Forecasting And Procurement At Le Club Fran Ais Du Vin Finance Essay
Le Club Français du Vin is founded in 1973 and had grown to a 10 million Euro per year business in 2004. The mission of Le Club is to offer wines of good to very good quality to its customers in France, Switzerland, and Germany, who receive interesting wines delivered directly to their homes. Every member of Le Club receives an offer of wine every two months via a catalog.
Le Club Français du Vin largely carries French wines. The heterogeneity of French wines makes forecasting consumer demand for particular French wine extremely difficult. At Le Club Français du Vin, a group of professional wine experts create a sales forecast for each wine in the upcoming catalog taking into account both taste considerations and the season of the year in which the wine is offered in the catalog.
Once the forecasting process is over, Le Club places an order with the wine grower, which happens months before publishing the catalog and at a point when little information beyond the wine experts’ personal opinions is available. The Club pays the wine grower 75 days after having received the shipment. If the wine forecast equals the actual demand or comes close to it these payment conditions are very favorable for Le Club. However, such desirable cash flows are not always the case. If Le Club has over forecasted sales for the catalog season, excess bottles are stored in the warehouse and are likely to be discounted in a future catalog (white wines are discounted by 40% of their retail price, and red wines – by 30%). There is also an additional handling and shipping cost for discounted bottles of 1.25 Euro per bottle, and 0.10 Euro warehouse operational costs per bottle.
The main problem of the company is the mismatch between forecasts and actual customer demand, which results in either excess inventory or unsatisfied customers. For example, the Club had ordered 10,000 bottles of the 2002 St Emilion wine for the company’s January 2004 catalog, but only sold 1,704 bottles. On the other side, the Club forecasted to sell 10,000 bottles of the Côtes du Rhône, but actually experienced a demand of over 11,000 bottles. The Club currently holds over 200,000 bottles of wine in its warehouse.
The company has to choose between few options in order to decide how many bottles of each wine to order – to maximize expected profit, to generate a certain fill-rate or to achieve a certain in-stock probability.
If the manager chooses as an objective to maximize the expected profit, as seen in Exhibit 1, the total expected profit is supposed to be 147,998 Euro. However, the profit-maximizing order quantity may generate some unacceptable fill rate and in-stock probability from the firm’s customer service prospective. The fill rate varies in the range of 50% to 100%, while the stockout probability varies in the range of 0% to 83%. This scenario will result in a lot of unsatisfied customers who might choose a different supplier in the future.
The customers of the Club place their order by mail, phone, fax, or over the internet. If the customers place their order by phone or online they can be informed right away if a particular wine is out of stock. However, as a large portion of Le Club’s customers are in their 60s, orders by mail are most common, and these customers are unaware of the availability of the wine there are ordering. It is very rare for the company to be able to place additional orders for wines that have been under forecasted. As a result all demand for a wine that remains unfulfilled is lost. Given the complications associated with stock-outs, Le Club aims at high availability for its wines throughout the catalog season. That is the reason why the first scenario is not suitable for the company.
Let us assume that the company chooses to guarantee a fill rate of 99%, which means that 99% of the demand will be satisfied. As seen in Exhibit 2, the total expected profit is 102,382 , which is about 45, 000 euro less than the profit it generates in the first scenario, however, the in -stock probability is 94.74%. This is a better scenario for the Club, because it is going to guarantee that most of the customers during the season can be satisfied, and there is also a great probability that the customer’s demand can be satisfied even at the end of the season. The fill rate is a good measure of average customer service because it treats each customer as equally important. So, even though the company might experience some profit loss for certain types of wine, the total expected profit is 102,382 Euro, and along with that the Club can also achieve high levels of fill rate and in-stock probability.
The third option for the club is to choose to set as its primary goal to achieve a high in-stock probability (let us assume 97.5% rate). As seen in Exhibit 3, in this case the total expected profit is only 88,138 Euro, which is almost half of the expected profit in the first scenario. The fill rate is 99.57%. We see that achieving a very high in-stock probability can be quite expensive and sets the company at a much lower profit level. This scenario is also unacceptable for the company.
The company has to constantly try to balance the cash constraints inherent in holding large inventory positions with the goal of sustaining healthy margins (the club typically enjoys around 50%) while ensuring availability of a broad selection of wines even late in a catalog season. Therefore the club needs to make tradeoff – to give up some of its profit in order to obtain higher fill rate and in-stock probability in order to ensure better customer service and to keep its positions in the market. The second scenario seems the most optimistic and optimal for the company – it will lose some of its profit, but on the other side will guarantee a greater customer satisfaction, which is very important for the Club that capitalizes on a niche market.
