Cracking the Code on Worker Sentiment in Trucking
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Increasing numbers of trucking companies are turning to artificial intelligence-powered worker sentiment platforms to assess — and act on — employee sentiment in the workplace.
Generally, these AI-enabled systems gather employee feedback or monitor comments on various communications platforms, such as Zoom, Slack and Microsoft Teams, then analyze what’s being said and offer insights on those exchanges for managers and human resource managers.
“With hundreds or even thousands of employees providing feedback, it’s difficult to step back and identify the signal through the noise,” said Katie Oliver, head of marketing at WorkHound, an anonymous employee feedback platform used by a number of trucking companies. “AI can help spot trends and correlations that might be missed when you’re in the weeds diagnosing one-off solutions.”
WorkHound differs from many employee sentiment monitoring systems in that it does not monitor all communications exchanged throughout a business. Instead, it only monitors anonymous feedback messages — often focused on grievances — which are posted on the system, analyzed by AI and responded to by management.
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Generally, WorkHound sets up the monitoring system at a trucking business by first seeking an executive sponsor for the platform to set sentiment monitoring objectives.
Next, a “quarterback” at the business meets weekly with a WorkHound representative to review data and trends and develop broadcast messages that go back to drivers.
Finally, a number of “dashboard users” are assigned to the system. They review worker comments daily and try to resolve worker issues. They also coach company managers based on the employee feedback they’re receiving.
Shawn A. Nelson, director of driver profitability at R.E. Garrison, said he’s impressed with WorkHound so far.
“We were surprised when we found out how many drivers we could help when we added WorkHound to our program,” he said. “We had been studying numbers and helping drivers and contractors that were struggling but had no idea there were so many that had great numbers but were still frustrated.”
For companies like R.E. Garrison, knowledge is the first step toward improvement.
“Once we found the issues affecting drivers, we could address them,” Nelson said. “We were able to get satisfaction by either repairing the issue or by educating the drivers on the processes.”
Ashley Cunningham, retention manager at PS Logistics, another WorkHound user, has had a similar experience.
“WorkHound is the best outlet in assisting with bridging the gaps of our driver communication,” Cunningham said. “Based on our feedback, we have changed some features and added new ones to improve the conditions of the network.”
PS Logistics ranks No. 28 on the Transport Topics Top 100 list of the largest for-hire carriers in North America.
One of the primary reasons AI is effective when it comes to employee sentiment monitoring is that the tech is perfectly suited to identify and offer deep analysis of patterns, trends, anomalies and areas of concern present in everyday employee communications, including those that might otherwise go unnoticed in the workplace.
Early adopters also find that AI monitoring enables managers of large, remote-working staff to get a behind-the-scenes look into what’s really going on with employees who are often scattered across the country or even world.
Plus, the best systems are the product of advanced collaborations between AI programmers and specialists in human behavior analysis.
Yet another bonus: There’s a good chance these monitoring systems will also save your trucking business significant coin if you’ve resorted to devoting significant funds on “bribes and Band-Aids” to help smooth over employee dissatisfaction.
“Your culture shouldn’t be built on expensive gifts, trips or catered in- office lunches — even though those can be fun,” said Erika Miller, content marketing specialist at Motivosity, another AI employee sentiment monitoring platform. “Culture is created through the connections you make with your team and day-to-day interactions. If you haven’t started already, work on making your company a place full of gratitude and connectedness.”
Some employee sentiment monitoring systems are anonymous, while some are not. (Transport Topics and Getty Images)
There are two schools of thought behind the design of employee sentiment monitoring systems.
Some, like WorkHound, take great pains to ensure that all monitoring of employee chats, emails, phone calls, video meetings, social media posts and similar remains completely anonymous.
The theory behind these “privacy-first” systems is that employees will feel much more comfortable being monitored — and much more prone to communicate sans inhibition — if they know that nothing they say will be traced back to their name.
But other systems operate on an entirely different philosophy, completely eschewing anonymity. These systems make no bones about the fact that each and every comment an employee makes will be tracked, archived and analyzed — and tagged with the employee’s name, title and department.
