TEAM: ______________________________________________________________________________________
NAME: AFIYA GEORGE
STUDENT ID#: 816018946
COURSE: MGMT 3060
Worksheet
1
Beg. Inventory
0
0
0
0
0
93
14
0
Marc
h
80
2
Order quantity
26
33
52
70
125
0
20
120
0
0
0
20
3
Number available
= (1) + (2)
Demand
26
33
52
70
125
93
34
120
80
44
27
20
29
40
55
99
32
79
93
40
36
17
28
18
5
End. Inventory
= max[(3)-(4), 0]
Revenue:
0
0
0
0
93
14
0
80
44
27
0
2
6
Sales
= $30 * min [(3), (4)]
Costs:
$780
$990
$1560
$2100
$960
$2370
$1020
$1200
$1080
$510
$810
$540
7
Ordering
If (2)>0, = $60 + ($20*
(2)), If (2)=0, = 0
Shortage
= - $7 * min[0, (3)-(4)]
Holding
= $1 * (5)
Total Costs
$580
$720
$1100
$1460
$2560
0
$460
$2460
0
0
0
$460
$21
$49
$21
$203
0
0
$413
0
0
0
$7
0
0
0
0
0
$93
$14
0
$80
$44
$27
0
$2
$601
$769
$1121
$1663
$2653
$14
$873
$2540
$44
$27
$7
$462
4
8
9
10
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Inventory Management Simulation Exercise
April
May
June
44
27
0
TEAM: ______________________________________________________________________________________
= (7) + (8) + (9)
11
12
Monthly Profit
= (6) - (10)
Annual Profit
$179
$221
$179
$400
$439
$839
$437
($1693)
$2356
$147
$1276
($417)
$1939
$2086
($1340)
$746
$1036
$1782
$483
$803
$78
$2265
$3068
$3146
A specific inventory forecast is exceptionally valuable, particularly when customer demand and supply chains are shifting
instantly. To accurately forecast future demand, forecasting demands for a mixture of data analysis, industry experience and
customer insights. Inventory forecasting allows you to determine how much of each sort of inventory will be needed in the future.
Resupply data, such as lead time, availability, and scheduling, are among the factors. The stock needed for replenishment is
determined by supply and demand, inventory targets, and inventory projections.
After monitoring the data given on the number of sticks sold for other new, state-of-the-art sticks from previous years, it
was determined that there has been a rise in sales in both months of July and August respectively in years 1 and 2. Therefore,
proven by the hysterical data, those months were expected to experience a rise in demand, which I predicted and however fell short
by a few. Upon realizing the pattern of increased demand, my predictions began to rise but were met with a shock in the month of
November where demand had decreased in comparison to the previous months and evidently led to holding costs. Having an excess
number of sticks on hand in November, no orders were placed in December as it was expected for demand to be within the
parameters of the stock on hand. After examining the market expectations of January being slow were high but there was still some
uncertainty, so an order was made in moderation which did not go as expected. Demand increased by 13 sticks in January causing a
major shortage cost. Moreover, during the months of January to May in the previous year’s sales increased slowly. With the rise of
demand in January, a larger number of sticks were ordered in February based on the fact that shortage costs overpowered the cost
of holding. The market took a complete turn compared to the previous years between February to June as demand dwindled slowly.
Furthermore, when taking into consideration the months of July to October if an increased amount of sticks were order there would
have been a cut down in cost. The quantity ordered for the particular months mentioned caused an increased shortage cost, it was at it’s highest
in the month of October. If I had evaluated the sales given for the previous year’s effectively, I would have realized that the sales figures given
Inventory Management Simulation Exercise
TEAM: ______________________________________________________________________________________
have never exceeded the amount of 100 sticks in any given month. This would’ve been reflected on there being little to no holding costs in the
months of November and December. With sales doubling in January year 2, it should’ve been expected that demand would be higher. If there
had been a greater order quantity this year shortage costs would not have been at an all-time high in January. This may have affected the
performance of the following moths as shortages lead to negative reviews which coherently affects consumer behaviour. For example, 1
customer looking to purchase a stick may have been met with the fact that the sticks are out of stock and took their dissatisfaction to the public
influencing others not to purchase. Furthermore, it may have driven potential and past customer towards purchasing the stick from a
competitor. The company experienced a major downturn in demand from January to June. However, on the bright side shortage costs were little
to none, although shortages could’ve been used to the company’s advantage. For example, people usually fight over popular products, hoping to
be first in line when they come back. One excellent method to turn a stockout into a sales opportunity is to ask clients to fill out a form to be
placed on a waitlist or to provide their email address to receive an alert when the item is back in stock.
Clear description of improved ordering strategy that would be implemented in the following year. Provides sound reasoning for this proposal.
Moving forward a hybrid of market research and time series would be implemented in the following year to improve the order
quantity. These specific strategies were chosen based on the fact that customer surveys are a crucial device for demand forecasting in market
research. Targeting your audience with online surveys is now simpler than ever and survey software has significantly enhanced analysis. Market
research can uncover opportunities, help with marketing campaigns, and help you better understand what your target audience needs. The
surveys listed below would be used: 1. Sample surveys are used to find out more about a small sample of potential customers' purchasing habits.
2. Conduct enumeration surveys, which involve talking to as many potential clients as is feasible in order to get more information. Secondly
there is time series analysis defined as a approach for predicting results over a period of time. By analysing historical inclinations, it forecasts
future outcomes with the assumption that future trends would be similar to those of the past. Better inventory management is one of the main
advantages of time series forecasting in supply chain management. Supply chain managers can optimize inventory levels to fulfil customer
demand while lowering inventory expenses by forecasting future demand. In conclusion, with the implementation of these two strategies
inventory management would become easier and more accurate.
Inventory Management Simulation Exercise