Actually a lot of people are asking questions around the amount of waste created by Amazon as a result of this excessive packaging issue.
After all, it stands to reason that if Amazon right sized the packaging for the contents for my order and your order and the orders of the other 300 million Americans, then the whole system would operate more efficiently saving Amazon time and money and reducing landfills by x percentage.
But I recently saw an article about why Amazon rejects that obvious logic.
Because sometimes it makes sense for Amazon to put that toothbrush in a giant box because that will be the last box in the truck and will make the contents of the truck ride better thus protecting the contents of all the boxes.
In other words, Amazon optimizes outcomes for the whole system not the individual part. They look for the path to minimize waste across ALL bazillion Amazon orders, not just the one box showing up to my doorstep.
Under what other circumstances does it make sense to optimize for the whole system not the individual item?
Let’s look at one that’s relevant in the meat (or any) business: profitability. Take retailers who are price competitive on a small number of core items that consumers use as their proxy price barometer on all items. Retailers are price competitive on those core items, (maybe breaking even, perhaps losing money) but capture even more margin on complementary items in the store that the consumer will buy on the same shopping trip.
This approach maximizes profit per customer or profit per shopping trip, not necessarily profit per item.
One example of this is Costco’s price strategy with the rotisserie chicken to pull consumers into the store on the assumption that once in Costco to buy rotisserie chicken, they will buy much (much, much) more.
Retailers have mastered this art, but what about integrators, packers, further processors, distributors? The same principle applies.
The easy way is to look at revenue, profit, or any other metric at hand is to look at each individual item.
The better way is to take a portfolio approach to optimize for the entire system, not falling for the trap of the individual part.
The challenge of this approach is that it requires the discipline to make these assumptions explicit plus a system to prove or disprove the hypothesis.
How do you test your assumptions? How do you optimize for the whole system?
Check out these 9 critical success factors for making analytics initiatives successful.
This article was originally published on Meatingplace.
