Product Availability

Level of product availability Also referred as customer service level. Is measured using the cycle service level or fill rate. Is high to improve the responsiveness and attract customers. But high level requires large inventories. These large inventories tend to raise cost for SC. Therefore, SC needs to balance between level of inventory and cost of inventory.

Factors affecting optimal level of product availability Before understanding factors consider one example of a storekeeper who sells jacket. He buys the stock for entire season’s supply of jacket before start of selling season. High level of product availability requires large number of jackets. It is likely to satisfy all demands. However, it results in a large number of unsold jackets at the end of season.

Example… On the other hand, low level of product availability results in few unsold jackets. In this scenario, a loss of potential customers has to bear. Must balance the loss from having too many unsold jackets and lost profit from turning away customers.

Mattel, Inc. & Toys ‘R Us Mattel was hurt last year by inventory cutbacks at Toys ‘R Us, and officials are also eager to avoid a repeat of the 1998 Thanksgiving weekend. Mattel had expected to ship a lot of merchandise after the weekend, but retailers, wary of excess inventory, stopped ordering from Mattel. That led the company to report a $500 million sales shortfall in the last weeks of the year ... For the crucial holiday selling season this year, Mattel said it will require retailers to place their full orders before Thanksgiving. And, for the first time, the company will no longer take reorders in December, Ms. Barad said. This will enable Mattel to tailor production more closely to demand and avoid building inventory for orders that don't come. - Wall Street Journal, Feb. 18, 1999

Key Questions How much should Toys ‘R Us order given demand uncertainty? How much should Mattel order? Will Mattel’s action help or hurt profitability? What actions can improve supply chain profitability?

Importance of the Level of Product Availability Product availability measured by cycle service level or fill rate Also referred to as the customer service level Product availability affects supply chain responsiveness Trade-off: High levels of product availability  increased responsiveness and higher revenues High levels of product availability  increased inventory levels and higher costs Product availability is related to profit objectives, and strategic and competitive issues (e.g., Nordstrom, power plants, supermarkets, e- commerce retailers) What is the level of fill rate or cycle service level that will result in maximum supply chain profits?

Factors Affecting the Optimal Level of Product Availability Cost of overstocking Cost of understocking Possible scenarios Seasonal items with a single order in a season One-time orders in the presence of quantity discounts Continuously stocked items Demand during stockout is backlogged Demand during stockout is lost

Cost of overstocking = C0 of understocking = Cu Is the loss incurred by a firm for each unsold unit at the end of selling season. of understocking = Cu Is the margin lost by a firm for each lost sale from current and future sales if customer does not return. Two factors that affect optimal level of product availability. Cost of overstocking Cost of understocking

Optimal level of product availability Makes sense in the context of demand uncertainty. Firms have forecast a consensus estimate of demand without any measure of uncertainty. Now they have better appreciation for uncertainty. Incorporation of uncertainty and optimal level of product availability can increase profit.

Example Demand distribution for jackets Demand Di (*100) Probability Cumulative probability of demand being Di or less probability of demand being greater then Di 4 0.01 0.99 5 0.02 0.03 0.97 6 0.04 0.07 0.93 7 0.08 0.15 0.85 8 0.09 0.24 0.76 9 0.11 0.35 0.65 10 0.16 0.51 0.49 11 0.20 0.71 0.29 12 0.82 0.18 13 0. 10 0.92 14 0.96 15 0.98 16 17 1.00 0.00

Example Expected profit from ordering a thousands of jacket =$49,900 Potential outcome to buy 100 more jackets If extra 100 are sold, then profit=$5,500 If 100 units are send to outlet, then loss=$500 From table, there is 0.49 probability that demand is 1100 or higher and a 0.51 probability that demand will be 1000 or less. Expected profit=$5,500Xprob[Demand≥1,100] -$500Xprob[Demand<1,100] =$5,500*0.49-500*0.51=$2,440 Expected profit from ordering 1,100 is 5% greater than that of ordering 1,000.

Optimal cycle service level for seasonal items Focus on seasonal product where leftover items must be disposed at the end of season. Input: C0: cost of overstocking = c-s Cu: cost of understocking =p-c CSL*=optimal cycle service level O*=corresponding optimal order size CSL*=probability that demand during season will be at or below O*.

Optimal cycle service level for seasonal items Rise in quantity from O* to O*+1 is with probability 1-CSL* Expected profit of purchasing extra unit= (1-CSL*)(p-c) If additional unit remains unsold if demand is below O* Expected cost of purchasing cost of extra unit=CSL*(c- s) Expected marginal contribution of raising the order size from O* to O*+1=(1-CSL*)(p-c)- CSL*(c-s)

Optimal cycle service level for seasonal items Expected marginal cost=0 CSL*=probability (demand≤O*)= (p-c)/(p-s) C0/(Cu+C0)=1/{1+(C0/Cu)} Optimal CSL* is referred as critical fractile If demand during season is normally distributed with mean µ and standard deviation σ, optimal order quantity O*=F-1(CSL*, µ, σ) Expected profit= Fs is the standard normal cumulative distribution function and fs is the standard normal density function

Desired cycle service level for continuously stocked items Focus on products such as detergent that are ordered repeatedly. Organization uses safety inventory to increase the level of safety inventory to avoid stocking out. Left over detergent can be sold in next cycle. However, holding cost is incurred form one cycle to next cycle. Two extreme scenarios All demands that arises when the product is out of stock is backlogged and filled later All demand arising when product is out of stock is lost.

