three customers contribute between 27% and 74% revenue 2004-2006 questions

Questions

As part of an effort to increase cash and reduce the cash cycle, the connections between...

As part of an effort to increase cash and reduce the cash cycle, the connections between the AP and AR processes are often scrutinized to see if the company is fully billing what it is entitled to bill … to this end, folks sometimes ask about "unbilled" and how long that "unbilled" has remained in that state … is number for "unbilled" best derived from what has been declared as revenue under 606 but not yet billed or as what has been billed out to vendors if vendors are involved in the performance?

In: Accounting

Chapter Case: Campus Bikes Campus Bikes is a popular bicycle shop located near a major university....

Chapter Case: Campus Bikes

Campus Bikes is a popular bicycle shop located near a major university. The business has grown and the owner, Mark Turner, wants to install an up-to-date computer system to handle all business functions.

Background
Campus Bikes sells several brands of new bikes, including everything from high-end racing models to beach cruisers. In addition to sales of new bikes and accessories, Mark’s service department is always busy. The staff includes Mark himself, a bookkeeper, two part-time sales reps, a full-time mechanic, and several part-time service helpers who assemble bikes.

Before opening the shop three years ago, Mark worked for many years in his father’s auto dealership, Turner Motors, and he learned all about the automobile business. In the bike shop, he runs a similar operation, but on a much smaller scale. For example, sales orders are recorded on pre-printed forms, and service requests are written up just as they would be in an auto service department.

Mark’s customers find him fair and reasonable. He likes to say that the main difference between his business and a big-box retailer is that he knows his customers and will do whatever it takes to keep them happy.

You work at the college as a lab assistant in the computer information department. You earned a computer science degree at a two-year school, and you recently decided to work toward your four-degree. The computer lab manager, Jill, often suggests that local businesses contact you for help in troubleshooting IT issues.

This morning, you received a call from Mark, who wants to hire you as a consultant to help plan a system for Campus Bikes. You learned that Jill had referred him, and you are excited to have this opportunity. It probably didn’t hurt that both you and Jill had bought bikes from Mark, and already knew him. After spending several weekends talking with Mark and the staff, you are ready to start. You decide to use an object-oriented approach that will be easy to understand.

Tasks
1. List possible objects in the new bike shop system, including their attributes and methods. Do not draw a diagram for this. Just a three column list will be appropriate.
2. Identify three possible use cases and actors.
3. Create a use case diagram that shows how service requests are handled. This diagram should be drawn similar to Figure 6-16 on page 189 of the text. Be sure to use the actors and use cases appropriate for this case as detailed above.
4. Create a state transition diagram that describes typical customer states and how they change based on specific actions and events. You can find an example of a state transition diagram in Figure 6-21 on page 192 of the text.

In: Computer Science

Willow Brook National Bank operates a drive-up teller window that allows customers to complete bank transactions...

Willow Brook National Bank operates a drive-up teller window that allows customers to complete bank transactions without getting out of their cars. On weekday mornings, arrivals to the drive-up teller window occur at random, with an arrival rate of 24 customers per hour or 0.4 customers per minute. In the same bank waiting line system, assume that the service times for the drive-up teller follow an exponential probability distribution with a service rate of 36 customers per hour, or 0.6 customers per minute. Determine the following operating characteristics for the system:

The probability that no customers are in the system. If required, round your answer to four decimal places.

P₀ = ??
The average number of customers waiting. If required, round your answer to four decimal places.

L_q = ??
The average number of customers in the system. If required, round your answer to nearest whole number.

L = ??
The average time a customer spends waiting. If required, round your answer to four decimal places.

W_q = ?? min
The average time a customer spends in the system. If required, round your answer to nearest whole number.

W = ??min
The probability that arriving customers will have to wait for service. If required, round your answer to four decimal places.

P_w = ??

In: Operations Management

Using C++ There are number of cable company in southern California which offer number of services...

