Commodity Value Reporting and Analysis

Commodity Value Reporting and Analysis for Ontario Greenhouse Vegetable Growers


Formed in 1967, the Ontario Greenhouse Vegetable Growers (OGVG) is a not-for-profit organization that represents 220 producers of greenhouse tomatoes, cucumbers and peppers on 2,500 acres of land in Ontario, Canada. OGVG lobbies and conducts research on behalf of the Ontario greenhouse growers and promotes their products through a variety of media.

As a part of its mandate, OGVG reports to its members upon the price of each commodity on a weekly basis. It acquires the data for this task from reports submitted by the marketers of their members’ produce. However, each marketer reports their net pay in disparate representations and deducts different expenses; consequently, a level of normalization is required in order to arrive at a final net commodity price with a consistent meaning.

Business Problem

Prior to the introduction of Dattivo‘s software, these weekly commodity price calculations were completed using spreadsheets, paper, and manual calculations. Some of the challenges that this presented included:

  1. Since each marketer reported net pay differently with disparate representations of expenses, the calculation and normalization processes were completed manually and required a significant amount of time.
  2. Analyzing and reporting upon the data was a tedious task. In particular, a weekly report needed to be created manually. Custom queries typically also required the data to be assembled manually between the multiple spreadsheets.
  3. Not all data on the reports received from the marketers were able to be collected and tracked in the spreadsheets, making the analysis of the data almost impossible.

Our Process

We used an iterative approach in this project. We began the requirements gathering process with in-person interviews and an analysis of the reports submitted by the marketers. From an investigation of how commodity prices were normalized, we were able to first determine the minimum amount of data required to calculate the net pay to ensure that data entry would be as efficient as possible. Then, we developed a prototype to validate the results and receive feedback about our proposed logic and methodology.

After receiving and including user feedback, we designed and implemented a general model capable of representing the normalization logic for each marketer. Care was taken not only to ensure the accuracy of the calculations, but also that the user interface was able to be configured to exactly match the labels of each individual marketer report for both efficiency and accuracy purposes. Moreover, a database model was developed to store as much of the data contained in the marketer reports as possible. Finally, using the spreadsheets as a basis, a report template was created so that commodity data could be pulled on demand for any specified week.

Specific efforts were put in place to ensure trust in the delivered solution. Moving from Excel to custom software brings with it the risk that the users will not trust the new software since its operation is not as transparent or familiar. Consequently, Dattivo ensured that intermediate calculations were displayed so that the origin of all data was clear, the project itself was phased in one step at a time, and supplementary reports were created to provide further visibility into the final calculations.

Our Solution

Dattivo delivered a custom-built desktop application synchronized with a custom-built cloud portal to collect nearly all data from the submitted reports, automate the normalization of commodity prices, and generate reports with the click of a button.  Also, since all the data now exist in a queryable database, OGVG is able to efficiently track, compare and analyze all net pay data they receive. Over the years, further extensions to include tracking of self-marketers, late slips, and packing fees have been added to the system.

Solution Highlights

  • Custom-built desktop application synchronized with a custom-built cloud portal
  • Collaborative development process with continual incorporation of user feedback
  • Configurable user interface to match the wording and layout of any submitted report
  • On-demand report generation with easy export to PDF, Word or Excel
  • Reliable back-up functionalities built-in


  • Increased data entry efficiency
  • Straightforward data access for analysis and export purposes
  • Time required to assemble data has been eliminated by on-demand reporting
  • Quick, reliable, and safe data storage


Our Work