LMS Update: Expanding into networked labor management

Software that helps organizations manage their workforces, labor management systems (LMS) are used to orchestrate schedules, track time and attendance records, and generate workforce productivity reports.

Used by businesses of all sizes—and across most industries—LMS is especially useful for those that have complex, large workforces. In fact, very large workforces have historically been the “sweet spot” for this member of the supply chain management (SCM) software family.

Whether part of a larger enterprise system or operating as standalone applications, LMS helps companies improve workforce productivity by providing employees with the tools and resources they need to do their jobs effectively.

The software is also good at detecting workforce issues—high employee turnover, absenteeism, productivity problems—helping firms comply with labor laws (e.g., by tracking breaks and lunches) and forecasting labor needs.

The latter has become a particularly big selling point for LMS in this constrained labor market where warehouses and DCs often experience turnover rates that exceed 46%—versus 12% to 15% for all other industries.

According to Dwight Klappich, research VP at Gartner, LMS isn’t just for large food and beverage, CPG and wholesale distribution firms anymore. Where in the past the emphasis on engineered labor standards may have turned small- to mid-sized companies away from using LMS—which was more fitting for firms that already had industrial engineers on staff—the software is becoming more applicable for a broader range of users.

“Labor management systems presented in the ‘engineer labor standard-centric’ sense wasn’t expanding out into other markets due to a lack of deep industrial engineering expertise on staff. Now, we’re beginning to see companies adopt LMS across multiple facilities in a ‘networked labor management’ scenario.” says Klappich.

For example, the company that has 250 employees to 500 employees working in 10 different warehouses (25 to 50 per warehouse) probably couldn’t justify a sophisticated LMS for every one of those facilities.

However, the same company can use a cloud-based LMS for networked labor management and effectively gain visibility over its entire, distributed workforce. Klappich points to Easy Metrics and Longbow’s Rebus platform as two providers that are making inroads in this area.

Half labor management/half network analytics

Companies are also using LMS to gain a “half labor management/half network analytics” view of their operations and optimize both their human and equipment assets.

For example, if one DC has five pricey, high-reach lift trucks that are only being used 60% of the time, and another DC that only has three such vehicles being used 100% of the time, then reallocating those vehicles probably makes sense.

“We’re starting to see some LMS vendors say ‘hey, not only can we look at labor, but we can start to look at asset utilization as well,’” says Klappich, who’s also seeing more gamification being infused into LMS systems, versus using the applications as a tool for identifying the lowest-performing workers.

“A lot of companies realize that identifying and then jettisoning the bottom 10% to 20% of your workforce just isn’t realistic anymore,” says Klappich. “If you find workers, you want to keep them.” Knowing this, companies and software providers are both positioning LMS as a true workforce management tool. They’re focusing on employee engagement, offering performance-based incentives and awarding points to employees that meet or exceed expectations.

“Manhattan is one company that has added gamification to their LMS, so it’s not just best-of-breed providers that are doing this—the larger software developers are too,” says Klappich, who gives the example of the warehouse that’s dealing with moderate turnover levels, but that wants to incent its current stable of employees to improve their productivity.

With an LMS in place, the company can measure individual productivity, determine areas of improvement and then offer movie tickets or free pizza coupons to individuals who exceed their performance expectations for the week.

Other employees may be more incentivized by cash, and still others may work a little harder to be able to enjoy a paid afternoon off. These are all examples of the LMS-gamification connection, and they’re already being used on warehouse and DC floors nationwide.

Looking ahead, Klappich sees great potential for machine learning and artificial intelligence (AI) in LMS, which relies on a great deal of data and calculations. “An LMS likely has tens of millions of data points that vendors could start to leverage using machine learning algorithms,” he adds. “This is a great use case for machine learning, but the idea is still fairly nascent. A lot of people are talking about it, but no one vendor is offering this type of off-the-shelf system yet.”

Tracking key LMS trends

According to Michael McCullough, vice president NA, and supply chain lead at Capgemini, more software applications are using AI and machine learning to calculate and update engineering labor standards (ELS).

Defined as the expected or calculated time needed for a specific activity in any area and process in the warehouse (e.g., the time it takes to travel and execute a task), ELS are used to perform data-driven labor analysis in the warehouse. This helps companies ensure consistency, address inefficiencies, set and manage reasonable goals, and eliminate waste.

“Traditionally, industrial engineers perform distance measurements, time and motion studies, industry benchmarks, and spreadsheets to calculate ELS within a process. This is a very time-consuming exercise that results in a static standard that has to be continuously updated in response to process changes.” explains McCullough.

With the new AI and machine learning developments in this area, data-driven labor standards can be calculated by using data from a warehouse management system (WMS). The ELS associated with specific activities can be continuously updated, says McCullough, and outcomes of potential process changes can be simulated based on calculated standards. That way, companies know exactly how any projected changes will affect overall warehouse labor efficiency.

“Although a select group of leading WMS and LMS vendors can offer this increased functionality, many others identified the opportunity and have included this in their development roadmap,” says McCullough, who sees cloud-based LMS solutions becoming more popular.

The main draws include ease of use, flexibility and cost-effectiveness. Cloud-based solutions also allow for remote access and real-time updates, which are particularly useful in today’s fast-paced work environment.

Finally, McCullough says the use of automation in LMS solutions is helping organizations automate tasks like scheduling, tracking, work assignment, process engineering and performance management. “This helps reduce manual errors and increases efficiency,” he adds.

Three other areas where LMS adds value in the warehouse or DC include the following:

• Schedule optimization. By analyzing historical data and employee preferences, machine algorithms can optimize employee schedules while considering the workload, shift patterns, and labor laws. This ensures that employees work efficiently and that managers maximize their resources.
• Predictive analytics. When powered by AI, LMS can analyze vast amounts of data to identify patterns and trends. “This information allows managers to predict labor needs, forecast demand, and adjust schedules accordingly,” McCullough explains. “Organizations can effectively plan for peak periods, avoid overstaffing and minimize labor costs.”
• Compliance management. LMS can also assist organizations in complying with labor laws and regulations by automatically monitoring and enforcing overtime rules, meal and rest breaks, and other labor-related policies.

Another factor driving LMS adoption right now is availability and affordability of technology as a whole—including cloud-based solutions—which make LMS more accessible to small and medium-sized businesses.

Looking ahead, McCullough expects LMS providers to continue innovating and upgrading their platforms to adapt to the evolving needs of today’s workforce.

Industrial engineer-in-a-box

As technology advances and more AI and machine learning are embedded into LMS applications, new doors will surely open up. For example, companies may be able to pinpoint the real effects of worker fatigue and then come up with ways to minimize it.

Using machine learning, a company could look across 10 million transactions and realize that worker performance starts to decline around 2 p.m. every afternoon. And knowing that performance at 3 p.m. will never match what is it at 7 a.m., the organization can adjust its standards to more realistic levels that factor in the fatigue.

“This is the kind of stuff that industrial engineers can do on an individual basis right on the warehouse floor with a stopwatch and a clipboard, but it’s considerable harder to do at scale—across those 10 million transactions,” says Klappich. “At some point, that’s what machine learning is going to be able to do. It’ll be like industrial engineer-in-a-box at scale.”

Klappich also sees LMS potentially playing a larger role in the automated warehouse, where companies can use current performance to gauge their future automation needs. Skip this step and you may wind up automating a function or area that’s already running effectively on all cylinders and performing well.

“Maybe there’s another area of your business where you’re less effective,” says Klappich. “That’s where you’d want to leverage automation or robotics. We’re definitely seeing an increased interest in using LMS for that purpose.”