Using C++

There are number of cable company in southern California which offer number of services

for customers. This company have two types of customers:

Residential and business. There are two rates for calculating a cable bill: one for Residential customers and one for business customers.

For residential customers the following rates apply:

Bill processing Fee $4.50
Basic service fee $20.50
Premium channels $7.50 per channel

For business customers the following rates apply:

Bill processing fee $15.0
Basic service fee $75.0 for the first 10 connections, $5.00 for additional connections.
Premium channels: $ 50.00 per channel for any number of connections.

Input:

The customer’s account number,

Customer code

Number of premium channels

And in case of business customers, number of basic service connections

What to deliver (output) Customers’ account number and the billing amount

Run your program for the given data:

Enter customer code: R or r (Residential) or B or b (Business) B

Enter number of service connections 16

Enter number of premium channels 8

Display total billing amount:

Run for residential customers:

R

Test your program for 12 premium channels.

flow chart, pseudo code are required for every projects and activities.

In: Computer Science

1. A supervisor suggests that the old computer program for estimating delivery times be abandoned. Instead,...

1. A supervisor suggests that the old computer program for estimating delivery times be abandoned. Instead, schedulers could use an alternative such as MapQuest to estimate driving times. As a pilot study, 500 recent deliveries were randomly selected. The Excel data listed below contains the following variables:

Actual Times: actual time required to make delivery

Old Model Deviations: difference in actual delivery time and predicted delivery time using old computer prediction model

MapQuest: predicted delivery times for the randomly selected routes using MapQuest

Use the data to calculate the deviations for the MapQuest estimates (DMapQuest = actual delivery time – MapQuest predicted delivery time), then construct an appropriate graph for comparing the deviations for the Old Computer model and the MapQuest model. Interpret the results and indicate which prediction model should be used in the future. (Do NOT include the calculated deviations here. Do include the graph and interpretation.)

2. A driver reads your answer to part (1) and makes the following comment: MapQuest gives driving times for cars. Driving times for trucks will probably be longer because we can’t go as fast, especially in city traffic. Is there some way to adjust the MapQuest prediction to make it fit trucks better? Construct a fitted line plot (scatterplot with fitted linear regression line) using the MapQuest times as the predictor variable and the actual times as the response variable. Call the fitted values ‘Adjusted MapQuest’ times. Provide the fitted line plot, regression equation and R2 values associated with the ‘Adjusted MapQuest’ times. Interpret your results and indicate whether the driver’s suggestion is valid or invalid.

3. Use the regression equation given in part (2) to provide ‘Adjusted MapQuest’ times for the sample of 500 deliveries and calculate the Adjusted Deviations = Actual times - Adjusted MapQuest times. (You do NOT need to put those values here.) Construct an appropriate graph for comparing the deviations associated with the Old Computer Model, the MapQuest model and Adjusted MapQuest model and include it here. Interpret the graph and recommend the modeling tool (method of predicting delivery times) you feel is most accurate.

