This is a paper that is focusing on the quantitative analysis in Supply Chain and Logistics operations. The paper also provides the learning outcomes to use in writing the assignment paper.
Quantitative analysis in Supply Chain and Logistics operations
Learning Outcomes covered in this Assignment:
1. Firstly, evaluate the necessity for quantitative analysis in Supply Chain and Logistics operations
2. Secondly, apply appropriate theory and methods to a Supply chain scenario to aid decision making improvements.
3. Thirdly, critically evaluate the results of such an analysis and also new knowledge learnt in the business context
Coursework Task.
This section will cover learning outcomes 1, 2 & 3.
1. Evaluate the necessity for quantitative analysis in Supply Chain and Logistics operations
2. Apply appropriate theory and methods to a Supply chain scenario to aid decision making improvements.
3. Critically evaluate the results of such an analysis and also new knowledge learnt in the business context.
Coursework scenario
Random Computers is a wholesale firm that distributes computers to customers. The arrival of Sam Snear the new Managing Director has brought a new business strategy based on efficiency and reduction of costs.
Quantitative analysis in Supply Chain and Logistics operations
Task 1: (20 marks)
Previously Random Computers had maintained ample inventories of computers in the warehouse to fulfil orders immediately. So rough forecasts of demand was adequate to make decisions about stock replenishment. Scientific management is to be used to reduce inventory levels and minimise total inventory costs.
Additionally, the logistics Manager Jo Branding has developed a system of forecasting based on statistical forecasting that considers seasonal effects. The system is to generate three sets of forecasts:
Moving average method
Exponential smoothing
Exponential smoothing with trend.
Jo will base her monthly inventory levels on the monthly sales of laptops over the past 3 years see fig1.
a) Firstly, you will need determine the seasonal factors for each of the 12 months based on past sales. Also, use these seasonal factors to apply a moving average based method to forecast monthly sales for each month. You will need to choose and justify how many months of previous data for your monthly moving average.
(4 marks)
b) Secondly, apply the exponential smoothing method to forecast the monthly sales for each month. You must decide and justify the initial estimate and the value of the smoothing constant (a).
(4 marks)
c) Thirdly, using the seasonal effect apply exponential smoothing with trend to forecast monthly sales. Use the initial estimates and also (a) value that you chose for section (b). Also use zero for the trend and suggest a value for (b).
(4 marks)
d) Fourthly, compare and comment on your MAD and MSE values for sections (a), (b) and (c).
(2 marks)
