The agribusiness problem

One of the limiting factors to accurate agribusiness market analysis is that complete regional supply and demand estimates are not available. These data form the foundation for agribusiness market research and therefore leaves a significant data gap.  Statistics Canada (STC) is the major source of agriculture supply and demand data in Canada similar to the role of the National Agriculture Statistics Services (NASS) plays in the United States. Although STC provides crop area statistics, livestock & poultry numbers by rural municipality (US county equivalent) every five years in the Agriculture Census, it does not estimate a complete supply and demand balance sheet for crops or livestock each year. This is similar to a lack of U.S. regional supply and demand data.

The only annual regional supply and demand data available in Canada are crop supply statistics (area and production) by Census Agriculture Region from STC.  The provincial level is, therefore, the most detailed and complete estimate of supply and demand available in Canada for crops and even then it is not entirely complete (i.e. feed, waste and dockage is estimated as a residual).  Although STC does not estimate agricultural regional demand, the Canadian Grain Commission publishes grain elevator demand estimates by grain delivery point, but the data is not current and can't be easily reconciled with Statistics Canada regional production data.  As a result, the underlying regional supply and demand picture remains incomplete.

This means that capital expenditures projects in Canada and the U.S. can easily be overbuilt or under built, both of which have long-term financial consequences.  In addition, revenue forecasting at the regional level is also difficult.  Click here to read a case study about the western Canadian grain elevator network rationalization.  It shows a major misallocation of resources that occurred primarily because of this data gap.

Our agriculture solution

Our solution is to build the missing regional demand data gap.  This ensures the foundational supply and demand picture is complete, which becomes the basis for accurately understanding and quantifying the complex nature of agriculture in Canada.  Trade Area Solutions has built this missing demand data for each of the major grains and oilseeds in western Canada.  These data are built using an advanced spatial economic framework which includes a GIS model.  The Spatial Grain Flow model allows Canadian Grain Commission major grain and oilseed deliveries by delivery point in western Canada (regional demand data) to be incorporated into a regional supply and disposition table.

The model incorporates these additional regional demand data by quantifying the grains and oilseeds trade area for each delivery point.  It differs from other more conventional analysis methods where only theoretical grain flows are estimated.  The model is a complex two stage model using both econometric and GIS techniques to model the major factors affecting grain deliveries (elevator size, freight costs, rail car spot, regional production and competition).  The model estimates the physical boundaries for grain elevator delivery trade areas by simulating the competitive interaction between delivery points.

The end result is a powerful new farm level supply and disposition table by rural municipality and/or by grain delivery point.  It is the first to estimate grains and oilseeds flows by rail and by truck. The model ensures spatial equilibrium at the regional level and therefore a level of accuracy and understanding conventional market analysis simple can't match.

Our market analysis framework offers the following abilities and advantages:

• Completes the foundational macro supply and demand picture for virtually all agriculture market research;
• Provides the framework for combining proprietary client data with publicly available data from various sources such as survey and customer point-of-sale data;
• It is the only technique that fully accounts for the impact of competitors. It can also estimate and compare the subject trade area with a competitor's trade area;
• Ability to analyze an entire market including the competition, not just a single factor or location;
• ideally suited for network planning and site selection studies because it identifies and automatically ranks market opportunities;
• verifiable accuracy.  The analysis framework can incorporate client point-of-sale data, the accuracy of the trade areas can be validated and verified;
• the analysis framework tests and analyzes for spatial equilibrium: market migration or the flows between trade areas is quantified as a separate demand layer;
• decomposable - since the framework and analysis process is based on an underlying supply and demand balance sheet, one can drill down into each trade area which yields a new higher level of understanding of market dynamics and improved predictive power;
• the analysis framework is closed. A closed system means that all supply and disposition of grains and oilseeds are accounted for within each rural municipality and/or grain delivery point;
• grain supply and demand analysis at a very detail regional level;
• a dynamic framework capable of modeling ‘what ifs’, such as changes in supply or demand, market structure, transportation policies or competition;
• short and long term forecasting; and

• other custom grain handling, transportation and policy analysis.