Actual Times	Old Model Deviation	MapQuest
142	42	113
82	-18	79
142	42	101
151	51	112
154	54	127
124	24	90
134	34	89
135	35	113
123	23	94
150	50	111
121	21	105
111	11	101
142	42	109
118	18	102
159	59	119
98	-2	89
150	50	115
128	28	101
134	34	110
158	58	123
106	6	89
147	47	123
117	17	84
153	53	105
126	26	96
129	29	100
98	-2	76
139	39	111
119	19	95
98	-2	69
137	37	105
140	40	110
140	40	121
134	34	99
131	31	100
98	-2	76
123	23	116
108	8	96
112	12	85
143	43	116
133	33	92
127	27	99
124	24	95
102	2	82
106	6	87
158	58	110
122	22	93
117	17	93
179	79	142
124	24	91
127	27	114
109	9	90
121	21	96
119	19	92
125	25	107
121	21	106
138	38	112
129	29	111
137	37	112
121	21	99
156	56	110
142	42	113
112	12	89
105	5	85
142	42	114
142	42	118
137	37	107
94	-6	79
132	32	115
112	12	98
97	-3	85
140	40	112
126	26	106
131	31	98
93	-7	81
161	61	115
113	13	87
108	8	81
117	17	102
147	47	108
113	13	98
92	-8	83
136	36	106
118	18	88
120	20	84
82	-18	68
139	39	111
121	21	101
157	57	129
150	50	110
133	33	95
118	18	107
115	15	93
144	44	110
124	24	110
110	10	77
145	45	112
172	72	123
111	11	88
134	34	106
131	31	103
118	18	116
122	22	100
118	18	93
132	32	108
109	9	100
100	0	83
111	11	97
109	9	82
141	41	102
124	24	108
85	-15	67
126	26	97
140	40	114
121	21	102
148	48	118
110	10	92
164	64	127
136	36	106
138	38	107
142	42	100
112	12	96
129	29	94
151	51	112
122	22	97
100	0	73
124	24	98
141	41	115
126	26	106
120	20	92
105	5	97
144	44	92
136	36	107
99	-1	94
97	-3	102
93	-7	86
132	32	97
130	30	108
89	-11	76
107	7	82
128	28	91
108	8	98
134	34	101
122	22	93
135	35	105
118	18	95
121	21	98
98	-2	78
104	4	82
117	17	83
135	35	112
175	75	131
120	20	113
94	-6	81
106	6	95
132	32	110
116	16	98
137	37	99
81	-19	73
122	22	93
101	1	85
126	26	111
148	48	116
136	36	109
90	-10	85
135	35	102
138	38	111
158	58	125
118	18	94
120	20	91
165	65	123
116	16	104
117	17	90
137	37	99
123	23	110
144	44	109
159	59	126
114	14	104
101	1	93
114	14	98
101	1	81
122	22	87
168	68	133
111	11	104
147	47	122
130	30	106
131	31	105
117	17	102
113	13	102
125	25	98
123	23	96
126	26	113
92	-8	78
136	36	106
124	24	95
153	53	131
91	-9	87
135	35	102
129	29	94
123	23	97
150	50	115
145	45	105
103	3	86
127	27	104
122	22	92
119	19	92
117	17	97
136	36	107
85	-15	70
106	6	84
111	11	89
166	66	119
124	24	112
163	63	122
154	54	104
134	34	93
100	0	83
109	9	82
125	25	105
72	-28	79
93	-7	86
148	48	110
70	-30	70
125	25	93
163	63	119
111	11	94
111	11	84
124	24	111
117	17	98
148	48	109
152	52	118
112	12	94
115	15	82
89	-11	87
124	24	88
126	26	104
133	33	103
131	31	107
178	78	134
69	-31	63
129	29	100
119	19	96
106	6	95
163	63	132
160	60	135
107	7	96
118	18	87
