Stay Data™
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The Stay Data™ provided through the TCA Profitability Program is intended to serve as an industry benchmark for TPP participants. Carriers can compare their performance on key indicators of retention so that they can highlight their successes and find areas for improvement. These charts will be updated on a quarterly basis by Stay Metrics.
As the leader in driver retention solutions, Stay Metrics works with carriers across North America. It offers three types of surveys that span the entire driver-carrier relationship. Its Onboarding Surveys measure drivers’ engagement and expectations coming into a carrier and then checks in to ensure this relationship remains positive throughout the onboarding process. The Annual Driver Satisfaction Survey assesses entire fleets’ satisfaction and gives carriers actionable data on what strategic changes will improve overall retention. Finally, Stay Metrics offers exit surveys, acting as a third party to conduct confidential post-termination surveys for its clients.
Utilizing advanced data analyses, Stay Metrics reports on the overall state of retention in the transportation industry. The variety of its clients provides a unique sample that allows Stay Metrics to learn valuable insights about the entire industry. Its clients represent, in general, carriers who are tackling retention as a key strategic initiative. They include multiple Best Fleets to Drive For™ winners and 11 of Transport Topics’ top 100 carriers. Among truckload carriers, the average driver turnover for 2018 was about 20 percentage points lower than the ATA average.
Stay Metrics’ database includes several thousand drivers with nearly a quarter of a million completed surveys. The drivers are mostly OTR but also contains local, regional, LTL, and private fleet drivers. These drivers haul in each major transportation sector—dry van, tanker, reefer, and flatbed.
Tenure at Termination, 2018 vs. 2017
[chart 1: Turnover by Tenure Pie Charts]
Data for these charts come from the Stay Metrics database. It measures driver tenure at turnover by finding the number of days between a driver’s date of hire and date of termination. It should be noted that this measure is for all drivers who terminated with their carriers, regardless of when they were hired; therefore, some in the 365+ category could be, as an example, 10-year veterans retiring or drivers on their 370th day at the carrier.
What the data tells us
One of the most obvious problems with truck driver turnover is how early it tends to occur on average. Early-stage driver turnover has been a major focus of research by Stay Metrics for many years, including a recent research paper on the topic available for free on its website. Early-stage driver turnover is defined as driver turnover that occurs during the first year a driver is with a carrier. The 90-day and 180-day milestones are often used as key benchmarks to measure it. Addressing the challenges of early-stage driver turnover is key to a carrier’s success.
As can be seen by these charts, the driver tenure at departure did not shift significantly in 2018; however, there was a small increase in the total proportion of departing drivers with tenure under 30 days and slight reductions in the other categories. Using this as a benchmark, carriers who have either kept their proportion of under 30-day terminations the same or reduced them this year are outperforming the industry.
Where to go next
In general, terminations this early point to a mismatch between driver expectations and on-the-job realities. As a great first step toward addressing this challenge, Brady Trucking introduced a strategy that any carrier can implement, too.
This oilfield carrier introduced a pay expectation assessment process. Each new driver told the team what they expected to make. The carrier responded by telling the driver what exactly would be required to meet that expectation. The drop in early-stage turnover that resulted from clarifying expectations helped them reduce overall turnover by 31% in one year. Read their story here.
Stay Days Table
[chart 2: Stay Table]
The Stay Days Table measures how long drivers hired* in specific months stay with their carriers. Each cohort is followed, and the percentage of drivers hired in that month that remain at specific time points is displayed. Each month’s performance in terms of retention can then be compared to see changes to retention rates over time.
Can the next paragraph be off to the side or in a small box or footnote?
*A note on terminology: Throughout this document the term “hire” is used to represent the beginning of a driver’s current professional relationship with a carrier. The Stay Metrics database includes a mix of company drivers, owner-operators, lease-purchase drivers, and drivers for fleet owners. The term “hire” is used to denote when a driver starts driving with a carrier regardless of whether they were hired, contracted, subcontracted, or leased.
What the Data Tells Us
As can be seen in the table above, among drivers hired in January 2018, only 40% remained with their carriers for one year (calculated as 365 days). Looking at this indicator another way, the average number of days drivers hired in this month stayed with their carriers was 254.
