Question

Acme Manufacturing

Forecasting Analysis Paralysis

Acme produces technology parts used by the manufacturers of self-driving vehicles. The primary demand for Acme’s four products is dependent on the output of the manufacturer’s MRP systems. Acme produces the required quantities for the manufacturers and ships them just-in-time to reach the production lines. Acme also must provide inventory to support the repair of vehicles after they are sold to consumers. To meet this additional demand, they augment their internal production plans by adding some amount for a spare parts inventory. Inaccuracy in this process for spare parts has generated significant complaints from repair facilities who order the parts and expect them to be available for immediate shipping.

Since Acme’s background was manufacturing, they had no need for forecasting methods and initially their simple process of having the production scheduler add quantities to production runs as he saw fit actually worked. Anything not shipped to manufacturers remained in the warehouse to fill repair orders. However, increases in the demand for their products has created a situation where on any given day Acme is overstocked on some items and stocked out on others.

Pressure on both costs and customer service have forced management to seek more formal forecasting methods. Management has requested that you evaluate the repair demand for Acme’s five products and make appropriate recommendations.

1a. Evaluate the historic demand of each item, discuss the demand pattern you detect, pertinent descriptive statistics, and any anomalies in the data (if anomalies are detected, make appropriate corrections).

1b. Recommend an appropriate forecasting method for each item. Justify your recommendation based on the historic demand pattern and the forecasting error.

1c. Provide forecasts for the next 3 weeks for all 4 items using the methods you propose.

Week	Product A	Product B	Product C	Product D
1	14	44	50	24
2	13	43	54	26
3	12	40	57	22
4	16	39	60	20
5	18	39	61	28
6	13	38	63	24
7	14	35	66	27
8	13	30	90	23
9	12	29	68	28
10	10	25	71	26
11	14	20	74	23
12	13	19	75	18
13	15	20	74	28
14	12	18	77	17
15	11	17	79	52
16	10	17	83	22
17	12	16	83	20
18	14	15	85	18
19	15	15	88	24
20	14	14	90	20

Answer 1

The attach images details solution in R-software given below

1.a)

DDemand pattern for each Product

By trend 1 (Product A)

By trend-2 (Product B)

Trend-3 (product C)

Trend-4 (Product D)

1.b)

1.

2.

3.

4

5.

6

1.c) Forecastion the next 3 weeks for all 4 items using the methods of ARIMA (auto Regressive moving average method)