130	30	111
123	23	102
133	33	112
139	39	123
115	15	104
101	1	89
152	52	123
117	17	105
110	10	86
130	30	98
138	38	117
111	11	85
123	23	98
99	-1	87
149	49	107
130	30	95
161	61	121
157	57	123
86	-14	76
108	8	98
128	28	92
112	12	88
149	49	104
127	27	96
93	-7	82
136	36	105
119	19	93
118	18	90
114	14	89
146	46	105
106	6	83
94	-6	74
129	29	112
133	33	97
156	56	125
151	51	122
108	8	87
84	-16	74
127	27	91
150	50	103
137	37	107
112	12	97
124	24	103
101	1	77
125	25	98
122	22	92
117	17	91
136	36	110
110	10	86
123	23	116
129	29	102
128	28	105
126	26	105
141	41	104
113	13	99
127	27	98
137	37	96
112	12	93
159	59	124
148	48	108
111	11	90
133	33	113
118	18	104
157	57	108
118	18	98
147	47	125
118	18	94
125	25	109
110	10	85
105	5	97
75	-25	74
130	30	100
127	27	110
93	-7	70
123	23	99
114	14	94
159	59	129
113	13	108
89	-11	78
131	31	102
154	54	138
90	-10	74
98	-2	87
139	39	114
136	36	107
103	3	76
114	14	96
126	26	98
147	47	117
101	1	74
133	33	92
143	43	109
110	10	95
98	-2	89
121	21	88
113	13	91
149	49	123
128	28	97
133	33	103
116	16	94
176	76	124
117	17	99
118	18	99
92	-8	89
96	-4	77
126	26	90
81	-19	72
139	39	108
107	7	93
76	-24	64
133	33	107
109	9	79
137	37	111
127	27	101
136	36	103
134	34	95
100	0	83
103	3	88
106	6	75
125	25	101
120	20	101
127	27	94
129	29	99
148	48	110
108	8	92
123	23	106
136	36	118
162	62	116
113	13	81
136	36	108
119	19	96
135	35	113
144	44	91
166	66	124
143	43	114
90	-10	74
146	46	111
167	67	124
128	28	107
125	25	96
112	12	93
151	51	122
73	-27	76
125	25	104
116	16	94
116	16	101
103	3	100
104	4	86
133	33	104
166	66	119
125	25	107
148	48	108
147	47	117
85	-15	78
123	23	95
98	-2	91
145	45	120
148	48	115
101	1	80
131	31	110
115	15	90
99	-1	84
146	46	120
129	29	107
91	-9	77
116	16	92
126	26	92
90	-10	69
125	25	92
143	43	101
114	14	94
144	44	107
76	-24	82
124	24	97
151	51	123
133	33	101
103	3	91
103	3	97
124	24	108
96	-4	77
132	32	107
142	42	108
136	36	110
124	24	104
146	46	123
97	-3	83
99	-1	90
118	18	81
117	17	101
135	35	116
151	51	123
124	24	88
115	15	92
142	42	111
92	-8	90
117	17	88
148	48	116
146	46	114
167	67	122
114	14	91
149	49	109
123	23	102
111	11	100
106	6	92
126	26	103
148	48	117
108	8	83
108	8	85
166	66	137
140	40	103
119	19	85
126	26	94
132	32	92
141	41	118
157	57	127
142	42	112
145	45	100
81	-19	77
119	19	112
153	53	112
97	-3	78
123	23	91
121	21	91
121	21	89
120	20	106
104	4	83
97	-3	70
159	59	122
106	6	83
180	80	134
144	44	108
152	52	120
120	20	98
126	26	102
101	1	89
131	31	109
94	-6	86
106	6	79
124	24	95
145	45	118
168	68	111
123	23	95
130	30	95
113	13	94
137	37	110
90	-10	90
93	-7	79
147	47	112
146	46	108
125	25	97
128	28	99
132	32	97
119	19	77

