Case: Procter & Gamble’s Supply Chain Redesign

Source – Blending ORIMS, Judgment, and GIS: Restructuring P&G's Supply Chain, by J.D. Camm ,T. Chorman, F. Dill, J. Evans, D. Sweeney, G. Wegryn, Interfaces 27: 1 January-February 1997 (pp. 128-142)

Snapshot of P&G,1990s• Worldwide market leader in laundry detergents,

diapers, feminine protection pads, shampoos, facial moisturizers, acne teen skin care products, and fabric softeners

• 300 brands of consumer goods • Sales in140 countries

• Operating units (plants, divisions, facilities) in 58 countries

• P&G had worldwide sales of $33.5 B in fiscal 1995 and earnings of $2.64 B.

Strengthening Global Effectiveness Initiative• Purposes

– streamline work processes

– drive out non-value-added costs

– eliminate duplication

– rationalize manufacturing and distribution

• Scope at outset– hundreds of suppliers

– over 50 product lines

– 60 plants

– 15 distribution centers

– hundreds of customer zones representing thousands of corporate customers

North American Product Supply Study

• Key part of SGE Initiative• Sought reengineering of

– Product sourcing

– Distribution network

• Principal tools– Business Analytics

– IT

– network optimization models

– geographical information system (GIS)

Five Factors Motivating Supply Chain Redesign

• Deregulation of the trucking industry had lowered transportation costs

• Product compaction (detergents in concentrated form, compact packaging of diapers) more product per truckload

• P&G's focus on TQM improved reliability and increased throughput at every plant

• decrease in product life cycles from 3-5 yr to 18-24 mo required plants to update equipment more frequently

• Corporate acquisitions gave P&G excess capacity

Scope of North American Product Supply Study

• Five Factors motivated update of product sourcing decisions, i.e. choosing best location for production, and scale of operations for each product

• Constraints and trade-offs– scope of production at any particular site is limited to products that

rely on similar technologies

– producing too many products at a site increases the complexity of operations

– large, single-product plants exposes a firm to risk

• Plant locations affect the costs of supplying raw materials and distributing finished products design of the distribution system must be considered

Planning and Organization

• 30 major multifunctional product-strategy teams for developing product sourcing options – aligned with P&G's major business categories: detergents, diapers, etc.

– composed of individuals from various functional areas: finance, manufacturing, distribution, purchasing, R&D, plant operations

– organized around product category groups that shared similar technology and could therefore be produced at the same manufacturing site

• One separate distribution and customer service team charged with developing options for DC locations, assigning customers to DCs, and making transportation decisions

3-8

p1 DC1 c1

50,000

c2

100,000

c3

50,000 candidate distribution centers

customers with demands shown

candidate plants with fixed costs shown

p2 DC2

p3 DC33

1

2

Sourcing Distribution

Business Analytics to the Rescue

• Business Analytics can identify a small set of the most promising alternative designs out of an astronomical number of possibilities– Enables product-strategy teams to collect and analyze

appropriate data in order to generate detailed risk-adjusted cash flows for a reasonable number of scenarios

– More important reason for sound analysis: potential impact of the project on people

• P&G Analytics group partnered with University of Cincinnati's Center for Productivity Improvement

Objectives of Business Analytics Team

• Sourcing: to provide mathematical models and decision support for the product-strategy teams

• Distribution: to provide support to a team of experts in transportation and distribution who were concentrating on warehousing, distribution, and customer allocation problems

• Putting the pieces together: to ensure that the composition of a complete-supply-chain solution across product-strategy and distribution teams was the best possible

Decision Support

• P&G’s legacy system: mainframe-based comprehensive logistics optimization model to support sourcing decisions for multiple product categories and multiple echelons, requiring long turnaround times for each model run

• New Target: simple interactive PC-based tool that would allow product-strategy teams to quickly evaluate options (choices of plant locations and capacities), make revisions, evaluate the new options, employ a GIS, and guide users to better options in an evolutionary fashion

Modeling Strategy

• To decompose the overall supply-chain problem into two easily solved subproblems:

– a distribution-location problem

– a product-sourcing problem for each product category

• Reasoning– Management's organization of the strategic-planning process into a distribution

team and product-category teams implied a natural decomposition across echelons of the supply chain and across product categories.

– Business Analytics team determined that manufacturing and raw-material costs dominated distribution costs by a very large margin, suggesting that product-sourcing decisions were not highly sensitive to the downstream distribution-system design.

– Direct plant-to-customer shipments accounted for the large majority of plant shipments, suggesting that sourcing decisions were more sensitive to customer locations than to DC locations.

Modeling Assumptions

• For each customer zone, the proportion of demand satisfied by direct shipments as well as the proportion satisfied by shipments through DC is a constant for each product category

• DC locations could be chosen independently of the plant locations, due to– relatively small volume (10 to 20 percent) shipped through DCs

– small number of DCs (five to eight) needed to support that volume

– fact that manufacturing costs dwarfed distribution costs

DC - Customer Optimization Model

• Aggregation of trade-customer demand into 150 customer zones, which provided sufficient granularity

• Major considerations on the choice of DC locations

– customer location

– customer services

– sole sourcing

– proximity to customer zones to maintain current levels of customer service

• Employed uncapacitated facility-location model to find optimal DC locations and to assign customers to DCs. For a fixed number of DCs, the model finds optimal locations, while ensuring that each customer zone is assigned to a single DC. The objective is to minimize the cost of all DC-customer zone assignments.

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DC - Customer Optimization ModelDC - Customer Optimization Model

Min CijXij

i Xij =1, j J

i Yi = k

Xij Yi, i I, j J

Xij = 1 if customer j assigned to DC i

Yi = 1 if DC i is chosen

Mixed Integer Linear Program

Product Sourcing Model

• Transportation model for each product category: product-strategy teams specify the plant location and capacity options to be evaluated

• Arc costs are the sum of manufacturing, warehousing at the plant, and transportation costs. – Manufacturing costs were the most important consideration in the

product-sourcing decision, so team made careful estimates.

– DC costs were composed of actual per-unit storage and handling costs at each of the company's existing DCs, and appropriate estimates at new DC locations

– Transportation costs estimates were based on• negotiated rates P&G was already paying for shipments between locations,

along with rate tables; or

• Fixed cost per linear function of distance between 2 points

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Product Sourcing ModelProduct Sourcing Model

Min CijXij

j Xij = ai, i I

i Xij =dj, j J

Xij 0, i I, j J

Xij = shipment from plant i to DC j

Linear Program

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Integration with GIS

• Used to display results of optimizations and manipulate data through a menu-driven system for sensitivity analysis and further model runs and evaluation

• Advantages– easy to understand - visualization provides insight

– query details by point-and-click

– facilitates acceptance of analytical techniques

– highlighted database errors

19

20

Solution Composition and VerificationSolution Composition and Verification

DC Location and Customer

Assignment

Option Generation

Option Selection

Verification

Distribution Team: Facility Location Model

30 Sourcing Teams: Product Sourcing Model and

@RISK NPV Model

Steering Team: Logistics Modeling System

Project Results & Benefits

• Integrated solution called for plant consolidations: by mid-1996, P&G had closed 12 sites and written off over a billion dollars worth of assets and people transition costs

• Over 6,000 people impacted, but treated fairly through early retirement, relocation, or retraining and placement

• As of 1997, annual savings were well over $250 million (before tax) – largest portion is due to lower manufacturing expenses, operating fewer plants

with less staff

– some savings in packing materials and ingredients

– …but with fewer DCs delivery expenses actually increased

• Securities and Exchange Commission closely monitored and verified the savings