions.
I can apply this analysis technique to study businesses that have a product or service which is seasonal in nature and businesses that have varying sales cycles. This is because moving averages are good indicators of a trend once it has been already established. This trend may be seasonal or cyclical in terms of varying sales patterns.
Williams, Jan R et. al (2008). Financial & Managerial Accounting. New York. McGraw-Hill Irwin