Labor Management Systems Get “Smart”
Labor management systems have started to expand beyond engineered standards by integrating machine learning and other capabilities that further enhance their position in the supply chain software stable.
As labor continues to hold its spot as one of the most expensive aspects of running a logistics and supply chain operation, the current labor crunch is making a costly endeavor even more difficult.
Currently, labor accounts for about 20% of a company’s supply chain expenses, according to a recent report issued by real estate services giant CBRE Group, and the average wage for a warehouse or DC worker was $11.82 an hour in 2016. Combine labor’s high cost and high need with the smaller pool of candidates to work with, or to pull from when business spikes, and it’s easy to see why labor is turning into a royal pain for many.
In response, many operations are turning to automated solutions—notably robotics—to drive throughput with a static number of workers. Others are implementing labor management systems (LMS), a blend of software and engineered standards that capture worker activity data to help define the most effective way to perform specific tasks.
“The use of LMS is heating up,” says Dwight Klappich, research vice president at Gartner. “Where, in the past, a company needed 200+ employees or ‘users’ to justify the time, effort and cost of buying LMS, these systems are now capturing information [e.g., every time an employee ‘does something’] and applying that logic in new ways. That’s making LMS more applicable for a wider range of users.”
Pointing to Easy Metrics as an example, Klappich says this new entrant on Gartner’s “Cool Vendors in Supply Chain Execution Technology” list is applying machine learning-like techniques in the labor environment. Machine learning, he adds, is a type of artificial intelligence that provides computers with the ability to learn without being explicitly programmed.
Why is this so cool? According to Klappich, the vendor is “expanding the market potential for warehouse workforce management (WWFM) solutions (aka, LMS).” “It offers an application platform and delivery approach that exploits the real-time data generated by warehouse management systems,” he says, “to replace industrial engineers that historically used stopwatches and clipboards to calculate goal times and planned work effort.”
Blurred lines
Used primarily within the warehouse’s four walls, LMS uses metrics to track productivity for individual employees or for groups of workers and is generally integrated with existing warehouse management systems (WMS) and other enterprise systems.
At its simplest, the applications help operations identify labor expenditures, optimize workforce productivity, and compare activity against established labor standards and their own internal, historical data. As Klappich mentioned, LMS is now stretching outside of its traditional boundaries by capturing worker and standards data, ferreting out valuable insights from that data, and then using it to help make smarter labor decisions.
“I think this is a step in the right direction,” says Klappich. “What it will do is allow companies of all sizes—not just 2,000-employee grocery companies—to operate more efficiently, and without the traditional issues associated with labor management.”
Historically, Klappich says only large shippers could afford to have two industrial engineers on staff, armed with stopwatches and clipboards. “They would walk about watching how people did stuff and conducting time studies,” he explains. “Then, that manifests itself into standards that they use to compare to actual performance.” He says Manhattan is one vendor that’s putting a bigger focus on using throughput versus just trying to align with engineered standards.
“Going forward, I think we’ll see some very interesting things that will allow labor to move down further into smaller organizations that want to enhance efficiencies, but that can’t afford industrial engineers,” says Klappich.
Turn a microscope into a telescope
Comparing warehouse labor to a science project, Klappich says that, historically, the industry has viewed warehousing through a microscope, like viewing an amoeba on a slide. This viewpoint provided answers to questions like, “How did we do yesterday?” “How many orders did we pick?” and “How did we do today versus yesterday?”
“It’s always looking backwards,” says Klappich. “What we need to do is flip the conversation, turn that microscope into a telescope, and really starting looking out in time.”
For example, a manager could be looking at the day’s agenda at 7 a.m. and say, “Hey, this is the work I need to do today, so I need more people in receiving in the morning and more people in packing in the afternoon.” And, if the right amount of human resources isn’t available during those times, the manager can also determine whether that will put any orders at risk, or not.
