eSupply Chain Solutions to Reduce the Bullwhip Effect - EBC6230

8/13/2019 eSupply Chain Solutions to Reduce the Bullwhip Effect - EBC6230

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E-Supply Chain Technologies & Applications

EBC 6230Winter Session 2014

Title :eSupply Chain Solutions to Reduce the Bullwhip EffectSubmitted to

Dr. Mohamed Baymout

Prepared byAnjali Sood

Elham Mohammad Pour

Irum Maqsood

Pilar Mata

Sergio Maldonado

Shymaa Slangor


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eSupply Chain

Solutions to Reduce theBullwhip EffectAnjali SoodElham Mohammad Pour

Irum Maqsood

Pilar Mata

Sergio Maldonado

Shymaa Slangor


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Agenda

Bullwhip Effect

Definition

Causes

Impacts

eSupply Chain Solutions

Information Sharing and Partnerships

Inventory Management

Forecasting

Just-In-TimeCase Study

Conclusions and Critiques


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Agenda

Bullwhip Effect

Definition

Causes

Impacts




Forecasting




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DefinitionBullwhip Effect (Boute, Disney , Lambrecht, & Houdt, 2008)

Jay Forester (1961): the tendency of replenishment orders to increase

in variability as it moves up the Supply Chain.

Procter and Gamble: Bullwhip Effect.

Most famous game describing the Bullwhip effect: the Beer

Distribution Game.

Source: stevekeifer.wordpress.com
http://stevekeifer.wordpress.com/2010/05/17/how-forward-buying-and-diversion-complicate-demand-planning-in-fast-moving-consumer-goods/http://stevekeifer.wordpress.com/2010/05/17/how-forward-buying-and-diversion-complicate-demand-planning-in-fast-moving-consumer-goods/


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Bullwhip EffectCauses (Lee, Padmanabhan, & Whang, 1997) (Joseph &Wilck ,2006):

1. Demand Forecast Updating:

Additional factors: distorted demand concepts, multiple forecasts, longlead times.

Downstreamoperation

Orderplacement

Upstreammanager

Demandforecast re-adjustment

Upstreamsuppliers


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2. Order batching:

Types: periodic ordering, push ordering.

The Bullwhip Effect depends on the type.

Additional factors: high fixed order costs, random ordering, and

correlated ordering.

3. Price fluctuation:

The effect of promotions.

Customers buy in bulks.

Customerbuyingpattern

Mistranslatedconsumption

pattern

BullwhipEffect


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4. Rationing and shortage gaming:

Gaming is placing numerous orders for one product by one

customer with the intention of receiving the fastest order fulfilment.

Causes a false spike in the demands.

Rationing is done by manufacturers whenever the product

demand exceeds the available supply.

The manufacturer allocates the amount in proportion to the amount

ordered.

Only 50% of orders of the real demand will be fulfilled.

Reason: customers exaggerate their real needs.

Free Returns Policy


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Bullwhip EffectImpacts (Boute, Disney , Lambrecht, & Houdt, 2008)

Many inefficiencies result from the Bullwhip Effect, such as:

Excessive inventory investment.

Poor customer service.

Lost revenues.

Wrong capacity plans.

Ineffective transportation.

Missed production schedules.


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Agenda

Bullwhip Effect

Definition

Causes

Impacts




Forecasting

Just-In-Time

Case Study



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eSupply Chain SolutionsInformation Sharing and Partnerships

Uncertainty caused by lack of perfect information between members of thesupply chain have been identified as a major cause of order amplification.

Information Sharing as a solution (Yu Zhenxin 2001)


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Benefits of Information Sharing:

Reduced costs

Reduced Inventories

Mitigate uncertainty that leads to order amplification

Products are manufactured at the right time, right quantity and distributedto the right location

Standards and Technologies that support information sharing:

Electronic Data Interchange (EDI): Transmission of POS data in real-time to allplayers of the supply chain

Point of Sale (POS)

Vendor Managed Inventories (VMI)


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Causes of Uncertainty(Mason-Jones R. et al. 1998):Manufacturing process

Supply Side

Lean Thinking

Partnership Source Programme

Demand Side

Planning and control systems

Information Sharing


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eSupply Chain SolutionsInventory Management

Vendor Managed Inventories (VMI)