In: Statistics and Probability

A -year study conducted by the American Heart Association provided data on how age, blood pressure,...

A -year study conducted by the American Heart Association provided data on how age, blood pressure, and smoking relate to the risk of strokes. Data from a portion of this study follow. Risk is interpreted as the probability (times 100) that a person will have a stroke over the next 10-year period. For the smoker variable, 1 indicates a smoker and 0 indicates a nonsmoker.

Risk	Age	Blood Pressure	Smoker
10	85	150	1
30	68	207	1
11	64	104	0
61	86	127	0
39	70	139	0
49	83	155	0
7	68	179	1
36	84	176	0
41	57	169	0
25	66	161	1
39	69	122	0
37	90	101	0
26	89	124	0
63	81	118	0
35	84	181	0
33	89	176	0
30	66	156	1
34	66	164	1
15	74	210	1
32	76	160	1

a. Develop an estimated regression equation that can be used to predict the risk of stroke given the age and blood pressure level. Enter negative value as negative number. Use Table 4 in Appendix B.

The regression equation is (to 4 decimals)

Risk=_______+________ age+________ blood pressure

	S=____	(to 4 decimals)
	R^2=_____	(to 4 decimals)
	R^2 adj____	(to 4 decimals)

Analysis of Variance

SOURCE	DF	SS (to 2 decimals)	MS (to 2 decimals)	(to 2 decimals)	-value (to 4 decimals)
Regression
Residual
Total

b. Consider adding two independent variables to the model developed in part (a), one for the interaction between age and blood pressure level and the other for whether the person is a smoker. Develop an estimated regression equation using these four independent variables. Enter negative value as negative number. Use Table 4 in Appendix B.

The regression equation is (to 4 decimals)

Risk=______+______ age+_______ blood pressure

	S=	(to 4 decimals)
	R^2=	(to 4 decimals)
	R^2 adj=	(to 4 decimals)

Analysis of Variance

SOURCE	DF	SS (to 2 decimals)	MS (to 2 decimals)	(to 2 decimals)	-value (to 4 decimals)
Regression
Residual
Total

c. At a level of significance, test to see whether the addition of the interaction term and the smoker variable contribute significantly to the estimated regression equation developed in part (a). Use Table 4 in Appendix B.

What is the value of the F test statistic?

(to 2 decimals)

P-value is - Select your answer -lower than 0.01between 0.01 and 0.025between 0.025 and 0.05between 0.05 and 0.10greater than 0.10Item 36 , so the addition of the two independent variables - Select your answer -is not is 37 statistically significant.

In: Statistics and Probability

Case Study: PackCo PackCo is an Australian-listed company that manufactures packaging products. PackCo services customers that...

Case Study: PackCo

PackCo is an Australian-listed company that manufactures packaging products. PackCo services customers that are mainly food and beverage producers. The company currently operates in Australia, New Zealand and USA, and employs more than 6,000 staff. With its head office in Melbourne, Victoria, PackCo is listed on the Australian Stock Exchange and operates a number of production facilities in Australia, mainly in Victoria and South Australia. Since its inception, the company has grown steadily with revenues reaching almost USD $4 billion in 2016. The company has also acquired a number of other businesses to support its business growth.

PackCo sells its products and services to both local and overseas customers, and is reliant on third party logistics (3PLs) for transportation and forwarding companies to move its products. A newly appointed Supply Chain Optimisation Manager, Aras, has been tasked to oversee transportation and freight optimisation within PackCo. His responsibilities include conducting RFPs (requests for proposals) for the selection of carriers, and also implementing S&OP and CPFR projects to ensure that demand planning within the category is cost efficient and service effective.

Despite the implementation of an ERP system, management and replenishment of inventory to the right location has been a challenge.

Aras, in his first weeks of this job in overseeing one of the business groups within PackCo, recognised that due to forecast inaccuracies, it would be a big challenge to get the transport planning right. Despite the implementation of an ERP system, due to master data inaccuracies, management and replenishment of inventory to the right location has been a challenge. This has led to the demand planners in his team resorting to using spreadsheets to communicate demand requirements to the providers. Also, the lack of accurate data has resulted in higher inventories and accumulation of aged and obsolete stock.

Aras realised that his supply chain team has constantly exceeded its logistics budget to provide outstanding service levels for customers. Due to lack of clear sales strategy, expedited delivery or special production runs for low-order customers have further reduced the profit margins. For example, one of PackCo’s biggest accounts, Healthy Foods, spends only $2 million a year and, yet the logistics costs incurred servicing this client as a percent of revenue is over 25%.

Aras, prior to his first quarterly C-level management meeting, asked his team to run some analysis for the customer base and its use of 3PL provider services. The results were astonishing:

36.1% of the customer base accounts for 73% of the company’s operating profits.

