Chapter 13

Linking Product Availability to Profits

• Product availability affects expected profits
• This chapter covers the following topics:
• Factors influencing the optimal cycle service level
• Managerial levers to match supply and demand
• Improving supply chain profitability

Factors Affecting the Desired Level of Product Availability

• Product availability is measured by the cycle service level or fill rate
• Customer service level is also known as product availability
• High product availability can improve responsiveness and attract customers, increasing revenue
• High product availability requires large inventories, which can raise supply chain costs
• It's important to balance product availability and inventory costs to maximize expected profits
• In Q4 2008, U.S. inventories rose by $6.2 billion due to a rapid decline in demand hitting retailers and manufacturers
• Retailers like Steve & Barry's and Circuit City declared bankruptcy due to excess inventories and a drop in demand
• Nintendo missed about $1.3 billion in sales in the 2007 holiday season due to not meeting soaring global demand for its Wii
• High or low optimal availability depends on if the company thinks it can maximize profits either way
• Nordstrom focuses on high product availability to become a successful department store chain having higher prices
• Lower product availability occurs at discount stores
• Power plants need to ensure they never run out of fuel because a shutdown is extremely expensive, whereas, Supermarkets carry only a few days of supply and out-of-stock situations can occur with some frequency
• Online retailers face pressure to increase product availability because the Internet allows customers to shop elsewhere
• Online prices have been lowered due to significant price competition
• Providing the optimal level of product availability is key to being successful online
• When demand is predictable, supply and demand can perfectly match
• It only makes sense to decide on an optimal level of product availability when demand is uncertain
• Traditionally, companies forecasted a consensus on demand, without uncertainty
• Traditionally firms ordered the consensus forecast and did not make a decision regarding the level of availability
• Since the start of the 21st century, companies have developed a better appreciation for uncertainty, and have started developing forecasts to include the measure of uncertainty
• Incorporating uncertainty and deciding on the optimal level of product availability can increase profits relative to a consensus forecast
• L. L. Bean has a buying committee that decides on the size of each product
• Buyers have estimated the demand distribution for a women's red ski parka based on demand over the past few years, deviating from the practice of using the average historical demand as a consesus forecast
• L. L. Bean places orders in multiples of 100

Optimal Cycle Service Level for Seasonal Items with a Single Order in a Season

• Focus should be on seasonal products for which all leftover items must be disposed of at the end of the session
• The season starts with product from the order placed and any leftover inventory is disposed of at a discounted price at the end of the season
• These are the inputs:
• Co is the cost of overstocking by one unit; Co = c – s
• Cu is the cost of understocking by one unit Cu = p – c
• CSL* is the optimal service cycle level
• O* represents the optimal order size
• CSL is the probability that demand during the season will be at equal to or below O*
• At the optimal cycle service level CSL*, the marginal contribution of purchasing an additonal unit is zero
• If order quantity is raised from O* to O* + 1, the additional unit sells if demand is larger than O*, which occurs with probabilty 1 – CSL* and results in a contribution of p-c
• This translates to : Expected benefit of purchasing extra unit = (1 – CSL*)(p - c)
• The additional unit remains unsold if demand is or below O*. Probability CSL* and cost c-s
• This translates to : Expected cost of purchasing extra unit = CSL*(c - s)
• The expected marginal contribution of raising the order size from O* to O* + 1 is given by (1 - CSL*)(p - c) – CSL*(c - s)
• Because the expected marginal contribution must be 0 at the optimal cycle service level
• As the ratio gets smaller, the optimal level of product availability increases
• Nordstrom has higher margins and greater cost of understocking and a higher-end store rather than a discount store
• Nordstrom gives a higher level of product availability than a discount store with lower margins and cost of stocking out
• The optimal CSL* is also referred to as the critical fractile
• The resulting optimal order quantity maximizes the firm's expected profit
• If the demand during season is normally distributed, the mean for u and the standard deviation for sigma, the optimal order quantity is given by formula.
• When demand is normally distribited, with a mean of u and standard deviation of sigma, the expected profit from ordering O units is given by the formula.

One-Time Orders in the Presence of Quantity Discounts

• Buyer makes single order, seller offers price discount based on the purchased quantity
• The manufacturer offers lower price per unit if order quantity reaches the set limit
• Arises at the end product’s life cycle or spare parts, where demand to product and spare parts are uncertain so the buyer gets a single opoortunity to order
• Buyer accounts for the discount when making the order size
• A retailer has a last chance to order parts before manufacturer stops production
• The part is a retail price per unit of p, with no discount for retailer, and a salvage value of s.
• The manufacturer offers discounted price if retailer orders at least K units
• Here are the order size decision steps:
• Using Co = c − s and C₁ = p - c, you can evaluate the optimal cycle service level CSL* and order size O* without a discount
• You can then evaluate the expected profit from ordering O*
• Using new variables, evaluate cycle service and order with discount given the new constraints/variables and associated values.
• Order the larger of the two values, only if the numbers are more than the constraints set by customer/retailer or K units for the business.

Desired Cycle Service Level for Continuously Stocked Items

• Retail store such as Walmart orders detergent repeatedly
• Safety inventory is used by Walmart to increase availability and decrease possibility of stocking out between shipments
• If detergent is left it gets sold, no disposal due to lower cost is needed like other inventory methods or constraints
• Product is charged with holding cost as it is carried from one cycle to the next
• Faced with the issue of finding CSL to aim for
• Here are two extreme scenerios:
• Demand that arises for product out of stock can be backlogged for when inventories replenish
• Demand that arises for product is lost
• In most instances it will be in between with either demand being lost for customers or products being in stock
• Demand per unit of time is typically distributed
• The example: Walmart sells detergent, the manager has a store offering a rain check at a discount, and all customers have to remain in stock.
• The backlogging or understocking cost per unit is backlogging
• The more a manager increases levels of safety, resulting in lower backlogs
• Lower inventory holding costs. The costs and benefits of this level will be taken into account
• If safe inventory is increased from ss and provides cycle level and D is the supply cycle cost

Use Basic Managerial Levers to Improve Supply Chain Profitability

• Having identified the factors for that influences the optimal level of product availability
• Basic actions a manager can take to increase profit supply chain
• Increasing profit
• Increasing profit if salvage is increased
• Decreasing stock out
• Increasing uncertainty

The Value of Speed in a Seasonal Supply Chain

• Quick response: Actions a supply chain takes to lower replenishment lead time
• Supply chain managers can improve forecase accurracy with lead times going down, which allows them to better match S&D
• Shortening the lead time allows the potential savings
• Illustration used: Saks Fifth Avenue as a high end dept store, purchasing cashmere shawls from India & Nepal where selling session lasts 14 weeks Historically replenishment took 25-30+ weeks. Therefore orders were in the dark Buyers were forced to guess/speculate in the face of uncertainty, creating overstocked or understocked opportunities Shortened times makes them make accurate forecasts faster

The Value of Postponement in a Seasonal Supply Chain

• It helps make better forecasts by using better data based on what the actual demands are, versus historical data
• Postponment can be particularly beneficial if customers are willing to wait for delivery
• This allows the ability to see accurate data, and have products made to order, leading to more accurate data
• Benetton example used; it was cheaper to traditionally knit garments, but to stay compettive, made the investment and was able to make garments on demand to stay competitive

Allocate Limited Supply Capacity Among Multiple Products Under Capacity Constraints

• A firm can set the level of product availability
• Common scenario of a firm ordering too much product to exceed the constraints of suppliers
• Best to minmize the capacity of available products