Case Study - Live Exports

Unexpected patterns in their own data flipped long-held assumptions—and transformed how they ship.

Live food exports come with the accepted risk of mortalities or defects caused during transit. The client, and their customers, were accustomed to sizeable portion of volume being subject to mortality claims. This typically amounted to millions of dollars a year in refunds paid to customers.

In addition to extensive discussions with their team and logistics partners, we used the client’s own data (sales, compensation claims, data loggers, product source, handling methods, packaging types) as well as external data (flight times, air temperature, humidity, even moon phases).

Our multivariate analysis turned up a number of surprises that broke from the traditional logistics practices that had prevailed for many years at the company. Among them:

Rather than 'the colder, the better', data revealed a clear 'Goldilocks' temperature zone for their product. Temperatures above and below this range resulted in increased mortalities.
Mortalities were much higher when using the client's preferred airline, due to their cargo hold temperatures being too low and longer transit times compared to competitor airlines.
An unexpected mortality factor was humidity - dry air, combined with cold climate in some months was causing mortalities to spike at times of peak demand.
Consistent with mātauranga Māori, the phase of the moon during harvest was clearly associated with fluctuations in mortalities later in the product's journey to market.

The resulting changes to their SOP, staff re-training and clearer expectations communicated to logistics partners resulted in over 50% reduction of mortality claims, saving the company over $NZ1.5 million per year.