The impact of information enrichment on the Bullwhip effect in supply chains: A control engineering perspective

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: orderup-to policies and smoothing policies (policies used to reduce or dampen variability in the demand). For the class of order-up-to 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.