Index
A
- absolute percentage error (APE)
- accountability, for unconstrained demand forecast
- accurate demand forecasts
- actionable information, versus data
- adoption
- aggregation, of data
- Amazon
- analytical outputs
- analytics
- about
- anticipatory
- applying to downstream data
- case study
- consumption-based modeling
- current state
- demand planning
- future state
- gaps and interdependencies
- predictability
- segmentation of products
- statistical models
- strategic roadmap
- analytics methods
- analytics technology
- anticipatory analytics
- APE (absolute percentage error)
- ARIMA (autoregressive integrated moving average)
- ARIMAX (autoregressive integrated moving average with causal variables)
- automated consumer engagement
- automation
- autoregressive integrated moving average (ARIMA)
- autoregressive integrated moving average with causal variables (ARIMAX)
- average forecast accuracy
B
- barriers, to adopting downstream data
- baseline history
- benefits
- big data
- See also data
- See also downstream data
- about
- actionable information versus data
- case study
- cleansing demand history
- consumer/customer orientation
- demand management data challenges
- demand signal analytics (DSA)
- demand-signal repositories (DSRs)
- downstream data
- eliminating information silos
- growth of
- how much to use
- sales & operations planning (S&OP)
- structured process supported by technology
- technology
- as a trend impacting supply chain
- bullwhip effect
- business priorities, core
- The Business Forecasting Deal: Exposing Myths, Eliminating Bad Practices, Providing ...
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