The impact of information enrichment on the bullwhip effect in supply chains: a control engineering perspective. (English) Zbl 1099.90503

Summary: This paper examines the beneficial impact of information sharing in multi-echelon supply chains. We compare a traditional supply chain, in which only the first stage in the chain observes end consumer demand and upstream stages have to base their forecasts on incoming orders, with an information enriched supply chain where customer demand data (e.g. EPOS data) is shared throughout the chain. Two types of replenishment rules are analysed: order-up-to (OUT) policies and smoothing policies (policies used to reduce or dampen variability in the demand). For the class of OUT policies, we will show that information sharing helps to reduce the bullwhip effect (variance amplification of ordering quantities in supply chains) significantly, especially at higher levels in the chain. However, the bullwhip problem is not completely eliminated and it still increases as one moves up the chain. For the smoothing policies, we show that information sharing is necessary to reduce order variance at higher levels of the chain.
The methodology is based on control systems engineering and allows us to gain valuable insights into the dynamic behaviour of supply chain replenishment rules. We also introduce a control engineering based measure to quantify the variance amplification (bullwhip) or variance reduction.


90B05 Inventory, storage, reservoirs
90B50 Management decision making, including multiple objectives
90B30 Production models


Full Text: DOI


[1] Adelson, R.M, The dynamic behaviour of linear forecasting and scheduling rules, Operational research quarterly, 17, 4, 447-462, (1966)
[2] Berry, D; Naim, M.M; Towill, D.R, Business process re-engineering an electronics products supply chain, Proceedings of IEE science, measurement, and technology, 142, 5, 395-403, (1995)
[3] Bertrand, J.W.M, Balancing production level variations in complex production systems, International journal of production research, 24, 5, 1059-1074, (1986)
[4] Chen, F; Drezner, Z; Ryan, J; Simchi-Levi, D, Quantifying the bullwhip effect in a simple supply chain: the impact of forecasting, lead times, and information, Management science, 46, 3, 436-443, (2000) · Zbl 1231.90019
[5] Chen, F; Ryan, J; Simchi-Levi, D, The impact of exponential smoothing forecasts on the bullwhip effect, Naval research logistics, 47, 4, 271-286, (2000) · Zbl 0968.90006
[6] Dejonckheere, J; Disney, S.M; Lambrecht, M.R; Towill, D.R, Measuring the bullwhip effect: A control theoretic approach to analyse forecasting induced bullwhip in order-up-to policies, Forthcoming in the European journal of operational research, (2003) · Zbl 1026.90030
[7] Dejonckheere, J., Disney, S.M., Farasyn, I., Janssen, F., Lambrecht, M., Towill, D.R., Van de Velde, W., 2002. Production and Inventory Control: The variability trade-off. Proceedings of the 9th EUROMA Conference, 2-4 June, Copenhagen, Denmark, ISBN 1 85790 088X
[8] Deziel, D.P; Eilon, S, A linear production-inventory control rule, The production engineer, 43, 93-104, (1967)
[9] Disney, S.M., 2001. The production and inventory control problem in Vendor Managed Inventory supply chains. PhD Thesis, Cardiff University, UK
[10] Disney, S.M; Towill, D.R, A discrete transfer function model to determine the dynamic stability of a vendor managed inventory supply chain, International journal of production research, 40, 1, 179-204, (2001) · Zbl 1175.90138
[11] Disney, S.M; Towill, D.R, A procedure for the optimization of the dynamic response of a vendor managed inventory system, Computers and industrial engineering, 43, 1, 7-58, (2001)
[12] Disney, S.M., Towill, D.R., 2002. A robust and stable analytical solution to the production and inventory control problem via a z-transform approach. Proceedings of the 12th International Working Conference on Production Economics, vol. 1. ISSN 0925 5273, Igls, Austria, 18-22 February, pp. 37-47
