In this week’s Logistics Insights podcast, using a statistical approach to Labor Management in distribution.
Labor is a hot topic distribution right now, with rising wages and labor shortages in most markets.
In fact, a recent survey by Gartner found that for the first time, addressing labor issues was cited as the top reason for investing in DC automation, surpassing reducing operating costs, the traditional driver of material handling systems adoption.
Labor management software can provide a variety of capabilities and benefits to address labor issues in distribution. The labor management software can be part of the WMS, or as a standalone system.
An important capability for labor management software involves advanced planning tools to determine the number of workers needed where and when throughout the course of a shift or even longer horizon. This is increasingly important given the shortage of workers on many days.
But the core of labor management is reporting of individual performance against some type of standard for each task they work, from receiving to picking and loading.
The labor management system should also track direct versus indirect time for each associate.
Sometimes, especially in the grocery and food service sectors, companies use what are called discrete engineered standards, in which industrial engineers study each type of task, such as say full case picking to pallet jacks, to identify the range of motions and travel each task requires.
Then as work is released, the labor system dynamically calculates a goal time for a given worker and task type. Performance and sometimes later incentive pay is then determined against that standard.
Full engineered standards have their place, but frankly we are seeing a turn away from their use. Why? In part because of the dynamic nature of today’s distribution environment, companies are concerned about the initial and especially on-going cost to develop and maintain those standards as things change.
Given that scenario, what’s the alternative?
Softeon has one. We call it a statistical approach to labor management.
Greatly simplifying, Softeon tracks a variety of data on each task type. We then publish that data as a bell curve of results across workers, along with measures such as the standard deviation of performance.
Here’s the thing: if the standard deviation is low, meaning the bell curve is narrowly spread, it means most workers are performing in a fairly tight range. That in turn indicates that using the average performance mark as the starting point for the standard may make a lot of sense.
Conversely, if the standard deviation is large, and the bell curve is wide, it means performance is highly variable for this task type – and someone needs to find out why before the data is used for standard setting.
In our experience, a high standard deviation often means the so-called “methods” used for the task by each worker vary considerably.
A statistical approach to labor standards – we like to say it delivers 85% of the benefits at 15% of the costs. That’s it for this week’s Logistics Insights podcast. Be sure to to learn more about our WMS and related Labor management software solutions – including use of simulation for planning activities.