This table can be used as an indicator of early turnover trends. It demonstrates how well the industry as a whole is performing on early turnover and serves as a benchmark for individual carriers. When each new month’s stats are released, we recommend comparing this table to your drivers hired that month to see if a higher or lower percentage of drivers are still with you today. Any carrier should be able to recreate this table for its own driver workforce from internal data systems.
Where to go next
The data from the current Stay Days Table is clear evidence that early-stage driver turnover is highly prevalent today. We believe the short length of time new drivers stay with carriers is a fundamental challenge to the industry. Those carriers that resolve it will increase their chances of long-term success.
Additional data on early-stage driver turnover can also be found in a recent Stay Metrics research paper.
Unmet Expectations
[Chart 3: Unmet Expectations by Tenure]
The data for this chart comes from responses to a two-part question on Stay Metrics Exit Surveys completed in 2018. Drivers are first asked if they quit due to unmet expectations at their carrier. If they answer yes, they are asked to select up to three areas of dissatisfaction. The chart shows the most common answers about unmet expectations and breaks down these results by driver tenure. It reveals how the reasons drivers quit change depending on how long they have been on the job.
What the data tells us
One of the interesting observations from the first version of this chart is that compensation seems to be more important for terminations between 31-270 days than for less than 30 or more than 270 days. Drivers that quit within 30 days were more likely to point to poor company culture, poor management, bad equipment, or a lack of respect as deciding factors. These factors seem to be more immediately apparent to new drivers, whereas factors like miles, loads, and home time become more determinative for drivers with longer tenures.
Where to go next
Exit surveys are one of the surveys Stay Metrics conducts for its clients. As a third-party administrator, Stay Metrics can often get drivers to provide more honest answers about why they left the team. These answers are one source of driver feedback that can help carriers learn more about where they can improve and help them on their journey to create driver-centric cultures.
Intent to Leave by Gender
[chart 4: Intent to Leave by Gender]
Intent to Leave by Haulage
[chart 5: Intent to Leave by Haulage]
The Stay Metrics Annual Driver Satisfaction Survey asks drivers the following question: “In the last six months I have considered leaving their carrier.” Responses to this question can be the following: Strongly Disagree, Disagree, Neutral, Agree, or Strongly Agree. A driver that responds by agreeing or strongly agreeing is more likely to turnover in the future, as they already have the preliminary pre-turnover thoughts.
The first chart compares men to women on these responses. The second one breaks responses into haulage groups. This report compares drivers with these categories of haulage: dry van, intermodal, refrigerated/temp control, flatbed/stepdeck/lowboy, tanker, and all others.
What the data tells us
While the metrics previously described have been based on actual turnover, this one is more concerned with indicators of future turnover. The data suggest that female drivers are less likely to be considering leaving their current carrier, meaning that we can predict fewer of these drivers will actually turnover than male drivers with a higher rate of intent to leave.
The chart on haulage type may be helpful to carriers in these specific sectors. Our analysis found that refrigerated/temp control and flatbed drivers were less likely to be considering leaving; whereas, intermodal drivers were most likely to have thought of leaving.
Stay Metrics’ research is continuing about the reasons for differences between drivers for future studies; however, carriers have the ability to examine results by sector to find the most relevant data for them.
Where to go next
Further analysis of this question is available at no charge through a report available on the Stay Metrics website. The report also segments the data by driver age, industry experience, driver type (company, owner-operator, etc.), and tenure at their current carriers.
Ease of Leaving
[chart 6: Ease of Leaving]
Just like with the “Intent to Leave” category, these scores are drawn from Stay Metrics’ Annual Driver Satisfaction Survey. This question asks drivers if they agree or disagree with the statement “It would be easy for me to quit this carrier.”
This chart compares the average score out of 5 (where 5 equals “strongly agree” that it would be easy to leave) of all responses among drivers who are active (still with their carriers) and those who are inactive (have subsequently left their carriers).
What the data is telling us
Drivers who left had a lower score than those who stayed. The research shows that across a fleet, this question is predictive of turnover.
