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Why Standards Must Come Before Shelf Life Prediction

Updated: Jan 20


There's a temptation in supply chain innovation to skip ahead.


We see the destination—real-time shelf life prediction, dynamic pricing based on freshness, quality-based routing that gets the right product to the right store at the right time—and we want to build the technology that gets us there.


But here's what we've learned: the technology isn't the hard part.


The agreement is the hard part.


Before you can predict shelf life across a supply chain, you need everyone to agree on how shelf life is measured. Before you can route based on quality, you need a shared definition of quality. Before you can exchange data between trading partners, you need a format both systems can read.


This is the unsexy work that makes everything else possible.



What HSSD is Actually Doing


The Harmonized Standards & Smart Data Escrow working group brings together GS1, ASTM International, retailers, growers, and technology providers to build this foundation.


Current workstreams:


  1. Certificate of Conformance — Standardizing how quality attestations travel with product through the supply chain

  2. Transportation Unit Identifiers — Creating common language for tracking units across different systems

  3. Transportation Status Codes — Defining what happened to a shipment and when, in a format everyone can use


These aren't abstractions. They're active deliverables with timelines and accountability.



Why this Matters for Retailers


The Retail Issues Forum made something clear: retailers are tired of technology solutions that require bespoke integration with every trading partner.


Standards change the math. When everyone speaks the same data language, integration costs drop. Pilot programs become scalable. The ROI case gets simpler.


But standards only work if the right people are in the room when they're written.



The Invitation


HSSD meets bi-weekly. Working sessions are open to qualified participants who commit to contributing—not just observing.


If your organization is waiting for "the industry" to figure out data standards, this is your chance to be part of the industry that figures it out.



 
 
 

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