Data & Support
The Monthly Autocast’s forecasts delineate volume by individual model line and assembly plant over a six year horizon for every manufacturer operating in the U.S., Canada and Mexico. The scope of the report, therefore, far exceeds that of other automotive trade publications, and creates a comprehensive, yet easily workable, framework for planning.
To ease use of this vast pool of intelligence, each subscription offers the following elements of analysis and support:
This monthly report keeps you abreast of recent events by providing a written overview of the industry’s performance and analysis of how these developments will affect sales and production. Over 50 tables and graphs support this assessment, and provide a comprehensive forecast of the market’s future volume potential by OEM.
Model & Plant Forecast
Offered as an adjunct to the Industry Outlook, this forecast forms the core of The Monthly Autocast’s analysis through providing a detailed breakdown of North American production activity. Projections of volume by individual model line and assembly plant offer an independent appraisal of future volume, and highlight areas of growth and decline. Product program charts and plant capacity figures are also included.
Frequency: Monthly, Quarterly or Semi-Annually (As Desired)
Electronic Data Release
This on-line service delivers the Model & Plant forecast in a spreadsheet format (Excel) via the Internet to speed access and ease manipulation of the data. In addition, these data files are also expanded to include by-month estimates (12-24 months out) for every forecast series.
To assist with time-series analysis and executive presentations, The Monthly Autocast makes available several historical databases. These can be downloaded in a spreadsheet format (Excel) and include measures of production over the past fifteen years by model, platform and plant.
Unlimited consulting support by telephone ensures that you can always exchange views with a knowledgeable industry source or receive supplemental insight into the forecast’s underlying assumptions.