Barilla Spa

T. A. PAI MANAGEMENT INSTITUTE

Barilla SpA Case Analysis DTMT Assignment Satrajit Chakraborty PGP: 2 Sec: 2 Roll No: 08247

Case Facts •

Barilla SPA - World’s largest pasta producer

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35% market share in Italy and a 22% market share in Europe

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2 Product Categories – 75% Dry and 25% Fresh

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Dry Products have longer shelf life than Fresh Products

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Vertically Integrated – Plants to Distribution Warehousing

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Distribution System

The distributors such as GD(grand distributor distributor), DO(organized distributor) and BD (i.e. Barilla-run run Depots) receives orders from the supermarkets and shops, and places orders to Barilla CDCs(Central (Central Distribution Centres) who then forward production orders to the factory. A distributor’s warehouse typically held 2 wee weeks ks supply of Barilla products in its inventory. At each level in the supply chain, inventory was reviewed periodically and orders placed with the preceding channel. Lack of customer demand information resulted in buffer stocks at each level, resulting in hhigher levels of inventory ory to meet the desired cycle service level.

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Issues Faced •

Extreme demand fluctuations

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Pressures to manufacturing in terms of production lead-time and perish ability of product

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High Inventory Carrying Cost vs. stock outs resulting in backorders

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Unacceptable Cycle Service Levels (CSL) – inadequate product availability

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Distributors’ inability to carry large number of SKUs

Demand variability exist because long order lead times, lack of information and forecasting ability at the distributors’ end, price and volume discounts and other promotional activities leading to forward buying during discounting period resulting in seasonality in demands and large number of SKUs making demand forecasting complex. This resulted in carrying high finished goods inventory at the factory and also safety inventory at the distributors’ end. Effects were strained manufacturing and logistics operations, trimming retailer/distributor margins, high inventory holding cost adversely affecting profitability. But, even then average weekly stock outs were as high as 5.5% or more, resulting in low order fulfilment rate, accumulation of backorders, poor customer service level. The result is high inventory pile up or stock-outs, a classic case of Bull Whip Effect or demand amplification as one move up the supply chain. Countering the BWE – Decision Taken •

Reduce Uncertainty and Lead Times – through information centralization

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Decision to go for Vendor Managed Inventory – JITD (Just-In-Time Distribution)

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Basis was to focus on customer demand rather than distributor orders

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Distributor to provide data on the shipment and current stock levels for each Barilla SKU

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Decision-making authority will be primarily with Barilla

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Benefits expected out of JITD •

Better demand forecasting using sophisticated tools

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Resulting in better production planning and distribution

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Reduced Inventory Levels and higher profits across the whole supply chain

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Better order fulfilment with reduced stock-outs and backorders

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Making the demand system pull-based from the existing push-based

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Information centralization leading to mitigation of BWE

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Elimination of fixed ordering cost of the distributors

Implementation issues faced •

Increase Distributor’s dependence on Barilla – shift in power towards Barilla

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Thus distributors unwilling to share warehouse data

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Distributor to push competitor products with increased shelf space

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SKU complexity leading to difficulty in proper forecasting

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Inability to run Trade promotions

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Sales and Marketing feared loss of responsibilities

Why JITD should be implemented?

Week

Orders

1 2 3 4 5 6 7 8 9 10 11 12 13

210 100 290 340 480 470 310 505 325 700 285 850 170

Sales

260 320 270 360 250 310 345 390 310 395 260 475 300

Inventory 1150 920 830 700 925 1090 1050 1175 1200 890 900 1270 1120

Forecasted Orders (3 Weeks MA)

Predicted Inventory Level

283 317 293 307 302 348 348 365 322 377

229 372 289 267 217 344 259 411 152 382

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14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 Mean SD

900 300 180 780 95 420 80 160 190 510 180 120 300 290 650 180 75 50 595 350 170 110 310 890 815 210 300 280 360 400 150 300 120 380 20 400 250 290 0 331 230

200 340 220 320 325 290 340 285 250 360 355 295 290 325 320 310 315 310 175 320 265 190 340 300 400 450 400 360 300 215 265 300 305 280 350 265 260 180 275 306 62

1020 700 650 1100 880 1000 740 610 550 700 510 370 380 320 630 500 400 210 620 640 550 490 470 1080 1490 1240 1150 1080 1120 1310 1190 1190 1000 1100 770 900 900 1000 700 855 299

345 325 280 253 293 288 312 318 305 292 298 322 337 313 303 312 318 315 312 267 268 253 258 265 277 347 383 417 403 353 292 260 260 290 295 312 298 292 235 309 39 5

451 291 366 239 274 304 277 339 361 237 249 332 352 294 289 307 309 311 442 252 309 369 224 271 182 202 289 362 409 444 332 266 261 316 251 352 344 417 266 307 69

CV

0.69

0.20

1600

0.35

0.13

0.22

ANALYSIS

1400

QUINTALS

1200 1000 800 600 400 200 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51

WEEKS Orders

Sales

Inventory

Forecasted Orders

Forecasted Inventory

By using simple 3 weeks moving average forecasting, it can be observed that the forecasted orders and forecasted inventory at Cortese Northeast DC has drastically reduced. Also from the table, it can be seen that the Coefficient of Variation (CV) has reduced from 0.69 to 0.13 for orders and from 0.35 to 0.22 for inventory by using this simple demand forecasting. Using more sophisticated techniques like exponential smoothing etcetera, it can be further reduced. Customer demand information flow and accurate forecasting can greatly reduce the BWE in supply chain. Also the SKU complexity can be addressed by 80:20 rule i.e. 20% of the SKUs to be focused for JITD implementation based on their demand. (highest demand items focus)

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How to implement? •

Sell the idea as a collaborative method of working – both the parties are equal partners

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Arranging pilot runs at one or two distributor sites

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Clearly specify the cost-benefit analysis for each distributor

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Explain the importance of marketing efforts in the new JITD model.

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Get top management support in evaluating and implementation of JITD

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