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Getting your food safety data to speak

Hear how the Western Growers Association is supporting members to advance food safety with data sharing.

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Identify company or industry-wide trends and risks that exist across your food production and supply chains.

Using data and scientific modelling alongside your existing food safety processes can save your organisation significant amounts of time and resources. But there is real advantage to be gained by viewing anonymised, aggregated data in order to identify company or even industry-wide trends that may exist across supply chains, that they could not have picked up from their own internal testing only – the wisdom of the masses as such.

 

Compare with industry benchmarks and ultimately keep consumers safe.

 

Even simply being able to confidentially view your own data in relation to where you fit with the overall industry can be very insightful for companies.

 

The barrier is typically not technology, it is the business value proposition. Solve that and you solve the data sharing challenge.

Creme Global's mission is to enable better decision-making in a complex world. Only by understanding what's happening in your business today, can you predict the future.

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Find out more about

  • How to gain key business insights to identify and manage emerging risks early.
  • Comparing your data with industry benchmarks.
  • Identifying industry trends for future market expansions.
  • Keeping consumers safe.
  • Reduce the risk of recalls and product holds.
  • What is a Data Trust?
Getting Your Food Safety Data To Speak - Western Growers

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Hear how the Western Growers Association is supporting members to advance food safety with data sharing.

See our solutions and services for food manufacturing, safety and nutrition.
Creme Global combines its deep scientific expertise with the world’s most accurate and user-friendly models that support regulatory requirements, risk assessment and root cause analysis.

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Data Sharing on Creme Global Platform

Gain critical business intelligence
from shared, anonymized data.