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EXECUTIVE SUMMARY
Studies show that 85 percent of a company's performance is affected by external economic factors. However, as companies make critical decisions on production, raw materials, staffing, marketing, and more, most consider only internal historical data in their forecasting models. Understanding how external factors can impact your business is the key to staying ahead in today's volatile market. This article discusses how combining external factors with the latest forecasting technologies and techniques can help to identify drivers to improve forecasts.
Big data and predictive analytics have brought demand forecasting more into the world of science than art. Unfortunately, many businesses still rely solely on intuition and the analysis of internal historical financial data in their decision-making. That's risking a lot, given that external influences drive as much as 85 percent of a company's performance. To survive in today's fast-changing and highly competitive global economy, organizations must consider evolving geopolitical and macroeconomic factors before making critical determinations on entering a new market, introducing a new product or service, establishing operations in a new geographic region, or shifting resources from one area of the business to another.
This vital real-time external information is not being used in generating forecasts. As such, extremely important intelligence is overlooked in strategic planning. Until now, companies had no way to gather external data and identify leading economic indicators for their demand patterns, much less analyze this cohort in relationship to their internal performance metrics, such as EPS (earnings per share), ROE (return on equity), ROI (return on investment), EVA (economic value added), and EBITDA (earnings before interest, taxes, depreciation, and amortization).
In today's extremely dynamic global business environment, it is crucial that organizations assess not only their internal information, but also the external data that can doom an otherwise sound business strategy. By leveraging predictive modeling to discern patterns and trends from large external data sets, companies can see opportunities to be seized or risks to be averted-especially when combined with internal performance data.
This type of integration is now possible, thanks to the algorithms imbedded in sophisticated predictive modeling software. For instance, external events such as slowing employment, reduced hourly earnings, and declining consumer sentiment may indicate a future reduction in consumer demand. For example, the combination...