Blending Human Workers and Robots

Since the birth of mechanization, humans have tended toward a mix of fear and curiosity when faced with any new technological movement. Collective anxieties about our relationship with machines have shown up in popular culture since the turn of the 20th century — take Metropolis, Blade Runner or the Terminator franchise. Today, as automation presents solutions to a host of supply chain problems across industries, workers are again wondering how they will fit into a more mechanized world.

Fortunately, the dystopic scenarios of cinema are far from reality. In practice, humans are hardly at risk of being phased out, but instead are poised to take on more desirable roles, leaving the physically taxing, repetitive and even dangerous tasks to the machines. Automated processes not only have the ability to solve supply chain problems such as labor shortages and changing customer demand, but can in fact improve the safety and quality of life for the human worker.

A New Kind of Co-working Relationship

According to Kevin Massey, senior director of strategic analytics and data science with Ryder, many supply chains are relying on “cobots,” robots that work alongside and in relationship with human employees, always prioritizing the safety of their living coworkers. “You're seeing more integrated systems being put on robotics, like vision or proximity sensors that allow the robot to know where the human is, so it can actually steer clear of the human being,” Massey says. “It's not unlike what you're seeing today in the world of autonomous vehicles.” The days in which machines had to be locked away in cages to protect humans from injury have long passed, beckoning in a new type of co-working space where humans and machines can maneuver a warehouse floor together without harming one or the other.

The key to a symbiotic relationship between the two species of workers is in the division of labor. Certain jobs are best suited to machines due to the repetitive nature of the task and the high risk of human error. For instance, kitting, the process by which two or more products are combined into one package, is both repetitive and prone to mistakes that could hold up an entire operation. “Humans are good to a point, but most often we either put the wrong features into a package or include too many or too few,” Massey says. “You have a lot of error-checking when there are humans involved, and robotics helps us solve that type of problem.”

Seasonal changes in labor similarly lend themselves to automated solutions. “We can staff up during the peak season more easily with robots,” Massey says. “They can actually help humans gain more efficiency.” Relying on bulk machine rentals during the busiest times of the year avoids the added time-cost of training new waves of employees and fosters a sense of consistency among the human staff.

When it comes to complex problem-solving, however, humans remain irreplaceable. “Anybody who’s been in a warehouse knows there’s always some kind of urgent matter happening,” Massey says. In these instances, as warehouse employees scramble to get the right product out the door, only a team of humans can collectively solve each problem as it comes. While machines are ideal for repetitive, error-prone tasks, humans have one thing their automated counterparts have not yet, and may never, truly match: the ability to adjust on a dime.

Data Analysis With a Hybrid Workforce

On the backend, machines are also improving how we collect and manage data, but still require a human eye to determine how that data should be used for strategic gain. Massey recommends having a dedicated plan in place at the front end of the collection process. “If you’re going to be generating data, you need to know what you want to accomplish with that information,” he says. “What is my key function, how do we support it from an analytics and data science perspective, and how do we get that information in to solve problems?”

In the case of predictive modeling, once the automated models collect and analyze the necessary data, Massey adds, it’s important for the human to understand the mechanics of how the system arrived at any given conclusion. “If you're really looking to problem-solve, optimizing how that model makes its decisions is actually going to give you more key insights into how to change your processes and gain even more efficiencies in that flow,” he says. Given the infinite amount of data available, it’s essential to outsource the collection and sorting of it to an automated system. But numbers are useless without a human-developed strategy for how to leverage, process, and act on the information those numbers provide.

Ryder Paves the Way to the Future

As we look ahead to the future of automation, Massey believes we’ll continue to see myriad versions of human–machine relationships in workspaces, each with unique applications and executions. “Machines are going to work completely alongside the human being,” he says. “We’re going to see things like drones that can hover above the facility, taking on tasks such as counting. That’s really going to help optimize the flow of a warehouse facility.”

Advances of this nature are far from new to the supply chain experts at Ryder, who have a long history of significant strides in the technology space. With their program RyderShare, launched over a year ago, they’ve been able to digitize end-to-end supply chains, giving customers a competitive advantage in a technology-driven world.

They’ve also been heavily involved in the optimization of labor management, solving global supply chain problems such as labor shortages and skills gaps.

Through its strategic use of technology solutions, Ryder has been able to get ahead of the game through analytics and automation. “We're using the latest data science to better understand how we attract and retain labor in our forces, in our warehouses and trucking,” Massey says. By using human insight to develop a data strategy, along with automated processes to collect and optimize that information, Ryder has been able to make the most of its analytic capabilities to create tangible gains for both its own workforce and that of its customers.

Logistics providers of the past used to be almost exclusively concerned with physically moving products from point A to B, often using technology as a supplementary tool. Ryder is looking beyond, to a future where machines are no longer an afterthought but a central piece of the larger supply chain puzzle. “It's very different from where we were 10, 20 years ago,” Massey says. “And data really has taken over how we view our business. I think it's taken over how people view other businesses as well. It really becomes the currency in which we need to function.”

Through high-quality data strategies and forward-thinking labor management, Ryder combines the best of humans and machines to solve supply chain problems for its customers both now and into the future.