7. Supply Chain Management (SCM)

Supply Chain Management  Integration of the activities that procure materials and services, transform them into intermediate goods and the final product, and deliver them to customers  Competition is no longer between companies; it is between supply chains

A Sample Supply Chain

Supply Chain Strategies  Negotiating with many suppliers  Long term partnering with few suppliers  Vertical integration  Keiretsu (affiliated chain)

Many Suppliers  Commonly used for commodity products – many sources per item  Adversarial short term relationship  Infrequent large lots  Purchasing is typically based on price - suppliers are pitted against one another

Few Suppliers  Longer term stable relationships  Partnership - JIT programs, design and technological contribution  High quality and possibly low price  Frequent small lots  Cost of changing suppliers is huge

Vertical Integration  Ability to produce goods or service previously purchased – make or buy decisions  Integration may be forward, towards the customer, or backward, towards suppliers  Can improve cost, quality, and inventory but requires major financial commitment  Hard to do all things well

Vertical Integration Raw material (suppliers) Iron oreSiliconFarming Backward integration Steel Current transformation AutomobilesIntegrated circuitsFlour milling Forward integration Distribution systems Circuit boards Finished goods (customers) Dealers Computers Watches Calculators Baked goods Vertical IntegrationExamples of Vertical Integration

Keiretsu Networks (affiliated chain)  A middle ground between few suppliers and vertical integration  Supplier becomes part of the company coalition  Often provide financial support for suppliers through ownership or loans  Members expect long-term relationships and provide technical expertise and stable deliveries  May extend through several levels of the supply chain

Make or Buy Decisions 1.Lower production cost 2.Obtain desired quality 3.Assure adequate supply (quantity or delivery) 4.Utilize surplus labor or facilities 5.Protect proprietary design or quality 6.Increase or maintain size of company Reasons for Making

Make – or – Buy Decisions 1.Frees management to deal with its primary business 2.Inadequate capacity 3.Reduce inventory costs 4.Ensure alternative sources 5.Inadequate managerial or technical resources 6.Item is protected by a patent or trade secret Reasons for Buying

Issues in SCM  Local optimization - focusing on local profit or cost minimization based on limited knowledge  Incentives (sales incentives, quantity discounts, quotas, and promotions) - push merchandise prior to sale  Large lots - low unit cost but do not reflect sales  Bullwhip effect - stable demand becomes lumpy orders through the supply chain

Opportunities in SCM  Accurate “pull” data  Lot size reduction  Single stage control of replenishment  Vendor managed inventory  Standardization  Electronic ordering and funds transfer

Example

Vendor Evaluation CriteriaWeights Scores (1-5) Weight x Score Engineering/research Production/process capability Distribution/delivery capability Quality systems and performance Facilities/location Financial and managerial strength (stability and cost structure) Information systems (ERP) Integrity (compliance/ethics) Total

Supply Chain Performance  Inventory Investment =Total Inventory / Total Assets * 100  Example: Inventory: $11.4 billion, Assets: $44.4 billion Inventory investment = 11.4/44/4*100 = 25.7% Manufacturing 20% (Toyota 5%) Wholesale 34% (Coca-Cola 2.9%) Restaurants 2.9% (McDonald’s.05%) Retail 27% (Home Depot 25.7%)

Supply Chain Performance  Inventory Turnover =Cost of Goods Sold / Total Inventory  Example: Inventory Turnover = 14.2 / 1.69 = 8.4 Net revenue$32.5 Cost of goods sold$14.2 Inventory: Raw material inventory$.74 Work-in-process inventory$.11 Finished goods inventory$.84 Total inventory investment$1.69

Supply Chain Performance Examples of Annual Inventory Turnover Food, Beverage, RetailManufacturing Anheuser Busch15Dell Computer90 Coca-Cola14Johnson Controls22 Home Depot5Toyota (overall)13 McDonald’s112Nissan (assembly)150

Network Design in a Supply Chain  Facility location  Capacity allocation  Market and supply allocation

Customer DC One week order response time - 1 Distribution Center

Customer DC 5 day order response time - 2 Distribution Centers

Customer DC 3 day order response time - 5 Distribution Centers

Customer DC Next day order response time - 13 Distribution Centers

Customer DC Same day order response time - 26 Distribution Centers

Cost vs. Number Percent Service Level Within Promised Time Transportation Cost of Operations Number of Facilities Inventory Facilities Total Costs Labor

Conventional Network CustomerStore MaterialsDC Component Manufacturin g VendorDC Final Assembly Finished Goods DC ComponentsDC VendorDC PlantWarehouse Finished CustomerDC CustomerDC CustomerDC CustomerStore CustomerStore CustomerStore CustomerStore VendorDC

Tailored Network RegionalFinished Goods DC RegionalFinished Customer 1 DC Store 1 NationalFinished Goods DC Local DC Cross-Dock Cross-Dock Cross-Dock Customer 2 DC Store 1 Store 2 Store 3

