Describe the Sales Tracking and Customer Relations Analyses? and to analyse a set of data, and write a brief report, identifying and explaining your insights into the operation of “The FedFone Co.”?
Businesses evolve around data, now a days, every business process of any organization generates a lot of data. Analysis of those data gives critical insight in the business process, future scopes and strategies etc. FFC or FedFone Co. is such a business in Ballarat area. It sells mobile phones, accessories, mobile phone insurance plans from 3 shops in the Ballarat area. Now the business is planning for expansion. Thus the owner wants to make new business strategies, improve customer relationships. In order to do so, the business needs to analyze the sales data from previous months.
In this section the outcomes of the sales data based on different criteria will be discussed. The total income, expense and profits will be analyzed by different combinations of the shops, staffs, phone models etc.
The company needs to pay $14 for postal charge, whenever, there is a phone repair. The phone manufacturing companies reimburse charge but that may be partially or totally. The income and expense from phone repair will also be analyzed.
1. Following pivot table shows the outcome of the analysis of total income based on different shops, staffs and phone modes. The sub totals of these three categories have been also there.
2. Following pivot table shows the outcome of the analysis of total expense of FFC, based on the shops and staffs. The subtotals of each of the two groups have been also there.
1. Following pivot table shows the outcome of analysis of total profit of FFC based on the shops, staffs and the phone models. The sub totals of each group also have been there.
2. Following pivot table shows the outcome of analysis of the repair income and expenses based on phone models, staffs and shops. The sub totals of each category have been also given.
In this section the outcomes of the analysis of sales information of FFC will be observed to find different best and worst cases. For example, the best and worst selling phone plans, the best and worst performing sales staff in terms of total sales, changes in total profit if the policy of charging for training service is changed etc.
1. Following chart shows the comparison of totals sales of different phone plans. The values will be observed to find out the best and worst selling phone plans. According to the chart, Optrus plan 1 and Vodrfon plan 2 are the best and worst selling phone plans respectively.
In this section the recommendation for FFC will be outlined. The recommendations are based on the current business process of FFC and the results from all calculation and observations carried out so far.
1. For improving the sales activities in future, FFC should take care of the different shops and staffs. All shops and staffs are not performing same and satisfactory levels. Particularly, FFC should focus on the sales activities in the Suburb area, on the sales staff like Ringo, who are not performing well, and on products other than phone models.
2. For improving the decision making activities, FFC should collect more information. Other than sales records it should focus on collecting customers’ demographics. These will help in building better customer relationships in future. The data should be collected in proper format and should be ‘cleaned’ before being used in data analysis.
3. Data validation restricts input to different fields and reduces the scope of erroneous data input, manual data entry errors etc. In the Sales datasheet, column A has dates. But there is no validation on the cells under this column. Thus anything other than a valid date can be entered. Also there may be outdated entry. A validation specifying range of possible inputs and proper format of the data will help in restricting the errors and data entry. In the column B, the valid input will be any mane of the three shops. But, there can be any string without proper validation. The valid input in column M should also be any whole number from 0 to 24. These validations in these columns will help in better record keeping and organizing.
Albright, S., Winston, W., & Zappe, C. (2010). Data Analysis and Decision Making. Cengage Learning.
Gross, D., Akaiwa, F., & Nordquist, K. (2013). Succeeding in Business with Microsoft Excel 2013: A Problem-Solving Approach. Cengage Learning.
Jelen, B. (2010). PowerPivot for the Data Analyst. Pearson .
Jelen, B., & Alexander, M. (2013). Excel 2013 Pivot Table Data Crunching. Que Publishing.
Ralston, B. (2011). PowerPivot for Business Intelligence Using Excel and SharePoint. Apress.
Winston, W. L. (2009). Microsoft® Excel Data Analysis and Business Modeling. Microsoft Press.
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