Image Source:

http://www.supplychain247.com/article/retailers_are_driving_rfid_adoption_and_propagating_the_benefits/omni_id/D2


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Share POS Data

POS data provides Actual Demand figures

Sharing POS data enables businesses to compare Shipment data withActual Demand Data and therefore allows for better shipment scheduling

Source: http://www.opsrules.com/supply-chain-optimization-

blog/bid/313709/How-to-Use-POS-Data-to-Improve-Supply-Chain-

Performance


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RFIDRadio Frequency Identification

Image Source: http://www.supplychain247.com/article/retailers_are_driving_rfid_adoption_and_propagating_the_benefits/omni_id


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eSupply Chain SolutionsForecasting

Forecasting techniques in e-supply chain to reduce thebullwhip effects are as bellow:

Simple Moving Average

Weighted Moving Average

Exponential Smoothing method


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Simple Moving Average (Sun,2005)


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Weighted Moving Average(Sun,2005)


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Exponential Smoothing Method (Sun, 2005) (Chen et al, 1999):

Forecast = (Actual Demand Previous Period x ) + (Previous Demand x (1-))


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Amazon Demand Forecasting

Source: www.amazon.com/wishlist
http://www.amazon.com/wishlisthttp://www.amazon.com/wishlist


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eSupply Chain SolutionsJust-In-Time

Just-In-Time

Introduced by Toyota in 1950s

Inventory = Waste

From Push to Pull processes


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eSupply Chain SolutionsJust-In-Time

Technologies that support JIT

Old days: Kanban Cards

Present time: Internet, RFID, Sensors


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Agenda

Bullwhip Effect

Definition

Causes

Impacts

eSupply Chain Solutions Information Sharing and Partnerships


Forecasting




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eSupply Chain SolutionsCase Study

Reducing Bullwhip effect by Centralizing Internal

Information (Boone and Ganeshan, 2008)

Background

Midsize retailer with annual sales of $1 billion operating in more than 20

locations

Each location could have more than one department store, convenience

store etc.

Corporate Headquarters are responsible for :

Setting the overall financial goals

Merchandising policies

Coordinating resources across retail locations

Maintaining responsibility for financial reporting


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Traditional model of how the retailer is doing

business


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Implemented New System

Installed 128-bit scanners that captured the product barcodes.

Information captured was stored in a centralizeddatabase

Corporate Headquarter can now look at this centralizedsystem which will help them make better decisions


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Benefits

Supply Chain Costs Before and After Information Visibility

Source: (Boone and Ganeshan, 2008)


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Agenda

Bullwhip Effect

Definition

Causes

Impacts

eSupply Chain Solutions Information Sharing and Partnerships


Forecasting




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Information sharing is considered one of the important strategies

for reducing or mitigating the bullwhip effect.

Information sharing through e-supply chain systems not only

facilitates effective sharing of information, it also allows fast

dissemination of important data.

It is essential for organizations to adopt measures to capture and

store data that can then be used for effective communication,

inventory management, forecasting and reporting.

There are increasing number of third party vendors that provide out

of the box, cloud, and open source solutions that can be adopted by

organizations of various sizes.

e-Supply chains are playing an important role in mitigating the

bullwhip effect and the scope to leverage them is only limited by the

costand technologyused by the organizations.


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References

Al-Zubi , H. (2010). Applying Electronic Supply Chain Management Using Multi-Agent System: A Managerial Perspective . (pp. 106-113). International Arab Journal of e-Technology. Anatan, Lina. INFORMATION SHARING AMONGST SUPPLY CHAIN PARTNERS:THE WAY TO SOLVE BULLWHIP EFFECTIN SUPPLY CHAIN MANAGEMENT, Fakultas Ekonomi Universitas Kristen

Maranatha Bandung

Aprille, D., & Garavelli, A. C. ( 2007). BULLWHIP EFFECT REDUCTION: THE IMPACT OF SUPPLY CHAIN FLEXIBILITY. 19th International Conference on Production Research(ICPR -19). Chile.

B.S. Sahay, Jayanthi Ranjan, (2008) "Real time business intelligence in supply chain analytics", Information Management & Computer Security, Vol. 16 Iss: 1, pp.2848

Bottani, E., Montanari, R., & Volpi, A. (2010). The impact of RFID and EPC network on the bullwhip effect in the Italian FMCG Supply Chain. Int.J.ProductionEconomics, 426-432.