Appellation
Q that maximizes expected profit
Expected profit
Fill Rate
Stockout probability
FAUGERES
12022
16235
88.47%
36.58%
GRAVES
803
1847
91.12%
30.32%
GRAVES
1149
2076
93.58%
23.77%
PESSAC LEOGNAN
3241
11721
100.00%
0.00%
CARTON PANACHE 6+2+4
5093
12880
99.38%
3.40%
BORDEAUX CLAIRET
3461
3286
81.65%
50.00%
CÔTES DE BOURG
1352
1985
90.00%
33.05%
ENTRE DEUX MERS
1129
940
74.41%
61.14%
BORDEAUX
4535
3063
74.63%
60.84%
CARTON PANACHE
5493
5993
84.41%
44.98%
Bordeaux
2127
1332
73.05%
62.96%
VDP des Côteaux de L’Ardèche
1651
344
50.59%
83.87%
VDP des Côteaux de L’Ardèche
1412
318
52.08%
82.91%
VDP du Comté Tolosan
1041
227
48.72%
85.02%
CARTON PANACHEE
1692
547
59.22%
77.54%
CABERNET D’ANJOU
2630
2581
82.31%
48.84%
SANCERRE
2092
6068
93.93%
22.76%
CHINON
4071
4315
83.84%
46.05%
ALOXE CORTON
2992
13549
100.00%
0.00%
BOURGOGNE ALIGOTE
1013
1505
84.68%
44.44%
GIVRY
1734
4028
99.95%
0.38%
COTEAUX DU LYONNAIS
2543
2293
80.61%
51.78%
CDR Vill RASTEAU
1075
2084
94.73%
20.40%
GIGONDAS
2493
5225
100.00%
0.00%
CÔTES DU VENTOUX
1052
1032
82.31%
48.84%
CARTON PANACHE
3742
7788
95.87%
16.85%
CORBIERES (6)
1155
1169
82.94%
47.71%
GAILLAC
2248
2347
83.54%
46.60%
MINERVOIS
3322
2847
79.57%
53.48%
MADIRAN
14445
28372
94.95%
19.75%
Total Expected Profit
147,998
Exhibit 1
Appellation
Q that guarantees fill rate of 99%
Expected sales
Expected leftover inventory2
Expected profit (fill rate = 99%)
In-stock probability
FAUGERES
18121
10280
7841
12379
94.74%
GRAVES
1133
642
490
1588
94.74%
GRAVES
1510
857
653
1926
94.74%
PESSAC LEOGNAN
1963
1114
849
10134
94.74%
CARTON PANACHE 6+2+4
4832
2741
2091
12871
94.74%
BORDEAUX CLAIRET
6040
3427
2614
1219
94.74%
CÔTES DE BOURG
1963
1114
849
1632
94.74%
ENTRE DEUX MERS
2265
1285
980
-341
94.74%
BORDEAUX
9060
5140
3920
-1022
94.74%
CARTON PANACHE
9060
5140
3920
3338
94.74%
Bordeaux
4379
2484
1895
-737
94.74%
VDP des Côteaux de L’Ardèche
5285
2998
2287
-3335
94.74%
VDP des Côteaux de L’Ardèche
4379
2484
1895
-2682
94.74%
VDP du Comté Tolosan
3473
1970
1503
-2623
94.74%
CARTON PANACHEE
4530
2570
1960
-2289
94.74%
CABERNET D’ANJOU
4530
2570
1960
1082
94.74%
SANCERRE
2718
1542
1176
5678
94.74%
CHINON
6795
3855
2940
2252
94.74%
ALOXE CORTON
1812
1028
784
11367
94.74%
BOURGOGNE ALIGOTE
1661
942
719
863
94.74%
GIVRY
1359
771
588
3997
94.74%
COTEAUX DU LYONNAIS
4530
2570
1960
663
94.74%
CDR Vill RASTEAU
1359
771
588
1985
94.74%
GIGONDAS
1510
857
653
5001
94.74%
CÔTES DU VENTOUX
1812
1028
784
433
94.74%
CARTON PANACHE
4530
2570
1960
7572
94.74%
CORBIERES (6)
1963
1114
849
542
94.74%
GAILLAC
3775
2142
1634
1181
94.74%
MINERVOIS
6040
3427
2614
571
94.74%
MADIRAN
18121
10280
7841
27136
94.74%
Total Expected Profit
102,382
Exhibit 2
Appellation
Q that guarantees In-stock probability = 97.5%
Expected profit(in-stock probability = 97.5)
Expected fill rate
FAUGERES
19745
10565
99.57%
GRAVES
1234
1444
99.57%
GRAVES
1645
1820
99.57%
PESSAC LEOGNAN
2139
10387
99.57%
CARTON PANACHE 6+2+4
5265
12876
99.57%
BORDEAUX CLAIRET
6582
466
99.57%
CÔTES DE BOURG
2139
1450
99.57%
ENTRE DEUX MERS
2468
-739
99.57%
BORDEAUX
9872
-2297
99.57%
CARTON PANACHE
9872
2286
99.57%
Bordeaux
4772
-1366
99.57%
VDP des Côteaux de L’Ardèche
5759
-4219
99.57%
VDP des Côteaux de L’Ardèche
4772
-3410
99.57%
VDP du Comté Tolosan
3784
-3300
99.57%
CARTON PANACHEE
4936
-3017
99.57%
CABERNET D’ANJOU
4936
526
99.57%
SANCERRE
2962
5391
99.57%
CHINON
7404
1450
99.57%
ALOXE CORTON
1974
11703
99.57%
BOURGOGNE ALIGOTE
1810
606
99.57%
GIVRY
1481
4018
99.57%
COTEAUX DU LYONNAIS
4936
85
99.57%
CDR Vill RASTEAU
1481
1903
99.57%
GIGONDAS
1645
5052
99.57%
CÔTES DU VENTOUX
1974
210
99.57%
CARTON PANACHE
4936
7347
99.57%
CORBIERES (6)
2139
304
99.57%
GAILLAC
4113
732
99.57%
MINERVOIS
6582
-215
99.57%
MADIRAN
19745
26076
99.57%