What We Offer?
UBQ Freshness Index using Alpha Numerical Quality Code (ANQC)
UBQ’s Alpha Numeric Quality Code (ANQC) Freshness Index Co-pilot uses the real time cold chain data and machine learning to predict product quality upon arrival and estimate shelf life for different commodities.
The Freshness Index calculates the proportion of products sold within their preferred freshness period expressed as a percentage in day ranges.  Industry Average: 85%, Best in Class: ≥ 95%.
Our Big Data model allows causal analysis of pick to cool, supply chain shipment duration and temperature degradation on food quality.
These simple automations help optimize inventory and prevent food waste, driving efficiency and sustainability across the entire ecosystem from producer, receiver and consumer.
Business Case Outcomes UBQ Freshness Index:
Hard Benefits:
  • Creates causal analysis of pick to cool, supply chain and temperature degradation for food quality and shelf life.
  • Rank performance by carrier and trade lane to target downstream optimization of Dwell Time (inactive), Transport Turn time,  Delivery Dock Window +/- and OTIF.
  • Enables downstream optimization of warehouse, FIFO, last mile routing, in store merchandizing and promotions.
  • Guarantee compliance of mandated commodity temp range.
  • Swift corrective action to be taken to prevent product loss or damage. This leads to cost savings and improved profitability for businesses.
  • Optimize the inspection process to focus on those shipments that are at most risk from a food quality and food safety perspective vs. Random sampling.
Soft Benefits:
  • Better use of food QA resources and improved FTE and team efficiency.
  • Real time trackers allows in process adjustments; reefer, door openings, routing that reduces rejections and losses.
  • Trusted quality data sets enable supply chain SLA improvements; trade lanes, carrier, port calls dwell time, handling, cross dock warehouse, and last mile.
  • Improve product satisfaction for downstream stakeholders from receivers to consumers.
  • Potential to maximize revenue and reduce food wastage revenue for all parties involved in agri food value chain.