Interactive, data-driven models solve five key problems when interpreting complex relationships where collaboration is needed (such as food supply chains):
1. Understood by Some, Not by All
It’s difficult to communicate the meaning of data to multiple levels within an organization, industry, or community.
— The value of a relational model lies in its ability to answer complicated questions with clarity. Presenting data that can be understood by all groups allows informed collaboration to occur.
Adding supply chain data is complicated; it requires three levels of processing: Collection, analysis, and visualization.
— The complexity of adding and managing data can be greatly reduced by using well-designed, user-friendly data entry tools, which allow records to be automatically analyzed, formatted, and incorporated into a live model. Complexity can also be distributed by crowdsourcing data from people, organizations, or the general public using the same data entry tools.
3. Artificial Barriers
Silos pose a significant challenge to collaboration. They exist not only between distinct industries, but also within individual industries (such as food). Numerous stakeholders need to converge on a common, purpose-built platform where collaboration can occur.
— Because it can aggregate data from diverse sources, a relational model is capable of providing a space for undiluted, evidence-based coordination across industries, or segments within industries.
4. Meet in the Middle....of What?
With inconsistent or incomplete information, collective decision-making becomes drawn out, compromises go unrealized, and strategies become disjointed. This ultimately results in a lack of direction and wasted resources.
— A relational model can collate, organize, and visually represent data from numerous channels, fostering synergy and creative thinking among stakeholders and focusing collective resources.
5. Incentives and Crowdsourcing
Without clear motivators, adding data becomes a low priority, especially for local organizations constrained by budget and time. The ideal system provides a simple-to-use interface and the freedom to enter as much or as little data as desired. Additionally, it needs to provide short- and long-term incentives for participation.
By including their data, organizations receive:
A no-cost system to track their own connections, find new opportunities, and understand their place in the wider network.
An opportunity to provide input and help guide future development of the system, to suit their specific needs.
An opportunity to support valuable research into creating a more resilient and inclusive network of local supply chains.