Reference no: EM133489374 , Length: word count:2500

Business analytics and Intelligence

Assignment Brief - Mode E and R Regulations

Learning outcome 1: Define and evaluate key concepts of business analytics.
Learning outcome 2: Critically apply business analytics skills for decision making.
Learning outcome 3: Critically analyse and interpret the outputs of data mining models and forecasting results for end-users.
Learning outcome 4: Solve managerial problems and make systematic decisions by applying business data analysis techniques.
Learning outcome 5: Have ability to apply business analytics to various international business contexts by
selecting appropriate techniques.

Task One-Business analytics concepts

a. Describe what you have learned about the Forecasting methods. Give a proper example for that
b. Critically discuss and analyse five published papers which have used forecasting with proper explanation. The technique, its application and the results need to be interpreted properly

Task Two- Marketing Analytics
By analyzing previous historical data for FitBit sale company, it can be seen that the sale volume has been changed according to its price in different periods. The values have been reported in the following table. This company is going to launch a new product and the price needs to be decided based on the market analysis. Determine the appropriate price for the new developed FitBit with the aim of maximizing the company's profit. The demand of new product has a direct relationship to its price.

Table 1- Demands of FitBit based on a price level according to previous experiences

Price (£)	Demand
115	4150
118	4070
121	3730
126	3420
126	3170
129	3020
131	2700
136	2550
136	2460
138	2400
141	2310
144	2220
146	2160
148	2140
151	2100
154	2080

The main objective of the company is to maximize profit regarding to the new product. It is assumed that the unit production and supply cost of each FitBit is £76, so the profit of each unit will be (the sale price - unit production cost).
a) Use Excel to determine the estimated demand quadratic equation function and describe why quadratic form is preferred.
b) Use Excel solver to find the optimal price which maximizes the company's profit.
c) Determine the optimal demand.
d) Compute the optimal profit.
e) Interpret the results.
f) If the supply cost of each FitBit is £67 and then £87 determine the optimal price and interpret the results appropriately.
g) Suppose that the supply cost is £87 and the company has decided to set the price less than £130, then what will be the optimal price? Interpret the results.

Task Three- Forecasting
Suppose that you have gathered sales data of above company from 2015-2021 in different quarters. You are going to consider the company sales value and to forecast the company amount of sales in 2021 in different quarters. Look at the gathered data of previous years related to the amount of sales in each quarter which have been reported in Table 2.

Table 2- Data of amount of sales among previous years

Year	Q	Revenue	Four Moving average	Baseline	Seasonality	Deseasonality	Trend	Forecast	Error	MAD Error	MSE	MAPE
2015	Q1	1920
2015	Q2	2910
2015	Q3	4630
2015	Q4	2520
2016	Q1	2100
2016	Q2	3120
2016	Q3	5050
2016	Q4	2570
2017	Q1	2250
2017	Q2	3240
2017	Q3	5230
2017	Q4	2640
2018	Q1	2360
2018	Q2	3430
2018	Q3	5600
2018	Q4	2880
2019	Q1	2590
2019	Q2	3790
2019	Q3	6220
2019	Q4	3150
2020	Q1	2810
2020	Q2	4050
2020	Q3	6560
2020	Q4	3320
2021	Q1	2940
2021	Q2	4280
2021	Q3	6900
2021	Q4	3440

a. Plot the data and describe the main features of the series.
b. Compute the four-period moving average and enter your values in the appropriate columns. Calculate the Centered Moving Average (CMA)/Baseline. Interpret it.
c. Calculate the Trend and interpret the trend.
d. Determine the Seasonality (St) and interpret it properly.
e. Forecast the revenue for 8th year.
f. Calculate the Error, mean absolute percentage error (MAPE), Mean Square Error (MSE) and Mean Absolute Deviation (MAD).
g. Write a brief report to explain and evaluate and make comments on the error variables, the forecasted and actual revenues.