Data Mingling In Networked Supply Chains

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Data Mingling In Networked Supply Chains

I am a big networker.  I really enjoy mingling with new folks and exchanging ideas.  It is a great way to learn and expand your thinking. New opportunities are created by networking; or more accurately co-created.

 

Curiously, the words mingle and network come up a lot in my business these days.  The first use-case for our secure Big Data sharing solutions relates to digital supply chain transformation in the Aviation industry.  Supply chain experts use the term “network” to describe supply chain transformations that are or will be entirely data driven and focused on agile co-creation within the ecosystem.  Mingling is the process by which those datasets are used for co-creation.

 

For example, Adam Mussomeli who runs Deloitte’s digital supply chain practice says “The connected community allows multiple stakeholders—suppliers, partners, customers, products, and assets, among others—to communicate and share data and information directly, rather than through a gatekeeper.

 

Michael Hu, a leader in consulting firm A.T. Kearney’s supply chain practice, offers the same thought: “Effectively managing and coordinating supply chains will increasingly require new approaches to data transparency and collaboration.  In particular, access to transparent, accurate data is a prerequisite for effective supply chain collaboration and coordination. Lack of transparency is often born from a lack of trust or confidentiality issues.

 

In the context of our work with Big Data sharing and analytics, to mingle means to mix, blend, merge, or fuse.  To network means to engage, share and exchange resources.  Secure means doing the mingling and sharing without the potential for misuse.

 

Taking these points together, it’s easy to understand how a) securely sharing, mingling and analyzing transparent and detailed datasets owned by unrelated organizations is actually vital to drive digital supply chain transformations and b) overcoming trust and confidentiality issues that prevent such data mingling and collaboration is paramount.

 

That is why our secure data sharing software, SecureQuery, uses a Zero-Trust paradigm typically applied to network security to enable secure data sharing and mingling. Zero-Trust data security is the basis of our architecture that makes shared data sets self-governing so they can be mingled but cannot be misused.

 

Click here to read how our approach worked for our client’s digital supply chain transformation efforts, and why aggregated, obfuscated or masked data sets are not sufficient to drive digital supply chain transformations in the networked economy.

Randy Friedman

Randy Friedman is Founder/CEO of 4Dini Software

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