Advancements in Demand Forecasting: Methods and Behavior Defended on Thursday, 10 November 2016
The demand that drives various activities in the supply chain is inherently uncertain, necessitating the need for forecasting. Retailers require forecasts for sales, inventory and order decisions, suppliers for production and procurement decisions, and distributors for capacity allocation decisions. In practice, forecast errors are substantial, which negatively affects operational performance. Reducing or minimizing these forecast errors is central to this thesis and is achieved by improving the forecasting capabilities of companies, which encompasses extending the available forecasting methods as well as analyzing how the forecasting process, the context in which these methods and models are embedded, can be improved.
demand, uncertainty, forecasting, decision-making, biases, judgmental, incentives