A major auto components manufacturer wanted to improve their long-term vehicle demand forecasting to inform strategic planning decisions. The client also wanted to be able to test future scenarios to evaluate the impact of a variety of potential macroeconomic changes, as well as the impact of different product designs.

RSG applied several parameters and algorithms to increase the integrity of an econometric model that forecasted vehicle demand for over 80 countries. RSG then conducted quantitative research to collect consumer purchase behavior across 6 different countries. RSG used discrete choice analysis to model that purchase behavior adoption and increased the accuracy of several model components using the results of these analyses.

This effort allowed the client to evaluate different market scenarios based on tested parameters including the price of fuel and fuel economy by vehicle classification. The final probabilistic model accounts for the uncertainty associated with various inputs and reports a range of possible outcomes to help our client better understand the market and make more accurate forecasts.

RSG continues to expand and update this work, as market conditions change and new geographic markets are studied in-depth.