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.

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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%

Total Expected Profit

88,138

 Exhibit 3