Promax PX Predictive Analytics and Multi-Causal Modeling
Trade promotions Management is most commonly considered is the ability to plan and track promotional events to ensure that the payments that are made to the trade are within the contractual, budgetary and policy constraints of the business. Trade funds (spend) is the bucket of money allocated by a business to fund discounts and cooperative activity with the trading partners (wholesalers and retailers) in the supply chain from the manufacturer to the consumer.
In assessing the effectiveness of the trade funds it is fundamental to understand two components of the demand signal;
1. Baseline Sales Rate – this is the forecast sales rate when there is no promotional activity.
2. Uplift – this is the sales rate over the baseline that occurs when a promotional event is implemented.
Trade Promotion efficiency and Trade Promotion effectiveness can only be assessed if data streams of these two measures are available.
To optimize the utilization of trade funds it is important to have reliable demand signal data available that is sourced from a point that is as close as possible to the consumer. In most markets around the world this data is derived from Point Of Sale (POS) devices and is commonly referred to as “scan data”. Unfortunately, this POS data is not available for every customer and product that is sold by a typical consumer products company. This being the case, how does a CPG business tackle the optimization challenge if a large proportion of the data set is missing?
This paper will shed some light on how Promax PX can conquer this challenge and provide a stream of quality multi-causal demand signal data on which predictive analytics can be used to optimize trade promotions.