Supply Chain Inventory Management and the Value of Shared Information

Gerard P.Cachon* Marshall Fisher

presented by Ağcagül YILMAZ

Content

Aim Literature Assumptions Policies Traditional Information Policy Lower Bound Full Information Policy Numerical Study Results Discussion

Aim...

How information technology improves supply chain performance?

Ex.Barilla (5 days lead time reduction). Under Traditional Information Policy, Lower Bound,Full

Information Policy w/ different parameters such as # of retailers,batch size,lead time,penalty cost,holding cost,demand distribution

Better supplier replenishments and better allocation to retailers.

Literature

*** studies on: -Sharing other parameters of retailer -Forecast Sharing for future demand -Perfect source of inventory -Limited supplier capacity -Nonstationary retailers demand -Sharing information w/different allocation rules -no outside inventory source -local information get retailers but not suppliers -lower bound for multiple retailer order over all feasible

policies

1 Supplier N identical Retailers Stationary Stochastic Consumer Demand w/known

distribution. Multiple of base batch quantity as shipment quantity Fixed transportation times btw locations Holding cost at all levels,backorder penalty cost at retailers 1 Product under constant pricing condition No capacity constraint

Assumptions

No incentive conflicts among firms Rational ordering policies in firms Perfect Information Sharing No diversion of stock among retailers Replenishment delays due to stock-outs at supplier Periodic inventory review within each period the following

sequence of events occur: retailers order,supplier orders,inventory shipments are received&released,inventory holding and backorders are charged.

Not perfect source of inventory Sharing local information of retailer by supplier

Assumptions

POLICIES

TRADITIONAL INFORMATION POLICY

LOWER BOUND

FULL INFORMATION POLICY

TRADITIONAL INFORMATION POLICY

Supplier knows only the retailer`s orders. (Rr, nQr) reorder point policy for retailers

(Rs,nQs) reorder point policy for suppliers

Batch priority allocation as supplier`s allocation policy(first-in-first-out)

R

LOWER BOUND Simulation based lower bound over all feasible policies. Independent of the level of the information sharing. Two steps: Division of the supply chain cost into two parts Lower bound for each components

LOWER BOUND Division of the Supply Chain Cost - Retailer Charged &Supplier Charged ( in fact actual cost in

infinite horizon) Evaluation of the Lower Bound - Uniformly distributed reorder point policy for retailer charge

calculation

- Location constraint is relaxed for supplier charges

-How inventory allocated btw retailers ,Myopic Policy

Calculation of the cost done by simulation due to large state space and difficulty in steady state distribution of IP

Confidence intervals for each cost found in simulations is given.

FULL INFORMATION POLICY Full information provides the supplier w/data to - improve its order quantity decisions - improve its allocation decisions Allocation based on -retailer`s inventory positions rather than the number batches they

order -the allocation of a batch based on retailer`s inventory positions in the

period the batch is shipped rather than ordered. -Order quantity by using the lower bound expression - Under traditional R* found and put in lower bound information

policy expression. Simulation is necessary

.

FULL INFORMATION POLICY

Out of balance in retailer`s inventory position is less likely when; -Qr is increased, -Consumer demand variability is decreased, -Ls is decreased.

Numerical Study 768 scenarios w/combination of following parameters N € (4,16) ; Qr € (2,4,8,16) ; Lr € (1,5) ; hr =1-hs ; pr €

(5,25) ; σr € (0.36,1) ; Qs € (1,4,16); Ls € (1,5) ; hs (0.5,1) µr=1 For each one traditional information policy, 40 simulations

for each scenario over 10 supplier order cycles for lower bound and full information policy

When lower bound greater than full inf. Policy cost 90 additional simulations per scenario.

95% confidence intervals for lower bound and full inf. Case.

N

RESULTS On the average cost reduction 2.2% lower in full inf.policy than

traditional inf. policy.12.1% is the max. difference. On the average cost reduction 3.4% lower in lower bound than

traditional inf. policy.13.8% is the max. difference. 21% reduction in cost by cutting lead times nearly half. 22% reduction in cost by cutting batches nearly half.

DISCUSSION - Demand information is most valuable when IP of the retailers approaches R, in an

unknown environment - Use information technology to accelerate the physical flow of goods rather than

expanding the flow of information to get higher cost reduction in supply chain. - Full information policy is close to optimal. - Full information policy is better than traditional as expected.

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THANKS!