The question of whether it is easy for a driver to leave his or her carrier is a different way to look at the data. Instead of asking if a driver has specifically thought of leaving, it assesses if a driver thinks switching carriers is an easy process. It serves, then, as another tool to identify risk factors for future turnover.
Where to go next
On this same topic, Stay Metrics CEO Tim Hindes recently released a groundbreaking theory on drivers leaving Because They Can. Because drivers seem to view the process of leaving as something they can do without much difficulty, carriers need to adjust their approach. If drivers can simply leave when they wish to, it is more likely that they actually will, so carriers’ responses to driver feedback and correction of problems identified are of paramount importance.
Ease of Leaving by Industry Experience
[Chart 7: Ease of Leaving by Industry Exp]
This chart uses the same data source as the previous one but segments its results by drivers’ industry experience. We define industry experience as the number of years a driver has worked in transportation at ANY carrier.
What the data is telling us
As you can see in this chart, there is a clear rise and fall to “ease of leaving” based on how experienced a driver is. New drivers do not feel they have a great deal of flexibility, but by the time they have 2-3 years of experience, drivers tend to consider leaving their carriers to be fairly easy. We notice that drivers in the 3-7 year range step back on this ease of leaving, but it steadily climbs again as a driver becomes more experienced.
This data gives carriers insights into which demographics of drivers are most at-risk of leaving based on experience. It also suggests that if a carrier hires a newly trained driver, they might consider offering some kind of additional benefit or recognition once his or her first year is completed to attempt to counteract the increased ease of leaving a driver experiences at that point.
Carriers should keep in mind that the ease of which a driver can leave is a combination of market forces and personal circumstances.
Where to go next
Because experience can make it easier for drivers to leave carriers, one of the most effective ways to counteract this tendency is to give the drivers something that makes it more difficult to leave. One of the most powerful ways to do this is to create “ownership.”
Ray Haight, retention coach with TCA and co-founder of TCA InGauge, is writing an ongoing blog series, the highlight of which for this topic is how it outlines a process whereby a carrier’s values can be shaped by its people, including drivers.
Part 1: The delusion of driver turnover
Part 2: Tackling driver turnover, Part 2
Part 3: Tackling driver turnover, Part 3
Haight recently moderated a discussion on this process with Geoff Topping (Challenger Motor Freight) and Mike Bash (Britton Transport) in a recent TCA Live Learning webinar. Mary P. Malone from Stay Metrics also wrote a blog summarizing this webinar.
Ease of Leaving by Pay Type
[Chart 8: Ease of Leaving by Pay Type]
Just as with the last two charts, this figure uses the responses from the Annual Driver Satisfaction Survey to how strongly drivers agree or disagree with the statement, “It would be easy for me to leave this carrier,” but this time segmenting by pay type.
What the data is telling us
In 2018, Pay type had an influence on how easy it was for drivers to leave a carrier. In general, drivers paid by ton/weight or component pay think it would be easier to leave. Especially compared to drivers paid by the hour and salary, who, on average, rate it more difficult to leave their current carrier.
This result might suggest that drivers think of salary/hourly pay models as more difficult to find on the market. This could also be a function of the type of trucking being done, as hourly/salary models are most often seen in LTL and local routes. These sectors tend to have lower turnover.
This topic is an ongoing subject of Stay Metrics research.
Where to go next
One of the best resources for pay-related questions is the NTI website This well-researched and authoritative site can help any carrier benchmark their pay packages and understand current trends.
The Stay Data™ provided here for TPP participants serves as the first-ever benchmarking data for driver retention in the transportation industry. Stay Metrics is excited to partner with TPP to provide this data, which will be updated quarterly. As its research continues, TPP participants will receive exclusive insights and the latest data.
One of Stay Metrics’ core values is “Never Quit Getting Better.” To that end, the data provided here will continue to evolve quarter-by-quarter. Your feedback or ideas for future areas of investigation are very welcome.
Do you want to be updated when new data is available? Fill out the form below to receive TPP Stay Data™ updates. You will also receive high-quality news, case studies, blogs, and other research reports directly from Stay Metrics.
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