- 02 Nov 2006
- Working Paper Summaries
Managing Functional Biases in Organizational Forecasts: A Case Study of Consensus Forecasting in Supply Chain Planning
Overview — By their very nature, consensus forecasts contain subjective elements that can compromise forecast accuracy. In this case study of the implementation of a sales and operations planning process in a consumer electronics company, Oliva and Watson studied the organizational and political dimensions of forecast generation and improvement. Ultimately, consensus forecasting constructively managed the influence of biases (such as overconfidence) on forecasts. Key concepts include:
- Better and more integrated information is not sufficient for a good forecast. Design the process so that social and political dimensions of the organization are effectively managed.
- Create an independent group to manage the forecast process, not the forecast itself. This helps to stabilize the political dimension.
- Unintended incentives and blind spots can arise as a result of newly implemented processes, so managers need to control for biases and their effects on system performance.
- Insights from this case study can be generalized and extended to other settings that require cross-functional coordination.
To date, little research has been done on managing the organizational and political dimensions of generating and improving forecasts in corporate settings. We examine the implementation of a supply chain planning process at a consumer electronics company, concentrating on the consensus forecasting approach around which the process revolves. Our analysis reveals how the implemented forecasting process manages the political conflict and individual and group biases occasioned by organizational differentiation. We categorize the sources of functional bias into intentional, driven by misalignment of incentives, and unintentional resulting from informational and procedural blindspots. We find consensus forecasting, despite a number of characteristics of that make it a challenge to fit to a dynamic supply chain environment, to be effective in that context. We further show that the forecasting process, together with the supporting mechanisms of information exchange and elicitation of assumptions, is capable of managing the political conflict and the informational and procedural shortcomings that accrue to organizational differentiation. Finally, we show that the creation of an independent group responsible for managing not forecasts directly, but rather the forecasting process, can stabilize the political dimension sufficiently to enable process improvement to be steered. We argue that these insights are generalizable and can be fruitfully extended to other settings that require such cross-functional coordination.