[13] Disney, S.M; Naim, M.M; Towill, D.R, Dynamic simulation modelling for Lean logistics, International journal of physical distribution and logistics management, 27, 3, 174-196, (1997)
[14] Forrester, J, Industrial dynamics, (1961), MIT Press Cambridge MA
[15] Forrester, J., 1958. Industrial dynamics, a major breakthrough for decision makers. Harvard Business Review July-August, vol. 36, 37-66
[16] Fransoo, J.C; Wouters, M.J.F, Measuring the bullwhip effect in the supply chain, International journal of supply chain management, 5, 2, 78-89, (2000)
[17] Garnell, P; East, D.J, Guided weapon control systems, (1977), Pergamon Press Oxford
[18] Holmström, J, Product range management: A case study of supply chain operations in the European grocery industry, Supply chain management, 2, 3, 107-115, (1997)
[19] Holt, C.C., 1957. Forecasting seasonals and trends by exponentially weighted moving averages. ONR memorandum, Carnegie Institute of Technology, Pittsburgh, Pennsylvania, p. 52
[20] John, S; Naim, M.M; Towill, D.R, Dynamic analysis of a WIP compensated decision support system, International journal manufacturing system design, 1, 4, 283-297, (1994)
[21] Lee, H.L; Padmanabhan, V; Whang, S, The bullwhip effect in supply chains, Sloan management review spring, 38, 3, 93-102, (1997)
[22] Lee, H.L; Padmanabhan, V; Whang, S, Information distortion in a supply chain: the bullwhip effect, Management science, 43, 4, 546-558, (1997) · Zbl 0888.90047
[23] Lee, H.L; So, K.C; Tang, C.S, The value of information sharing in a two level supply chain, Management science, 46, 5, 628-643, (2000) · Zbl 1231.90044
[24] Makridakis, S; Wheelwright, S.C; McGee, V.E, Forecasting: methods and applications, (1978), John Wiley & Sons
[25] Mason-Jones, R; Towill, D.R, Information enrichment: designing the supply chain for competitive advantage, International journal of supply chain management, 2, 4, 137-148, (1997)
[26] Mason-Jones, R., 1998. The holistic strategy of market information enrichment through the supply chain. PhD Thesis, Cardiff University, UK
[27] Metters, R, Quantifying the bullwhip effect in supply chains, Journal of operations management, 15, 2, 89-100, (1997)
[28] Nise, N.S, Control systems engineering, (1995), The Benjamin/Cummings Publishing Company, Inc California
[29] Shannon, C.E; Oliver, B.M; Pierce, J.R, The philosophy of pulse code modulation, Proceedings of the IRE, 36, 11, 1324-1331, (1948)
[30] Simon, H.A, On the application of servomechanism theory to the study of production control, Econometrica, 20, 247-268, (1952) · Zbl 0046.37804
[31] Sterman, J, Modelling managerial behaviour: misperceptions of feedback in a dynamic decision making experiment, Management science, 35, 3, 321-339, (1989)
[32] Suzaki, K, The new manufacturing challenge, (1987), The Free Press New York
[33] Towill, D.R; McCullen, P, The impact of an agile manufacturing programme on supply chain dynamics, International journal logistics management, 10, 1, 83-96, (1999)
[34] Towill, D.R, Transfer function techniques for control engineers, (1970), Iliffe Books London
[35] Towill, D.R, Dynamic analysis of an inventory and order based production control system, International journal of production research, 20, 369-383, (1982)
[36] Towill, D.R., 1999. Fundamental theory of bullwhip induced by exponential smoothing algorithm. MASTS Occasional Paper No. 61, Cardiff University
[37] Van Ackere, A; Larsen, E.R; Morecroft, J.D.W, Systems thinking and business process redesign: an application to the beer game, European management journal, 11, 4, 412-423, (1993)
[38] VanAken, J.E, On the control of complex industrial organisations, (1978), Martinus Nijhoff (Social Sciences Division) London
[39] Vassian, H.J, Application of discrete variable servo theory to inventory control, Operations research, 3, 272-282, (1955) · Zbl 1414.90054
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