Analyst Insight: Supply chain executives are developing their 2025 strategies to contend with inflation, economic slowdown, talent shortages, excess inventory and a continued level of geopolitical uncertainty. One thread of that is the barrier of trust within their complex supply chains. The lack of data transparency can lead to inefficiencies, increased costs and vulnerabilities. These challenges are compounded by a lack of standardized data sets, frameworks, and insufficient psychological safety and cognitive diversity.
Supply Chain Data Transparency: The Inconvenient Truth
Trust is pivotal in the supplier-buyer relationship and impacts data sharing within supply chains. Stephen Covey asserts that trust is both tangible and influential, affecting relationship management costs and the speed of accomplishments. He concludes that trust is hard, real and quantifiable, and affects both the speed and cost of a relationship. When trust is present, the cost to manage the supplier-buyer relationship decreases, while the speed or rate at which things are accomplished is accelerated. That said, as a supply chain professional, one should be asking these poignant supply chain data sharing questions: First, as a business owner, I need to understand what data is commonly requested by customers and whether it’s safe and advantageous to share. Second, as a manufacturer, I want to provide a safe and secure interface for my suppliers to obtain their buy-in. And third, as a supply chain pro, I want to understand the types of data sharing which are the highest-value-add and lowest risk to all parties.
Supply Chain Trust Matrix: The Secret Sauce to Success
Based on extensive literature searches and recent studies, one can conclude that supplier trust relates directly to the level of satisfaction suppliers have with their customer. Furthermore, supplier satisfaction with a customer correlates directly with a greater desire by suppliers to provide preferential treatment to that customer. Trust can potentially be modeled through the development of probability analysis with n-possible factors [e.g. frequency, criticality, risk, accessibility), leveraging Design of Experiments (DoE) principles with sensitivity analysis.
A trust matrix has been bandied about for a couple of years within the academic community. This would ensure that informed decisions can be made when prioritizing the data elements for all parties within the supply chain. This n-dimensional, non-linear approach to trust in the supply chain could help define how trustworthy the data elements are perceived to be across the supply chain, from suppliers’ suppliers to OEM manufacturers. Trust matrix survey results could also help us understand the key data elements associated with trust that could accelerate decision-making and drive added value. Results could be used to help identify risks, their levels of severity, and the root cause associated with the risks that act as barriers to full transparency.
Outlook: Supply chain sharing of data will be the secret sauce of success over the next five years. Success in this new, multipolar, geopolitical environment will hinge on fostering trust and transparency throughout every industry’s entire supply chain. A statistically strong trust matrix can provide a roadmap for organizations to evaluate and develop progressively increased supply chain transparency based on incrementally verified trust between trade partners.
Resource Link: www.thescrmconsortium.com
