The Business Forecasting Process

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Business Forecasting What are the ramifications if one or more of your projections or forecasts do not hold true? What will you do if, during implementation, you find that you overstated your projections? How does sensitivity analysis relate to contingency planning? What are several risk mitigation strategies that you could implement to desensitize these variables? Of the many strategic and tactical uses of forecasting, the most critical from a cost standpoint is to mitigate risk and optimize potential revenue gains over time. The best forecasting frameworks and implementations balance risk mitigation and optimized revenue levels to stabilize the entire value chains of businesses (Hanafizadeh, Moosakhani, Bakhshi, 2009). The forecasting process over time can become an indispensable aspect of any broader strategic and knowledge management process including serving as a highly effective system of record (Kahn, Adams, 2001). Forecasting processes that resonate with reliability and serve as the foundation of their businesses also have tolerances defined to compensate errors in reported results (Jain, 2003). When a forecast is missed or not accurate, the best forecasting systems have tolerances or ranges of performance defined that can also be used for managing supply chain, production, pricing and services levels as well (Jain, 2003). The same holds true for overstated projections and the need for continually evaluated in terms of their reliability and validity. The
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