With ever increasing integration and disruption of the world economies, businesses of all sizes are increasingly impacted by external economic influence. It is no secret that economic and geopolitical events can have historic and long-lasting impacts. What might be more of a surprise is that these impacts on certain industries can be accurately forecast with the right tools and information.

Firms that understand this can predict how different macroeconomic scenarios will impact how their customers think and act (and buy). Thinking back to New Year’s Day 2020, all firms were looking forward to a year filled with optimism and a feeling of contentment in where they stood regarding the economy at that time. We all believed in our power of prediction.  But, in predicting how the year would play out, would any firm have had the foresight to see the utter dismantlement and economic disaster looming?

Systems that understand and apply historical correlation between economic indices and a firm’s revenues can be empowered to forecast future results. While insight derived from thoughtful conversations with sales managers, supply chain leaders, local business partners, key customers, and ‘others who may know’, data analytics an or financial analytics software can enable the elimination of errors, bias, reasoning, subjectivity, and assumptions that may miss key signals. Quite often, revenue forecasting is wrought with massive bias and noise from individual motivations. No one is immune from these cognitive missteps.

One foundational economic factor that has proven to be a strong baseline for prediction is the Gross Domestic Product (GDP).  In layman’s terms, the GDP is simply a monetary measure of the market value of all goods and services produced by a nation within a specific time period. Put another way, its everything we produced and services that we rendered. The formula is C + I + G + (X-M), which roughly means Private Consumption + gross private investment + government investment and spending + net different of exports and imports. GDP is typically communicated as a percentage and is shown as an annualized growth rate quarter over quarter. It can be shown with or without inflation (Real GDP).

AnalyticsFYI is an example of a data analytics system that smartly integrates GDP data forecasting with revenue forecasting. Using advanced correlation calculations, a forward looking forecast of revenues is derived, grounded in the work that leading investment banks, economists, institutes, and other experts publish regularly.  Having this framework in place is both a massive time saver (it’s like having an analyst in a box for a fraction of the price), and also provides piece of mind in the basis for forecasting – helping to keep projections grounded in the ‘bigger picture’. Companies without this feature in their analytics and forecasting would need to hire expensive consulting firms (or hire additional FP&A professionals) to analyze, track, measure, and advise. None of that comes cheaply.