### Final Grade & Feedback
Q1: 15/15
Q2: 15/15
Q3: 15/15
Q4: 10/15 [No quantitative example provided]
Q5: 10/10
Bonus: 0/10 [Only censoring mentioned, no distribution assumption]
**Total: 65/80**
---
Yedioth CASE: Study Team S2 Section A:
S.H Jo
(Seonghoon Jo)
Christalyn Rhodes
Bernard O’bien
Estefania Guevara Diaz
Yoav Gour-Lavie
Question 1 – Recommended shipment quantities
(99 % service)
Methodology: For each retailer we calculated the sample mean (μi , i : retailer #1
through 50) and standard deviation (σi ) of weekly sales from the experimental data.
Assuming weekly demand is normally distributed, the shipment quantity needed to
achieve a 99 % in‑stock probability is
Σ [ Qi * = μi +z0 .99 x σi ] ,
where the 99th percentile of the standard normal distribution is z~0.99=2.32, where k=2.32.
Because fractional magazines are not feasible, we rounded Qi up to the nearest integer.
The expected returns for each retailer are Qi −μi . Appendix A lists the recommended
quantities for all 50 retailers.
Total production and returns under the current policy: Summing the recommended
shipments across retailers yields a total weekly production of 419 copies. (See
Appendix A for recommended quantities to the 50 retailers)
The total expected weekly demand is = 228 copies, implying expected returns of = 191
copies (we rounded the μ values for each as described in Appendix A.)
Question 2 – Benefit of full pooling
Under full pooling the 50 retailers share a common inventory pool and are replenished
in real time. We aggregated weekly demand across all retailers; the aggregated mean
and standard deviation are =190 and = 20 copies respectively. (See Appendix B)
Using the same 99 % service formula gives a pooled order‑up‑to level of = 236 copies
per week. Expected demand remains 190 copies, so expected returns drop to = 46
copies per week.
The benefit of full pooling relative to the current independent shipments (419
copies produced, 191 returned), full pooling reduces production by =183 copies (44%) and returns by = 145 copies (-76%) per week.
Question 3 – Pooling by sales agent
Pooling inventory only among retailers served by the same sales agent (five retailers
per agent) offers a more modest risk‑pooling benefit. Aggregating weekly sales for each
agent and applying the 99 % service formula yields a total weekly production of = 293
copies and expected returns of = 99 copies. (See Appendix C)
Compared with the independent policy, this represents savings of = 126 copies in
production and = 24 copies in returns. However, relative to full pooling, per‑agent
pooling requires about 57 extra copies and results in 5 additional returns per week.
Q1
Q2
Q3
No pooling
Full Pooling
Pooling only
among retailers
SVC LVL 99%
419
236
293
RTN
191
46
99
Question 4 – Leveraging the mid‑week visit
First, we would like to suggest a mid-week replenishment based on observed sales. We
propose a two-step supply process: in addition to the usual Wednesday visit, introduce
a Sunday visit as follows: On Sunday, replenish 70% of the forecasted demand, and on
Wednesday, make the final adjustment. We believe this approach will reduce both
overstocking and returns due to a more dynamic relationship with the retailers.
Additionally, this maintains a high level of service since we are using existing visits, so
no extra costs are incurred. More visits make less standard deviation, which means less
safety stock and less inventory, and a return.
The second idea is to use a mobile app, accessible from any cellphone, specifically
designed for retailers and linked directly with their agents. This would facilitate direct
communication between retailers and agents. From the agents’ and company’s
perspective, it provides an opportunity to have a centralized system. The main benefit is
access to real-time information to identify which magazines are selling faster, which
have lower demand, and to improve demand forecasting. Given the high penetration of
cellphones in the population, an app is a low-cost and effective tool.
Finally, our last suggestion is based on incentives for the retailers. We propose creating
a compensation system based on total units sold as a percentage of sales, with an
additional bonus for accurate demand forecasting of magazines. This approach would
align not only the retailers but also the agents with the company’s goals to increase
sales and reduce returns. It would also encourage both retailers and agents to make
better decisions regarding distribution.
Question 5 – organizational challenges
Implementing pooling or dynamic replenishment raises several organizational issues:
•
Analytical and IT capability: Most small retailers lack systems for real-time
data sharing. Capturing first‑half‑week sales data and coordinating mid‑week
replenishments requires new IT infrastructure and demand forecasting tools.
• Sales‑agent incentives: Sales agents are compensated based on volume, not
efficiency on sales and may resist smaller shipments. Incentive schemes must
reward sell‑through rather than shipments.
• Operational complexity: Mid‑week replenishments add routing complexity and
may require additional vehicles or time. Centralized pooling also requires a
system for prioritizing retailers when inventory is scarce.
• Cultural resistance: Yedioth’s conservative, family-owned culture may resist
operational changes. Long-standing loyalty to employees could slow down
restructuring. Given their loyalty to the employees and the tradition of
over‑production there may cause resistance to change that reduce printed
volumes.