When Demand during stockout is backlogged No demand is lost, minimizing costs is equivalent to maximizing profit. When store is out of stock, discount of Cu is provided to each customer. Ensures that each customer will return. Increase in safety inventory satisfies more orders resulting in less backlogs Cost of holding inventory increases. Level of safety inventory that minimizes backlogs and holding cost?? Optimal cycle service level CSL*=1-(HQ/DCu)

Example Input Q=400 gallons, ROP= 300 gallons, D=100 gallons, σD=20, unit cost=$3, holding cost as a fraction of cost h=0.2, cost of holding one unit for one year=0.6 Lead time =2 weeks Cost of stocking out?? If all unfilled demand is backlogged and carried over to next cycle.

Solution Mean demand over lead time DL=DL=200 gallons Standard deviation of demand in lead time CSL=F(ROP, DL, σL) =F(300, 200, 28.3) CSL=NORMDIST(300, 200, 28.3, 1)=0.9998 Imputed cost of stocking out Cu=HQ/(1- CSL)Dyear=0.6*400/0.0002*5,200=230.8 per gallon

When Demand during stock out is lost Optimal cycle service level CSL* CSL*=1-HQ/(HQ+DCu) Cu is the cost of loosing one unit of demand during stockout period.

Managerial levers to improve SC profitability Focus on actions that can be taken to improve the SC profitability Two obvious managerial levers Increasing the salvage value of each unit increases profitability. Decreasing the margin lost from a stockout increases profitability. Strategies to Increase to salvage value include selling outlet stores so that left units are not merely discarded. To decrease the margin lost in a stockout include arranging the backup sourcing so that customers are not lost forever.

Importance of the Ratio of cost of overstocking and understocking If this gets smaller, optimal level of product availability increases.

Another lever Is to reduction of demand uncertainty. By this, better supply and demand can be matched by reducing over and understocking. Means to reduce demand uncertainty. Improved forecasting Quick response Postponement Tailored sourcing

Improving forecast Helps the demand planning information systems. Can help a firm to increase its profitability while decreasing excess inventory overstock and sales lost due to understocking.

Improved Forecasts Improved forecasts result in reduced uncertainty Less uncertainty (lower sR) results in either: Lower levels of safety inventory (and costs) for the same level of product availability, or Higher product availability for the same level of safety inventory, or Both lower levels of safety inventory and higher levels of product availability An increase in forecast accuracy decreases both the overstocked and understocked quantity and increases a firm’s profits.

Impact of Improving Forecasts (Example) Demand: Normally distributed with a mean of R = 350 and standard deviation of R = 100 Purchase price = $100 Retail price = $250 Disposal value = $85 Holding cost for season = $5 How many units should be ordered as R changes? Note: Cost of understocking = 250-100 = $150 Cost of overstocking = 100+5-85 = $20 p = 150/(150+20) = 0.88 Order size = 426

Impact of Improving Forecasts

Quick response Is the set of actions a supply chain takes that leads in the reduction of lead time. Decrease in lead time results in increase in forecast accuracy. This allows them to better match with the demand and increase in profitability. Typically, buyers are able to make accurate forecasts once they have observed demand in first or second week in season.

Quick Response Set of actions taken by managers to reduce lead time Reduced lead time results in improved forecasts Typical example of quick response is multiple orders in one season for retail items (such as fashion clothing) For example, a buyer can usually make very accurate forecasts after the first week or two in a season Multiple orders are only possible if the lead time is reduced – otherwise there wouldn’t be enough time to get the later orders before the season ends Benefits: Lower order quantities  less inventory, same product availability Less overstock Higher profits If quick response allows multiple orders in the season, profits increase and the overstock quantity decreases.

Example Selling season is of 14 weeks. Replenishment time is 25 to 30 weeks. Difficult for a buyer to make a accurate forecast of demand this far in advance. This results in high demand uncertainty, leading the buyer in too many or too less units each year. Consider a case where replenishment time can reduce upto 6 weeks. Its results in entire seasons purchase in two orders.

Variation of profit and inventories with forecast accuracy Expected over stock Expected profit Standard deviation of forecast error Expected understock

Quick Response: Multiple Orders Per Season Ordering shawls at a department store Selling season = 14 weeks Cost per handbag = $40 Sale price = $150 Disposal price = $30 Holding cost = $2 per week Expected weekly demand = 20 SD of weekly demand = 15

Comparison of two policies A single order must arrive at the beginning of the season to cover the entire seasons demand. Two orders are placed in the season, one arriving at the beginning of the season and other arriving at the beginning of the eight week. Now consider two instances One where buyers forecast accuracy does not improve for the second order and where it improves and the SD can be reduced.