“This is where LMS is getting pretty exciting,” says Klappich, “by enabling companies to go beyond just comparing yesterday’s performance to a specific standard and allowing shippers to use the data to figure out how to run their businesses going forward.”
Wanted: Next-gen LMS
As he looks around at the logistics industry, Joe Vernon, senior manager of supply chain technology for consulting firm Capgemini, says a growing number of shippers are asking for next-generation LMS. That, he says, is driving a slight increase in adoption rates for the software.
“Logistics professionals want predictive and prescriptive solutions that not only show them how their labor is working, but that can also put the whole picture together and optimize workflows,” says Vernon. As shippers wait for the “next leap” in LMS to come into full focus, he says he’s already envisioning a time when warehouse managers can use the software to track equipment and forklift usage in the warehouse or DC.
“When you’re running a full shift, equipment and assets need to be measured and optimized [i.e., rates of speed, congestion on the warehouse floor] using technology like geo-positioning,” says Vernon, noting that the combined effort of “people and machines” that creates throughput efficiency should be viewed as a single, cohesive, productivity ecosystem. “Particularly as we move forward with robotics, labor management should play a part in that.”
In looking around at what vendors are doing to make that happen, Vernon points to Radial, an omni-channel tech and operations provider, as one company that’s “on the leading edge” of introducing science into labor management.
“LMS is no longer a reporting tool for workforce performance,” Radial’s executive vice president Sean McCartney recently told Vernon. “It has to be a wired, aware, intelligent, responsive, predictive and prescriptive solution, and it will be used to dynamically inform WMS and other systems to make adjustments to things like wave planning, sorter speeds and load plans.”
And this, adds Vernon, represents a true “blurring of the lines” between WMS, LMS and warehouse execution systems (WES). “It not only addresses labor utilization,” he says, “but also flow, optimization and employee engagement.”
Wired, aware, and responsive
With more warehouses and DCs assuming responsibility for a higher volume of orders that were once handled by their companies’ retail components—namely due to the huge uptick in e-commerce sales—the need for good labor management has become a focal point for many logistics operations.
“There’s a continuous need to manage and balance the labor force properly, particularly between retail fulfillment and e-commerce fulfillment,” says Norm Saenz, managing director at supply chain consultancy St. Onge Co. “Proper staffing and load planning are both important, and LMS can help with both.” As the complexity of operations continues to grow, Saenz sees LMS playing an even more important role in balancing and managing labor across multiple channels.
Calling LMS “a reporting tool for workforce performance,” Vernon says the next generation of the software is going to have to be wired, aware and responsive. “It’s really going to jump forward,” he predicts. And for operations that are either considering an LMS implementation or an upgrade to an existing system, he says: “Don’t be afraid to get started.”
“Sometimes, when working with customers, we advise them to wait a year until they really get to understand their operations,” says Vernon. “But because LMS can start pushing out valuable data immediately—something it really couldn’t do a few years ago—we’ve changed our perspective on that. And even if an operation doesn’t have standards in place right now, it can still look for patterns and find useful data to start working with.”
The warehouse-retail connection
Going forward, Klappich expects to see software developers like JDA continuing to leverage retail labor (i.e., the planning of people in stores) in the warehousing environment, which has traditionally been focused on scheduling and planning versus comparative analysis (i.e., “We have a problem with our pickers who aren’t meeting their plans”). Now, the same companies are using software to handle load planning and warehouse scheduling.
“Where warehousing was more about the comparative analysis, and then giving that information to warehouse supervisors to infer from that data the decisions that they needed to make,” says Klappich, “JDA, Manhattan and others are taking what they’ve done for the Walmarts of the world and applying it in the warehouse, and in a way that becomes more useful and actionable for supervisors.”
Manhattan’s DM Mobile, for example, combines data and functionality from the WMS and LMS to help distribution managers systematically record active interactions with employees, including observations and performance measurements, review work in the warehouse by wave, job function and task/activity, and other tasks.
“This allows managers to get out on the floor very proactively,” says Klappich, “and fix issues before workers get too frustrated.”
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