‘What-if’ analysis drives profits and market share

Companies moving to a progressive demand-driven business model seek sophisticated analytics as traditional enterprise resource planning and supply chain technologies often fall short of expectations. Poor forecasting harms companies across all functional areas: lost sales, budget over-allocations, product obsolescence, overstocks and higher prices.

According to AMR Research, "demand-planning applications with innovative new capabilities, such as attribute-based forecasting, direct ties into sales and operations planning processes and integration of downstream data are driving market demand and causing firms to re-evaluate existing demand-planning and forecasting implementations."

Further, AMR Research estimates demand planning and forecasting will command a 12 percent revenue share of total supply chain management (SCM) application spending with a compound annual growth rate (CAGR) of 6 percent through 2011. (http://www.amrresearch.com/Content/View.asp?pmillid=20566

To meet the need for robust demand planning and forecasting, SAS, a leading company in business intelligence and predictive analytics, has introduced SAS® Demand-Driven Forecasting. Demand-Driven Forecasting integrates customer and other upstream data into a demand plan that helps maximize profits, market share and customer satisfaction. Implementing SAS Demand-Driven Forecasting helps users: 

  • Generate accurate, demand-driven forecasts using the right methods and models at any hierarchical level with SAS' patented Forecast Server engine.
  • Respond profitably to demand using "what-if" analyses and scenario modeling to gauge the financial impact of changes in marketing strategies or product mix.
  • Create more accurate automatic-weighted consensus forecasts that track variations between forecasted and actual numbers to help with sales and operations planning. 
  • Reduce finished goods inventory levels and stock-outs.
  • Measure and manage forecast performance by monitoring, tracking, reporting and surfacing alerts on forecast performance metrics.

Source: http://www.sas.com/news/preleases/060308/demandrivenforecasting.html