Boute, R. N., Disney , S. M., Lambrecht, M. R., & Houdt, B. V. (2008). A win-win solution for the bullwhip problem.

Disney, S. M., & Towill, D. R. (2003). The effect of vendor managed inventory (VMI) dynamics on the Bullwhip Effect in supply chains. Int. J. Production Economics, 199215.

Frank Chen,1 Jennifer K. Ryan,2 David Simchi-Levi3. 1999. The Impact of Exponential Smoothing Forecasts on the Bullwhip Effect

HX Sun, YT Ren. 2005. The Impact of Forecasting Methods on Bullwhip Effect in Supply Chain Management

Johansson H J, McHugh P., Pendlebury AJ. And Wheeler III WA. (1993). Business Process Re-engineering (Willey).

Joseph , H., & Wilck , I. (2006). Managing the Bullwhip Effect .

Keifer, S. (2009). Why amazon.com has the best demand forecasting data. Retrieved January 2014, from gxsblogs: http://www.gxsblogs.com/keifers/2009/12/why-amazon-com-has-the-best-demand forecasting-data.html

Lee, H. L., Padmanabhan, V., & Whang, S. (1997). The Bullwhip effect in Supply Chains . MIT Sloan Management Review , pp. 93-102.

Mason-Jones R and Towill, D R (1998). Shrinking the Supply Chain Uncertainty Circle. Control Vol. 24,No. 7,pp 17 -23. Mason-Jones Rachel and Towill Denis R., 2000, Coping with Uncertainty:Reducing Bullwhip. Behaviour in GlobalSupply Chains , Supply Chain Forum, An International Journal.

Napolitano, M. (2013). Retailers are Driving RFID Adoption and Propagating the B enefits Throughout their Supply Chains. Retrieved from SupplyChain24/7:http://www.supplychain247.com/article/retailers_are_driving_rfid_adoption_and_propagating_the_benefits/omni_id/D2

Sari, K. (2010). Exploring the impacts of radio frequency identification (RFID) technology on Supply Chain Performance. European Journal of Operational Research, 174-183.

Schonberger, R. J. (2006). Japanese production management: An evolutionWith mixed success. Bellevue, WA, United States: Journal of Operations Management.

Srinivasan K, Kekre S., and Mukhopadhyay, T. (1994). Impact of Electronic Data Interchange technology on JIT shipments. Management Science, Vol. 40, pp1291 -304.

Sugimori, Y., Kusunoki, K., Cho, F., & Uchikawa, S. (1977). Toyota production system and kanban system: materialization of just-intime and respect-for-human system. International Journal ofProduction Research.

Tonya Boone and Ram Ganeshan (2008). Forecast Process Improvement: The Value of I nformation Sharing in the Retail Supply Chain - Two Case Studies

Traub, T. (2012, July). Wal-Mart Used Technology to Become Supply Chain Leader. Retrieved from Arkansas Business: http://www.arkansasbusiness.com/article/85508/wal-mart-used-technology-to-become-supply-chain-leader?page=all

Wahl, M. (2013). HOW TO USE POS DATA TO IMPROVE SUPPLY CHAIN PERFORMANCE. Retrieved from OPS Rules Blog: Insights into Supply Chain and Operations Strategy:http://www.opsrules.com/supply-chain-optimization-blog/bid/313709/How-to-Use-POS-Data-to-Improve-Supply-Chain-Performance

Wang, H., & He, B. (2011). Research on the Reducing Measures of Bullwhip Effect. 2011 International Conference on Software and Computer Applications ( pp. 202-206). Singapore: IACSIT Press.

Wilck, J. H. (n.d.). Managing the Bullwhip Effect.

Yasushiro, M. (2012). Toyota Production System: An Integrated Approach to Just-In-Time, Fourth Edition. Auerbach Publications.

Yu Zhenxin, Yan Hong and Cheng Edwing T.C. (2001). Benefits of Information Sharing with Supply Chain Partnerships. Industrial Management & Data Systems. 101/3.Pp114-119

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eSupply Chain Solutions to Reduce the Bullwhip Effect - EBC6230

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