24.9% of the customer base accounts for approximately USD246 million in losses.

the average DIFOT (deliver in-full and on-time) rate is 99.6% for the customer base.

the average logistics costs as a per cent of revenue across the customers is 16.3%.

there is no long-term contract with any 3PLs. Contracts tend to be 'arms-length' and negotiated with the 3PLs on ad-hoc basis.

68.2% of the outbound deliveries tend to be LTL (less-than-truckload).

special production runs lead to overtime wastage of more than USD $46 million in the last financial year.

Question:

Students are required to prepare a one-page executive summary (no more than 500 words) that describes the problem(s) identified from the case company and to prescribe recommendations to overcome the problems and take following elements in consideration.

1) Identification of key issues and their practical ramifications.

2) Rich recommendations (or recommended solutions).

3) Logical and coherent argument to support recommendations, substantiated, where appropriate, by credible, tested practices and/or well established academic paradigms or perspectives.

4) Indication of limitations or plausible pitfalls arising from implementation of recommendations.

In: Operations Management

Capwell Corporation uses a periodic inventory system. The company's ending inventory on December 31, 2018, its...

Capwell Corporation uses a periodic inventory system. The company's ending inventory on December 31, 2018, its fiscal-year end, based on a physical count, was determined to be $338,000. Capwell's unadjusted trial balance also showed the following account balances: Purchases, $740,000; Accounts payable; $270,000; Accounts receivable, $285,000; Sales revenue, $920,000.

The internal audit department discovered the following items:

Goods valued at $44,000 held on consignment from Dix Company were included in the physical count but not recorded as a purchase.

Purchases from Xavier Corporation were incorrectly recorded at $64,000 instead of the correct amount of $46,000. The correct amount was included in the ending inventory.

Goods that cost $37,000 were shipped from a vendor on December 28, 2018, terms f.o.b. destination. The merchandise arrived on January 3, 2019. The purchase and related accounts payable were recorded in 2018.

One inventory item was incorrectly included in ending inventory as 220 units, instead of the correct amount of 1,600 units. This item cost $50 per unit.

The 2017 balance sheet reported inventory of $472,000. The internal auditors discovered that a mathematical error caused this inventory to be understated by $74,000. This amount is considered to be material. Comparative financial statements will be issued.

Goods shipped to a customer f.o.b. destination on December 25, 2018, were received by the customer on January 4, 2019. The sales price was $52,000 and the merchandise cost $28,000. The sale and corresponding accounts receivable were recorded in 2018.

Goods shipped from a vendor f.o.b. shipping point on December 27, 2018, were received on January 3, 2019. The merchandise cost $30,000. The purchase was not recorded until 2019.

Required:
1. Determine the correct amounts for 2018 ending inventory, purchases, accounts payable, accounts receivable, and sales revenue.
2. Calculate cost of goods sold for 2018.
3. What was the effect of the error in ending inventory on 2017 before-tax income

Determine the correct amounts for 2018 ending inventory, purchases, accounts payable, accounts receivable, sales revenue, and cost of goods sold.


Ending inventory
Purchases
Accounts payable
Accounts receivable
Sales revenue
Cost of goods sold

What was the effect of the error in ending inventory on 2017 before-tax income?

2017 before-tax income was

by

In: Accounting

Currently, the term structure is as follows: One-year bonds yield 8.25%, two-year zero-coupon bonds yield 9.25%,...

Currently, the term structure is as follows: One-year bonds yield 8.25%, two-year zero-coupon bonds yield 9.25%, three-year and longer maturity zero-coupon bonds all yield 10.25%. You are choosing between one, two, and three-year maturity bonds all paying annual coupons of 9.25%. You strongly believe that at year-end the yield curve will be flat at 10.25%.

a. Calculate the one year total rate of return for the three bonds.

b. Which bond would you buy?

In: Finance

Logistic Management Learning Outcomes: Develop a framework for analyzing the logistics function of the firm (Question...

