The Promax PX statistical modelling engine is used to define both the Baseline and Promotional volumes that are used within all planning areas of the solution. Promax PX will store the Statistical Forecast separately so that an analysis of the Statistical Forecast vs. Manual overwrites can be performed.

The essence of advanced trade promotion management requires an understanding of consumer behaviour under normal conditions and during a promotion.  Normal conditions are generally considered as baseline and it is necessary to be able to de-construct the historical demand data to identify the component that makes up baseline sales.  Promax PX has a number of statistical techniques that assists the planner in identifying and modelling baseline sales.  These techniques deal with a variety of data quality conditions from advanced multi-causal statistical models based on point-of-sale information to user-defined baselines that maybe used for “new” products.

Multiple tools allow the creation of a baseline which includes seasonality and trend to which is added the effect from each promotion.

This technique has proven to give a higher level of forecasting accuracy with the least amount of effort from the users.

Promax presents to the supply chain management a forecast of ex-factory sales which has automatically incorporated the baseline and promotional uplift correctly timed to align with the promotional program.

Promax PX can use multi-causal models to predict the effect of price, catalogue, display or any other causal factor that is available to improve the quality of the uplift prediction.
A company adopting this approach to forecasting can expect significant improvements in forecasting accuracy over those techniques that smooth promotional effect into the baseline prediction.  The extent to which forecast accuracy can be improved is a function of the environment and business process however most Promax customers have received significant improvements in this area.

Promax PX provides users with the ability to specify trend adjustments that are applied to the baselines. They can also be manually overridden to adjust for growth and distribution changes.

Understanding the effect of price and volume is one challenge, however, an understanding of profitability is crucial to the most effective planning of promotions.

Promax PX creates a profit/price/volume relationship for every product/customer combination.  It identifies the discount at which maximum profit can be achieved and that discount level at which the profit from the promotion is the same as that achieved by not discounting.

Knowledge of these parameters assists the account manager in pricing.  As every product has a different curve.  Promax also assists in identifying those products that may be included in a promotion that have no response to discount.

Using Promax’s powerful optimisation technology the business planner can test the effects of changing promotion parameters such as frequency, pricing strategy and return on investment to determine the business outcome they desire.

A range of scenarios can be created for any selection of products and these can be compared to assist in the development of a business strategy.

Causal factors within Promax are user-defined.  Customer store numbers and store size weightings are valid options.