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Learning Curve for Order Selection

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jlieber2

Industrial
Jun 16, 2022
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I work in the food service industry, and am looking to conduct an analysis of what the true learning curve is for our order selection. It is a highly manual process (look at wearable RF device for pick location and quantity, travel to location, scan case, label case, place on pallet, repeat). I'd like to understand how to determine the amount of time before we can expect a new warehouse associate to pick at 100% to standard (the level of a "veteran" order selector). Is there a particular model that works best for this (Wright model?)?
 
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I would imagine that the model is secondary to the values of two inputs called for by the Wright model. Additionally, there is the complexity of the work flow itself, and its "naturalness" relative to normal behavior.

Just a nit; "100% to standard" is seemingly impossible in the short term, since that sort of achievement is asymptotic to that of a "veteran"

TTFN (ta ta for now)
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Wow, go and talk to people?!?! Why didn't I think of that?!

It's definitely a good idea to set a company standard with 75+ warehouses and over 20,000 employees with a 90%+ turnover ratio based on the anecdotes of a few employees. Let's not use empirical data and learning curve studies/models that have been extensively researched.

If these are the answers I can expect, signing up for this forum was a total waste of time. Good grief.
 
As much as I'd like to make a snarky reply;

Your top level floor supervisors see this as part of their jobs. They train people. They see the operators and get performance reports. They know the onboarding process. They know how long it takes an employee to go from useless to an independent worker.

There's probably a handful at each location who have this data at hand, now that we know this isn't a single warehouse in the middle of nowhere with 5 employees (since we got no context).

You might even uncover regional differences that a single corporate standard would negatively impact, and which a model would never account for or allow.

You might have already done this, but guess what? We only know what you tell us.

Good grief.
 
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