Network/Location Decisions  Long-term decisions  Decisions made infrequently  Decision greatly affects both fixed and variable costs  Once committed to a location, many resource and cost issues are difficult to change

Critical Factors to Consider  Proximity to raw materials and customers  Labor, availability, costs  Land/construction costs  Government incentives and fiscal policies  Corporate desires  Environmental regulations

Methods of Evaluating Locations  Factor Rating Method  Locational Break-Even Analysis  Center of Gravity Method  Transportation Method

Factor Rating method  Most widely used location technique 1. Develop a list of relevant factors 2. Assign a weight to each factor 3. Score each location for each factor 4. Multiply score by weights for each factor for each location

Example CriticalScores Success(out of 100)Weighted Scores FactorWeightFranceDenmarkFranceDenmark Labor availability and attitude (.25)(70) = 17.5(.25)(60) = 15.0 People-to car ratio (.05)(50) = 2.5(.05)(60) = 3.0 Per capita income (.10)(85) = 8.5(.10)(80) = 8.0 Tax structure (.39)(75) = 29.3(.39)(70) = 27.3 Education and health (.21)(60) = 12.6(.21)(70) = 14.7 Totals

Locational Break Even Analysis  Method of cost-volume analysis used for industrial locations 1. Determine fixed and variable costs for each location 2. Plot the cost for each location 3. Select location with lowest total cost for expected production volume

Example Akron$30,000$75$180,000 Bowling Green$60,000$45$150,000 Chicago$110,000$25$160,000 Selling price = $120 Expected volume = 2,000 units FixedVariableTotal CityCostCostCost

Example – $180,000 $180,000 – – $160,000 $160,000 – $150,000 $150,000 – – $130,000 $130,000 – – $110,000 $110,000 – – $80,000 $80,000 – – $60,000 $60,000 – – $30,000 $30,000 – – $10,000 $10,000 – – Annual cost ||||||| 05001,0001,5002,0002,5003,000 Volume Akron lowest cost Bowling Green lowest cost Chicago lowest cost Chicago cost curve Akron cost curve Bowling Green cost curve

Center of Gravity Method  Find location of distribution center that minimizes distribution costs  Consider location of markets, volume of goods shipped to those markets, and shipping cost (or distance) 1. Place existing locations on a coordinate grid 2. Calculate X and Y coordinates for ‘center of gravity’

Center of Gravity Method x - coordinate = ∑d ix Q i / ∑Q i Computation of center y - coordinate = ∑d iy Q i / ∑Q i Evaluation of potential locations

ExampleNorth-SouthEast-West – – – – – |||||| Arbitrary origin Chicago (30, 120) New York (130, 130) Pittsburgh (90, 110) Atlanta (60, 40)

Example Number of Containers Store LocationShipped per Month Chicago (30, 120)2,000 Pittsburgh (90, 110)1,000 New York (130, 130)1,000 Atlanta (60, 40)2,000 x-coordinate = (30)(2000) + (90)(1000) + (130)(1000) + (60)(2000) = 66.7 y-coordinate = (120)(2000) + (110)(1000) + (130)(1000) + (40)(2000) = 93.3

ExampleNorth-SouthEast-West – – – – – |||||| Arbitrary origin Chicago (30, 120) New York (130, 130) Pittsburgh (90, 110) Atlanta (60, 40) Center of gravity (66.7, 93.3) +

Transportation Model  Find amount to be shipped from several points of supply to several points of demand  Solution will minimize total production and shipping costs

Transportation Model

Location Strategy Service/Retail/Professional Location Goods-Producing Location Revenue Focus Cost Focus Volume/revenue Drawing area; purchasing power Competition; advertising/pricing Physical quality Parking/access; security/lighting; appearance/image Cost determinants Rent Management caliber Operations policies (hours, wage rates) Tangible costs Transportation cost of raw material Shipment cost of finished goods Energy and utility cost; labor; raw material; taxes, and so on Intangible and future costs Attitude toward union Quality of life Education expenditures by state Quality of state and local government

Location Strategy Service/Retail/Professional Location Goods-Producing Location Techniques Regression models to determine importance of various factors Factor-rating method Traffic counts Demographic analysis of drawing area Purchasing power analysis of area Center-of-gravity method Geographic information systems Transportation methods Factor-rating method Locational break-even analysis Crossover charts

Location Strategy Service/Retail/Professional Location Goods-Producing Location Assumptions Location is a major determinant of revenue High customer-contact issues are critical Costs are relatively constant for a given area; therefore, the revenue function is critical Location is a major determinant of cost Most major costs can be identified explicitly for each site Low customer contact allows focus on the identifiable costs Intangible costs can be evaluated

Video Case Study

Beer Game  Was the game realistic?  Did you blame your customers or vendors?  Who is responsible for the performance?  Why not ship them directly from the factory to the retailer?  What was the real demand?  Why are there big fluctuations?  Can we use some inventory policies?