SCM: Information distortion1 Supply Chain Management Demand Variability and Coordination in a Supply Chain

SCM: Information distortion 1

Supply Chain Management

Demand Variability and Coordination in a Supply Chain


Demand variability and information distortion

• The Pampers Supply Chain (P&G)

Babies Customers Retailers Wholesalers P & G 3 M



• HP printer

• HP executives found:– Sales at major resellers show some fluctuation– Orders from these resellers show much larger

fluctuation– Orders from HP printer division to HP’s IC

division show even larger fluctuation



• The Barilla Supply Chain– Show similar pattern of variability in the supply

chain


Consequences of variability in the supply chain


Common symptoms of information distortion in SC

• excessive inventory

• poor product forecast

• insufficient or excessive capacities

• poor customer service (unavailable product or long backlogs)

• uncertain product planning



• Manufacturers– not able to see the actual sales from the

retailers, thus product forecasting, capacity planning, inventory control and production scheduling are based on distorted data.

• not able to meet actual demand or excessive inventory

• insufficient capacities or high proportion of idle capacities



• The supply chain – excessive inventory in every stage of the supply

chain while still unable to meet customers’ demand

– Every partner in the supply chain is burnt



• the grocery industry

• the computer industry

• the Pharmaceutical industry

over 100 days of supply in the supply chain, if the raw material of the suppliers are included, it could well over a year of supply.


What caused the Bullwhip?



• Decision makers’ irrational behavior in decision making

• their misconception about demand information and inventory information– better training for the decision makers



• Consequence of rational behavior in the supply chain’s infrastructure– to mitigate the Bullwhip effect, we need to

modify the supply chain infrastructure and related processes, rather than the decision makers’ behavior.


Causes of bullwhip

Causes Contributing Factors

Multiple dataprocessing

No visibility of end demand,multiple forecases, long lead time

Order batching High order cost, full truckload,long lead time

Price fluctuation Hi-low pricing, promotion

Shortage gaming Proportional rationing, ignoranceof supply information


Demand forecasting

• forecasting is often based on the ordering history from the immediate customers of the firm, it then projects the future demand for the lead time plus the safety stock required for the period

• the decision process is repeated as one moves up the chain, thus amplifying the variability– the longer the lead-time, the more pronounced

is the fluctuation


Order batching

• “Manual” ordering is too costly– P&G estimate : each invoice to customers is around

US$35-$75– place orders when a firm runs its MRP system

• Economy of transportation– full truckload (FTL) get better rates than less FTL

• Push ordering – salespersons push sale in time when they are evaluated by

their company


Price fluctuation

• manufacturer induced forward buying by offering discounts or during promotion– retailer buy more when price is low and stop

buying until inventory is depleted when price returns to normal (P. Sellers, “The Dumbest Marketing Ploy”, Fortune, Vol. 126, 5 Oct. 1992, pp88-93)


Rationing and shortage gaming

• If demand is greater than supply, allocation scheme used by supplier may induce gaming:– exaggerate demand when item is selling hot, in

anticipation of rationing and inventory shortage– cancel orders when demand becomes cool

• e.g., DRAM chips in 80’s, HP LaserJet III printer, IBM Aptiva PC in October 1994, etc


Mitigating the bullwhip effect


Mitigating the bullwhip effectCauses Mitigating strategies

Multiple dataprocessing

POS data, Sell-through data,VMI, CRP, leadtime reduction,consumer direct ordering

Order batching Consolidation, EDI, setupreduction, 3rd party logistics,

Price fluctuation Every day low price, moreaccurate accounting systems

Shortage gaming New allocation rules, capacity &inventory sharing,


Avoid multiple demand forecasting

• make demand data downstream available to the upstream site– computer manufacturers request sell-through data on withdrawn

stocks in the retailers’ central warehouse (IBM, HP, Apple, etc)

• Increase use of EDI facilitate data commission• vendor managed inventory (VMI)or continuous

replenishment program(CRP), (P&G with Wal-Mart, Campbell Soup)

• get demand data by bypassing downstream site (consumer direct program of Apple, Dell Computers)


Break order batches• Use electronic Data Interchange (EDI) ordering -

lower ordering cost• 3rd party logistics for competitors in the same

region or for different supplier in the same region

• manufacturer induces distributors order mixed product in a truckload (at FTL discount rate), e.g., P&G gives discounts to distributors to order mixed SKU’s


Stabilize prices

• Reduce the frequency and level of wholesale price discounting (P&G, Kraft use EDLP),

• More accurate accounting systems, e.g., activity-based costing (ABC)


Eliminate gaming in shortage situation

• allocate product according to past sale records, not proportional to orders, e.g., GM used it, HP and TI are switching to it

• Sharing of capacity and inventory information - to alleviate customer anxiety

• more stringent order cancellation policy

Documents

SCM: Information distortion1 Supply Chain Management Demand Variability and Coordination in a Supply Chain