Comparison Single order: consists of a quantity ordered at the beginning of season. Two orders: consists of initial order quantity for first seven weeks followed by an order upto level for the second week. Second round quantity should account for sales during the first week and inventory remaining. The quantity ordered in second round it the difference between order up-to-level and inventory remaining after first week.

Consequences of being able to place a second order The expected total quantity ordered during the season with two orders is less than that with a single order for the same cycle service level. The average overstock to be disposed of at the end of the sales season is less if two orders are allowed. The profits are higher when a second order is allowed during the sales season. Total quantity is broken up into multiple smaller orders, the buyer is better able to match supply and demand and increase profitability.

Impact of Quick Response

Forecast Improves for Second Order (SD=3 Instead of 15)

Postponement Delay of product differentiation until closer to the time of the sale of the product All activities prior to product differentiation require aggregate forecasts more accurate than individual product forecasts Individual product forecasts are needed close to the time of sale – demand is known with better accuracy (lower uncertainty) Results in a better match of supply and demand Valuable in e-commerce – time lag between when an order is placed and when customer receives the order (this delay is expected by the customer and can be used for postponement) Higher profits, better match of supply and demand Postponement allows a firm to increase profits and better match supply and demand if the firm produces a large variety of products whose demand is not positively correlated and is of about the same size.

Postponement Refers to the delay of product differentiation until closer to the sale of product. Aggregate forecasts are more accurate then individual product forecasts. Individual forecasts are required close to the time of sale when demand is known with greater accuracy. Allows a SC to better match SC demand.

Postponement… A powerful managerial tool to increase profitability. However, while using it production cost would be higher than the case where there is no postponement. Is valuable to for a firm that sells a large variety of products with demand.

Value of Postponement: Benetton For each color Mean demand = 1,000; SD = 500 For each garment Sale price = $50 Salvage value = $10 Production cost using Option 1 (long lead time) = $20 Production cost using Option 2 (uncolored thread) = $22 What is the value of postponement? Expected profit increases from $94,576 to $98,092

Value of Postponement with Dominant Product Color with dominant demand: Mean = 3,100, SD = 800 Other three colors: Mean = 300, SD = 200 Expected profit without postponement = $102,205 Expected profit with postponement = $99,872

Tailored postponement A firm uses production with postponement to satisfy a part of demand with the rest being satisfied without it. Produces higher profits then when no postponements is used or all are produced using postponement. A firm produces a portion of demand which is uncertain, postponement significantly improves the forecasts accuracy. Thus, allows a firm to increase its profitability by only postponing the uncertain part of the demand and producing the predictable part at a lower cost without postponement.

Tailored Postponement: Benetton Produce Q1 units for each color using Option 1 and QA units (aggregate) using Option 2 Results: Q1 = 800 QA = 1,550 Profit = $104,603 Tailored postponement allows a firm to increase profits by postponing differentiation only for products with the most uncertain demand; products with more predictable demand are produced at lower cost without postponement

Tailored Sourcing A firm uses a combination of two supply sources One is lower cost but is unable to deal with uncertainty well The other is more flexible, and can therefore deal with uncertainty, but is higher cost The two sources must focus on different capabilities Depends on being able to have one source that faces very low uncertainty and can therefore reduce costs Increase profits, better match supply and demand

Tailored sourcing Firms uses a combination of two supply sources Focusing on cost but unable to handle the uncertainty. Focusing on flexibility to handle uncertainty but at higher cost. But, to be effective, having supply sources where one serves as the backup to other is not sufficient. The first should be required to supply the predictable portion of demand. The second should be responsive and be required to supply the uncertain portion of demand. Allows to better match supply and demand and increase of profit.

Tailored sourcing… Value depends on the reduction in cost that can be achieved. Small benefit— it may not be ideal. May be volume based or product based depending on source depending on the source of uncertainty.

Volume based Tailored sourcing, the predictable part of a product’s demand is produced at an efficient facility. Should be considered by firms that have moved a lot of their production overseas to take advantage of lower costs. In this condition source with shorter lead time is more profitable even if he is more expensive.

Product based Low volume product with uncertain demand are obtained from a flexible source while high volume product with less demand uncertainty are obtained form an efficient source. New products have a very uncertain demand while well established products have more stable demand. May be implemented with a flexible facility focusing on new products and efficient facilities focusing on well established products.

Tailored Sourcing Sourcing alternatives Low cost, long lead time supplier Cost = $245, Lead time = 9 weeks High cost, short lead time supplier Cost = $250, Lead time = 1 week

Tailored Sourcing Strategies

Tailored Sourcing: Multiple Sourcing Sites

Dual Sourcing Strategies

Multiple product order Decrease the order size Allocating the products Setting Product Availability for Multiple Products under Capacity Constraints Single product order Multiple product order Decrease the order size Allocating the products When ordering multiple products under a limited supply capacity, the allocation of capacity to products should be based on their expected marginal contribution to profits. This approach allocates a relatively higher fraction of capacity to products that have a high margin relative to their cost of overstocking.

Setting Optimal Levels of Product Availability in Practice Use an analytical framework to increase profits Beware of preset levels of availability Use approximate costs because profit- maximizing solutions are very robust Estimate a range for the cost of stocking out Ensure levels of product availability fit with the strategy