Logistic Management

Learning Outcomes:

Develop a framework for analyzing the logistics function of the firm (Question 1 and 2)

Make decisions related to managing the logistics effort of the firm. (Question 3)

Case Study

NADHEEFCO is a company manufacturing cleaning products serving the grocery retailing market in Europ. NADHEEFCO currently segments its customers based on customer accounts values. The primary division is between national accounts, for which ten accounts constitute 70 per cent of sales by value, and field sales, which comprise a long ‘tail’ of more than 200 accounts that together make up only 30 per cent of sales. Due to the size of the field sales structure, a secondary classification groups accounts by channel type:

Neighbourhood retail, discount and pharmacy. NADHEEFCO recognizes the need to reduce the long customer ‘tail’ and is introducing distributors for orders below a minimum quantity. NADHEEFCO’s current approach to segmentation is summarized in the following Table

National accounts

Field sales

70 percent sales

30 pecent sales,

more than 200 accounts

10 accounts

Neighborhood retail

Discount sector

Pharmacy

Table 1: segmentation approach-current

While Nadheefco currently segments its retail customers by account size, its sales organisation has identified two significant types of buying behaviour displayed by the customer base:

● volume-driven buying behaviour;

● margin-driven buying behaviour.

Volume-driven customers are keen to capitalise on both product and supply chain cost savings in order to pass them on to their customers to drive volume sales. There are two variants of the volume-driven behaviour:

● everyday low price (EDLP);

● discount.

Retailers pursuing an EDLP strategy strive for continuous price reduction from suppliers such as Nadheefco to drive a fairly consistent, high volume of sales. This should result in a relatively stable pattern of demand in the washing and bathing sector. Discounters, on the other hand, are looking for bargains. Because they are aimed to sell products with very low prices compared to the market, which is a strategy more likely to result in a volatile demand pattern.

Margin-driven customers are keen to add value for their customers by offering a wide selection of products and value-adding services. This strategy also results in a relatively stable demand pattern in this sector.

A complicating factor when trying to deconstruct the buying behaviour of Nadheefco’s customers is that several secondary factors are used to support products in the marketplace.

Such factors include product types (e.g. premium, mid, utilitarian), product range (e.g. current products, end of lines, ‘b’ grade), merchandising requirements (e.g. category captains) and promotions strategy (e.g. roll-back, 12-week, 4-week, Hi-Lo). Promotions are by far the most disruptive of these factors. Although the promotions are generally planned well in advance with the retailers, they cause significant disruption to the supply chain operations due to the peaks and troughs in demand that they create.

Furthermore, the deeper the promotional activity the greater the volatility created and the greater the disruption to the supply chain. This has the effect of masking what is fundamentally a fairly stable demand pattern with somewhat artificial volatile demand.

Strategic alignment can only be achieved if the supply chain is aligned behind the segmentation strategy that Nadheefco has adopted. This is not currently the case with the Nadheefco supply chain. Each operation within the supply chain makes decisions or segments its customers based on the functional criteria that affect its part of the supply chain. We have called this lack of alignment ‘matrix twist’, because the matrix of business processes at each stage of the supply chain has been apparently twisted so that the processes fail to fit with each other. As illustrated in Table 2, the decision criteria for Nadheefco and its suppliers and customers change at each stage. This not only complicates material flows, but becomes a minefield if one considers it in terms of behavioral segments.

Management process Supply chain decision Determined by

Source Which supliers? Raw material commodity type

Make Which manufacturing site? product family type

Deliver Which manufacturing order size? Hostorically a function of warehouse?

in process of being dividedby export paperwork requirements and customer account (arbitrary split)

Which customer RDC? Product type and location of store to serve.

Ehich products to which store? Demographics of the stor's catchament area, which drives layout and range decisions.

Questions

What does this case illustrate and What is ‘matrix twist’? (Marks= 4)

Explain the causes of ‘matrix twist between Nadheefco and its retail customers? (Marks= 2)

What actions are needed to straighten out the ‘matrix twist’? (Marks= 2)

In: Economics