Consider a small-scale cheese producer in rural British Columbia. When summer starts, and production increases, they end up with surplus cheese that their local market can’t absorb. High transportation costs make reaching distant farmers’ markets financially unviable, leading to wasted food, resources, and lost profit.
Many organizations, industries, and communities face challenges when trying to understand and visualize complex relational data, such as those found in supply chains. Traditional tools like geographic maps offer only a single perspective for representing complex relationships, often failing to capture nuanced details and valuable information. This can ultimately lead to missed opportunities and collaboration. Additionally, the conventional methods used for data collection and entry often lack user-friendly interfaces, which can deter individuals and organizations from getting involved.
The aforementioned cheesemaker could use their local food supply-chain model as a tool to identify opportunities to collaborate and become more efficient. By applying filters to the model for refrigerated transport, weekly trips, farmers’ markets, proximity within 15km, room for additional products, and availability from June to September, they could quickly narrow down and identify potential neighboring producers with a refrigerated truck making weekly trips to regional farmers’ markets. In this way, the model facilitates connecting directly with each other, enabling the cheesemaker to access broader markets, and the neighboring producer to expand their reach due to shared transportation costs. This arrangement not only provides more local food options for residents but also helps control costs for the 2 businesses, increasing profitability. In addition, by making the transportation of goods more efficient, there is a net positive effect on the environment through reduced fuel consumption and emissions and less food waste.
Our models incorporate traditional geographic maps as one component, but expand beyond this perspective by also visualizing intricate relationships between the different roles various organization types play within the supply chain such as transportation companies, producers, community non-profits etc. The various perspectives can aid in identifying potential or existing loops and circularity within regions, industries and even between apparently unrelated sectors. This approach allows for a more comprehensive understanding of the network, fostering informed data based decisions and more effective collaboration. Additionally, our models incorporate user-friendly data entry forms for quick and easy data addition, with automated formatting, analysis, and display. This helps overcome the complexities and streamlines data entry, especially when dealing with crowdsourced entries.
Models range from straightforward designs with a few elements and only one layer, to elaborate systems with multiple layers and views, representing thousands of elements and connections. Built with either crowdsourced/real-time data, a static data set, or a combination of both, they are adaptable for a wide variety of applications.
Whether you’re a small business seeking local collaborations, an educational institution conducting research, a regional organization aiming to boost your local economy, or a community looking to optimize its supply chains, our models are customised to address the unique challenges presented by your industry, geography, or organizational structure.
We go beyond data management by cultivating meaningful relationships with organizations or agencies that have a deep understanding of their region or industry and are invested in its future prosperity . This strategic approach guarantees the effective use of our tools, maximizing benefits for communities and contributing to regional growth and prosperity.
Our models are designed to be constructed for an initial build cost and then continuously developed and maintained through an annual subscription fee. Our pricing structure takes into account the diverse complexities of our models, ensuring accessibility for organizations of all sizes.
Participating organizations who contribute data enjoy a range of benefits, including free visibility and optional inclusion within our expanding network. Additionally, they gain access to a complimentary system that allows them to track their own supply chain, identify new opportunities, and exert influence over the future development of the system.