Barilla Case Study: Operational Ineffeciencies

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Case Presentation Barilla SpA

Company & Industry background • World’s largest pasta producer in 1990 • Pasta Share - 35% in Italy and 22% in Europe Channels of Distribution • Products divided in 2 categories – “Fresh” and “Dry” • Fresh Products had 21 day Shelf Lives • Dry Products had Long ( 18 to 24 Months) or Medium(10 to 12 weeks) Shelf Lives • Retail Outlets – Small independent

The Issue
• During the late 1980s, Barilla suffered increasing operational inefficiencies and cost penalties that resulted from large week-to-week variations in its distributors’ order patterns

Distribution Procedure
• Original flow of goods and information
PLANT CDC’s Barilla run depots GD’s Chain supermarkets DO’s Independent supermarkets “Signora Maria” Shops



*CDC = Central Distribution Centre GD = Grand Distributors DO = Organized Distributors

Sales and Marketing
• Advertising – Heavy, Brand Positioned as the Highest Quality • Trade promotions – Frequent • Canvass period, 10 to 12 in a year, typical duration of 4 to 5 weeks • Distributor could buy as much product as desired to meet present and future needs at the offered discount • Volume Discounts also given • Sales representatives used more at DO’s than GD’s – Merchandise Barilla Products – Set up In-Store Promotion – Take note of competitor’s prices, stockouts, new product launches – Work out ordering strategies for the retailer etc

• Demand Fluctuations • Just in Time Distribution

Variability in Demand
• Reasons
– – – – Transportation discounts Volume discount Promotional activity No minimum or maximum order quantities – Product proliferation – Long order lead times – Lack of forecasting systems or sophisticated analytical tools at Distributer’s end

Exhibit 12: Demand Fluctuations

Variability in Demand
• Methods employed to counter variability
– Holding buffer FGs to meet Distributor requirements – Asking Distributors/Retailers to carry additional inventory

• Impact
– Strained Manufacturing and Logistics operations* – Poor Product delivery management – Thinning retailer/distributor margins – Increased Inventory Holding costs – Impossible to anticipate Demand swings – Changing customers due to lack of storage space

Bullwhip effect
• Amplified Variation in demand as one moves up the Supply Chain (away from the order order customer) order Factory Distributor Wholesaler Retailer

Order Variation

The Causes of Bullwhip Effect
• Demand Forecast • Long lead times • Order Batching • Price fluctuation (Promotional sales) • Inflated orders in high estimated demand scenarios

Counteracting the Bullwhip Effect
• Reduce Uncertainty
- POS - Sharing Information - Centralizing demand information

• Reduce Variability
– Year round or Everyday low pricing

• Reduce Lead Times
- Information lead times: EDI - Order lead times: Cross Docking

• Strategic Partnerships
– – – – Quick Response Continuous Replenishment Advanced Continuous Replenishment Vendor managed Inventory (VMI)

Just-In-Time Distribution (JITD)
• Vendor-Managed Inventory Concept • Treats end-customer as the Input • Aims at managing the Input filter that Produces the Orders • Decision-making authority for determining shipments in hands of Barilla SpA • Barilla would monitor the flow of its products through the distributor’s warehouse, and then decide what to ship to the distributor and when to ship it • Distributor provides Data on the shipment and current stock levels for

Expected Benefits of JITD
• Manufacturer
– Reduced manufacturing costs – Better Relationship with Distributors • Increased supply chain visibility • Increase Distributor’s dependence on Barilla

– Improvement in manufacturing planning using objective data – Reduced inventory levels

• Distributors
– Improved fill rates to Retail stores – Additional service without any extra cost – Reduced Inventory Holding costs

JITD - Internal...
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