Automatic Forecasting Systems Announces Release of AUTOBOX 4

NEW YORK--(BUSINESS WIRE)--

Technically agressive companies such as Anheuser-Busch, Coors, Coca-Cola of New York Inc., have been using AUTOBOX for years to drive production systems. This new version combining all the strengths of previous versions with Windows is an outstanding achievement.

AUTOBOX is a state-of-the-art forecasting engine that uses Box-Jenkins modeling techniques enhanced by Intervention (Outlier Detection) schemes. These tools are both univariate and causal and can produce forecasts for large numbers of series with limited or no manual intervention.

Amy Nesbitt Waters, Manager of Sales Forecasting for the Coca-Cola Bottling of New York Inc. says "When we began the development of an automated statistically based sales forecasting system in 1993, Autobox was the only software providing the statistical sophistication our business demanded. The ability to incorporate numerous cross correlated variables (promotional pricing and major holidays) in modeling was the selling feature of Autobox. The statistical capability of Autobox has enabled us to develop extremely accurate forecasts which are confidently utilized by manufacturing. Once these weekly forecasts are reviewed and approved by each respective Sales Center they drive our MRPII/DRP systems. Customer service is our top priority. Accurate forecasting is the crucial beginning step in achieving exceptional customer service."

"There are extraordinary benefits to be achieved in Supply Chain Management through the use of sophisticated and flexible forecasting software packages such as AUTOBOX. Interestingly, one of the ironic aspects of the Box-Jenkins methodology, so well implemented and automated in AUTOBOX, is that while the steps of Identification, Estimation, and Diagnostics/Forecasting have to be applied rigorously by either an analyst or sophisticated software, the resulting models are almost always intuitively appealing, organizationally effective, and operationally insightful. David Reilly and his analysts have an excellent product for managing forecasts in the supply chain. While, in my opinion, the Box-Jenkins methodology is the most versatile of forecasting methods, there are some time series which may not be most accurately forecast with ARIMA model building techniques. However, AUTOBOX has outlier and event modeling methods that greatly enhance the general applicability of ARIMA/TRANSFER FUNCTION model building strategies. Also, when some time series do not fit the ARIMA/TRANSFER FUNCTION scheme, AUTOBOX has additional modeling capabilities such as Winters and classical regression procedures. This complementary group of several well executed forecasting methodologies provides an essential supply chain management tool."

Steve DeLurgio, Sr. Professor of Operations Management Henry W. Bloch School of Business University of Missouri author of Forecasting Principles and Applications, Irwin McGraw-Hill, Burr Ridge, IL, 1998.

AUTOBOX can generate forecasts using historical data and causal data. Current forecasting systems vary in their ability to automatically detect seasonality and general trends in historical data and to deal with unusual values. It is extremely important to be able to quickly identify changes in trends.

Demand forecasting is usually performed using some variety of moving average or exponential smoothing, probably with seasonal adjustment. There are many applications where these tools are cost-effective and satisfy the customers needs. Some customers have found a need for more robust methods which have the additional benefit of optimally incorporating cause variables because the past never causes the future. Autobox is a tool that has been characterized as being useful in dealing with unusual values or quickly incorporating changes in level or trend or detecting changes in response to company policies. For example, a 25% drop in price may not have the same effect now as it had when the product was first introduced. Statisticians refer to this as time-varying parameters.

Robust tools have become important as enterprises need to forecast at the SKU level and use point-of-sale (POS) data. AUTOBOX is an expert system and now embedded in an advanced data management system, such as Planner, closes the loop. AUTOBOX incorporates causal variables by detecting lead, contemporaneous or lagged effects.

This fine art even extends to cannibalization effects and even the price of competitors products. AUTOBOX can account for events like advertising and promotions, including lagged effects (e.g., reduced sales the week after a promotion ends) along with the best weighting.

AUTOBOX does not select a model from a user or system-defined set of models. To produce more-accurate forecasts, AUTOBOX automatically tailors the forecast model to each problem. and the best weightings. It corrects for omitted variables (e.g., holidays or price changes that have unknowingly affected the historical data) by identifying pulses, seasonal pulses, level shifts and local time trends, and then enhances the forecast model through dummy variables and/or autoregressive memory schemes.

At the same time AUTOBOX eliminates unneeded structure (e.g., a statistically unimportant causal variable) to keep the model manageable. These are all performed as part of its normal routine without human intervention. A wide variety of reports provide detailed information on the statistical tests used to determine the model parameters. Advanced users may manipulate the coefficients and model structure if they want.

Company Backgrounds

About Automatic Forecasting Systems

AFS is a privately held company founded in 1975. AFS was the first to launch a a radical piece of software for its time - a forecasting package that did automatically what was thought to be an art; Forecasting.

In the twenty plus years since its launch, AFS has continued improving it's heuristic based engine by adding features from the statistical journals. AFS' products, across platforms and interfaces, continue to be based on a forecast engine that has been programmed and tuned to do what only the best forecasters can do; build Box-Jenkins ARIMA and Transfer Function models.

AFS continually sets the pace for forecasting software. This includes both methodologies and in applications. As advances in the field are made, AFS has the depth of statistical knowledge and the practical programming experience to integrate them into its packages. Consistent effort is made to expand the products breadth of application into exciting areas such as production planning and inventory control and real time systems. For more information visit http://www.autobox.com or call AFS's headquarters in the United States at 215/675-0652.

CLICK HERE:Home Page For AUTOBOX