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Are you looking for a
forecasting solution that is easy to use and saves
you a lot of time, yet improves forecasting reliability and
accuracy? Are you spending more time manipulating parameters in
forecasting models than actually producing results? Dont you wish
you could get the rolling forecasts you need more
accurately... inexpensively... and
faster and easier? Now you can with the
PEERForecaster Add-in for
Excel!
If you are spending a
lot of time and money manipulating rolling forecasting models with your
large-scale demand planning systems without getting reliable
feedback and simple answers, then we may be in a position to help
you get those analyses done more quickly and with greater
reliability.
Forecasting
technology has improved so much in recent years
that most demand forecasting software providers, including the most
dominant ERP software vendors, may have fallen behind in providing
improved rolling forecasting solutions in their systems.
In the
Certified Professional Demand Forecaster (CPDF) training
workshop, Delphus is offering PEERForecaster, a
FREE Excel Add-in with all the horsepower of a full-fledged forecast
modeling tool without the overhead commonly associated with many
forecasting systems. This is ideal for training and benchmarking
your existing forecasting tool box. The models include all the
well-known techniques from decomposition and simple smoothing, Holt
trending, Holt-Winters trend/seasonal models, damped trend
exponential smoothing models as well as the univariate Box
Jenkins ARIMA time series models. The algorithms for creating rolling forecasts and interpretations are well documented in the literature as State Space
forecasting models as well as the book entitled Forecasting:
Practice and Process for Demand Management coauthored
by Hans
Levenbach and J.P. Cleary.
A copy of this forecasting book is
also offered at a significant discount when you enroll
in the CPDF
certification curriculum for demand planners. The CPDF (Level I)
Workshop is a hands-on workshop that utilizes Excel Add-ins along
with PEERForecaster to re-enforce the modeling capabilities
of seasonal decomposition, exponential smoothing, rolling forecasts, ARIMA models and
the State Space modeling environment. You will learn how to use
techniques that have been proven superior to the conventional Holt
and Holt-Winters models.
The international M3
forecasting competition has established that the family of
"damped trend" models generally
outperform the more conventional models used for
forecasting trends and seasonality in historical data. This
information has been published in the peer-reviewed International
Journal of Forecasting. Yet, these models are rarely, if ever,
found in many of the mainstream ERP/SCM demand planning systems
available in the market today! | 
