The bullwhip effect

00:08 Introduction
00:30 Stephen, perhaps you could start by telling us a little more about your background?
01:20 Can you give us a brief overview on the Bullwhip Effect?
02:20 Which are the factors that can influence the Bullwhip Effect?
03:59 What is your view on the four factors?
05:48 Stephen, what were the main conclusions of your paper? Are they still relevant today?
07:57 Do you agree with the idea that the Bullwhip Effect can be mitigated, if not eliminated completely?
12:14 How can the control theory be applied?
15:39 What are your thoughts on the control theory? Can it work?
19:07 Stephen, what advice would you give to the companies you work with?
23:14 How relevant is the Bullwhip Effect today? Was Covid-19 a good example of the Bullwhip Effect in action?
26:05 Stephen, what are you research interests right now?


The “Bullwhip Effect” was an influential paper published in 1997 that looked at how transactional information can be distorted, resulting in knock-on effects upstream on the supply chain. For this episode of LokadTV, we’re delighted to welcome Stephen Disney to learn more about how this phenomenon occurs and what impact it can have on supply chain practitioners.

Stephen Disney is Professor of Operations Management at University of Exeter, as well as head of the Science Innovation Technology and Entrepreneurship department. Stephen has spent the last 25 years studying the Bullwhip Effect.

We can say that the Bullwhip Effect consists of the fluctation observed in a system, in this case a supply chain, which exceeds the magnitude of the fluctation that feeds the system’s input, i.e. the demand. There are then various elements that can magnify and diminish these fluctuations, for example very basic things such as inventory buffers. The original paper identified four key sources: “demand signal processing”, “batching”, “rationing and gaming” and “price variations”.

Joannes and Stephen discuss whether the Bullwhip Effect is inevitable in modern supply chains and the all important role of forecasting. They go into more detail about deep learning and the rediscovery of stochastic gradient descent. Joannes also explains why Lokad made the move to probabilistic forecasting.

To conclude, we expand upon the impact of Covid-19 and if this has exarcebated the Bullwhip Effect for supply chains or not, the importance of thinking in financial outcomes for your company and not just percentages, and the future of dual sourced supply chains.