Appendix A
Retailer
Average of StdDev of
Sales
Sales
μ
Kxσ
Q
(μ + K x σ)
Q* (Rounded)
recommended
Quantities to
each Retailer
Return
(Q*- μ_rounded)
1
4.27
1.76
4.27
4.09
8.36
9.00
4.00
2
5.45
1.94
5.45
4.50
9.95
10.00
4.00
3
1.61
0.74
1.61
1.73
3.34
4.00
2.00
4
1.80
1.19
1.80
2.75
4.55
5.00
3.00
5
3.09
1.46
3.09
3.38
6.47
7.00
3.00
6
3.61
1.73
3.61
4.02
7.63
8.00
4.00
7
3.93
1.60
3.93
3.72
7.65
8.00
4.00
8
14.43
3.91
14.43
9.08
23.51
24.00
9.00
9
4.73
1.62
4.73
3.75
8.48
9.00
4.00
10
3.17
1.37
3.17
3.18
6.36
7.00
3.00
11
4.00
1.86
4.00
4.32
8.32
9.00
5.00
12
4.07
1.01
4.07
2.34
6.41
7.00
2.00
13
2.24
1.11
2.24
2.58
4.82
5.00
2.00
14
2.46
1.13
2.46
2.62
5.08
6.00
3.00
15
4.56
1.58
4.56
3.67
8.23
9.00
4.00
16
6.52
2.01
6.52
4.66
11.18
12.00
5.00
17
4.78
1.70
4.78
3.94
8.72
9.00
4.00
18
1.86
0.80
1.86
1.87
3.73
4.00
2.00
19
5.85
1.76
5.85
4.09
9.94
10.00
4.00
20
3.25
1.74
3.25
4.04
7.29
8.00
4.00
21
2.78
1.01
2.78
2.34
5.12
6.00
3.00
22
4.20
2.15
4.20
4.98
9.17
10.00
5.00
23
5.14
2.10
5.14
4.87
10.00
11.00
5.00
24
1.57
1.15
1.57
2.66
4.23
5.00
3.00
25
8.74
2.39
8.74
5.54
14.28
15.00
6.00
26
3.15
1.48
3.15
3.42
6.57
7.00
3.00
27
2.16
1.70
2.16
3.95
6.11
7.00
4.00
28
6.65
3.11
6.65
7.21
13.86
14.00
7.00
29
1.94
1.26
1.94
2.92
4.86
5.00
3.00
30
8.00
2.68
8.00
6.23
14.23
15.00
7.00
31
4.80
1.94
4.80
4.50
9.30
10.00
5.00
32
2.59
1.24
2.59
2.88
5.46
6.00
3.00
33
3.67
1.61
3.67
3.73
7.40
8.00
4.00
34
2.22
1.30
2.22
3.01
5.23
6.00
3.00
35
3.95
1.66
3.95
3.85
7.81
8.00
4.00
36
2.67
1.55
2.67
3.60
6.27
7.00
4.00
37
3.61
1.58
3.61
3.68
7.28
8.00
4.00
38
3.40
1.08
3.40
2.51
5.92
6.00
2.00
39
3.04
1.41
3.04
3.28
6.32
7.00
3.00
40
9.07
2.51
9.07
5.82
14.88
15.00
5.00
41
3.70
1.47
3.70
3.42
7.11
8.00
4.00
42
3.74
2.09
3.74
4.86
8.59
9.00
5.00
43
3.07
1.47
3.07
3.40
6.47
7.00
3.00
44
3.38
0.92
3.38
2.13
5.50
6.00
2.00
45
1.48
0.94
1.48
2.17
3.65
4.00
2.00
46
6.35
1.92
6.35
4.46
10.81
11.00
4.00
47
5.51
2.03
5.51
4.70
10.21
11.00
5.00
48
1.43
1.07
1.43
2.47
3.90
4.00
2.00
49
2.93
1.27
2.93
2.94
5.87
6.00
3.00
50
4.00
1.22
4.00
2.84
6.84
7.00
3.00
419.00
191.00
Grand Total
Appendix B
# 0f Week
Sum of Sales
Variance
1
208
339.04
2
180
91.91
3
197
54.95
4
185
21.04
5
186
12.87
6
232
1798.87
7
207
303.21
8
206
269.39
9
165
604.52
10
192
5.82
11
201
130.26
12
208
339.04
13
177
158.43
14
179
112.08
15
188
2.52
16
183
43.39
17
170
383.65
18
143
2170.34
19
173
275.13
20
238
2343.82
21
216
697.65
22
198
70.78
23
175
212.78
24
172
309.30
25
158
997.74
26
189
0.34
27
193
11.65
28
181
73.74
29
195
29.30
30
192
5.82
31
215
645.82
32
199
88.61
33
181
73.74
34
242
2747.13
35
184
31.21
36
189
0.34
37
184
31.21
38
198
70.78
39
181
73.74
40
184
31.21
41
148
1729.47
42
184
31.21
43
171
345.47
44
181
73.74
45
201
130.26
46
192
5.82
Total
8,721
17,979.2
ㅇ AVG (μ value): 8721 / 46 = 189.59 = 190
ㅇ STD (σ value) : SQRT (17,979 / 46) = 19.77 = 20
Appendix C