Such “no-privacy” systems are sold to employees on the promise that managers are not looking to penalize staff members who happen to be expressing negative thoughts or happen to be communicating negatively in some way now and then.
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Instead, no-privacy systems are programmed to identify specific sources of negativity in the workplace so that human resources and managers can focus on working with specific employees to turn the situation around.
Either way — privacy or no privacy — vendors selling AI employee sentiment software said customers should seek full employee consent and acceptance for sentiment monitoring.
Before you buy, you’ll also want to take a look under the hood at the day-to-day operations of these AI systems to ensure that the system you’re considering is at least analyzing:
- the kinds of words your employees are using
- the overall tone of your employees’ discussions
- the kinds of emotions your employees are exhibiting or expressing, including joy, happiness, surprise, anger, disgust and sadness
And you’ll also want to take a close look at the kind of reports the system you’re considering will be generating. Often, reports regularly issued by these systems are expressed in the form of generalized analytical graphs that are sometimes accompanied by analysis in text form.
Plus, many of the systems also can be programmed to generate out-of-the ordinary, anomaly reports designed to help you pinpoint when there is an unusual spike in a specific emotion at your business.
Moreover, no-privacy systems in particular can also furnish reports on specific employees who tend to be expressing mostly negative thoughts, which employees tend to have a high degree of negative interactions with other employees, which employees are having a tough time working with superiors or business partners, and similar.
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Companies opting for such reports often say they work extremely well as an “early warning” system for HR executives and managers, who can quickly spotlight the workplace problem — and then proactively work with the dissatisfied employee or employees with solutions, such as offers to join new projects or take advantage of new training opportunities.
As fleet managers know, offering such solutions can be much less costly than watching helplessly as a disgruntled employee quits — knowing they’ll be later forced to spend considerable time and money recruiting a replacement and getting the new employee up to speed.
Meanwhile, early adopters are also finding that both genres of systems are often much more effective than traditional tools used for employee sentiment assessment.
For example, many old-school businesses still use basic surveys to assess workplace sentiment, which are often augmented by interviews conducted with outside consultants who specialize in identifying workplace problem areas and improving overall employee morale.
Unfortunately, as many businesses have discovered, the downside to this approach is that employees often craft their responses to tell management what it wants to hear, rather than providing a true picture of what’s going on.
In contrast, over time, early adopters of the AI alternatives have found that employees tend to become comfortable with continuous AI monitoring of their sentiment, as long that monitoring is used responsibly.
And over time, early adopters have also found that employees tend to become less and less inhibited about what’s really going on with them, according to many HR leaders and managers who use the systems.
Peters
As with many things AI, some trucking industry veterans view the use of AI for employee sentiment monitoring with a mixture of fascination and caution.
JT Peters, CEO of Truck Driver Power, a driver app developer, sees the value of such systems — to a point.
“The context for the sentiment is critical,” Peters said. “Without context, sentiment analysis yields noise and requires empathetic follow-up communications to discover what’s driving the sentiment.”
Meanwhile, Jane Jazrawy, CEO of online driver training firm CarriersEdge, said any AI employee sentiment monitoring system would need to clear significant trust hurdles before it would be welcomed by workers in the trucking industry.
Jazrawy
“As we know from the implementation of inward-facing cameras, monitoring systems can easily be perceived as ‘spying’ on employees and are not popular,” she said. “The idea of ‘permission’ [to monitor] is also precarious — employees may feel that granting permission to be monitored is a condition of employment and they are at risk if they refuse.”
Obviously, you and the people at your trucking organization will ultimately be the best judge of whether an AI employee sentiment monitoring system is a good fit.
Fortunately, there are scores of systems in the marketplace you can evaluate. In addition to WorkHound, check out Lattice, Culture Amp, Vantage Circle, Workvivo and Motivosity for a representative sampling of vendors.
Joe Dysart is an internet speaker and business consultant. Voice: (631) 233-9770. Email: joe@customtechadvisor.com Web: www.dysart newsfeatures.com.
