What are your thoughts? Please leave them in the comments.
When the Owner-Operator Independent Drivers Association Board of Directors meet in April, they will be seating five new alternate board members.
Every two years, OOIDA’s voting members cast ballots to elect alternates to the Association’s Board of Directors. Voting for the two-year alternate positions closed on Jan. 31 with five new alternates elected. On Feb 6, Bob Esler, chairman of OOIDA’s Nomination-Election Committee, announced the names of the newly elected alternates.
The new alternate board members are Linda Allen of Spring Hill, Fla.; Rodney Morine of Opelausas, La.; Brad Peterson of Brookings, S.D.; Danny Schnautz of Pasadena, Texas; and M. Carl Smith of Marysville, Ohio.
Linda Allen entered the trucking industry 10 years ago during the economic recession, when both she and her husband lost their jobs. At the time, her husband knew how to drive a truck so they both got their CDLs, bought a truck and obtained their own authority. Linda says she knew virtually nothing about the industry or the business at that time, but then she learned about OOIDA.
Senior OOIDA member Rodney Morine comes from a trucking family. His grandfather, his father and his uncles were all truckers. Rodney says he knew from the time he was 5 years old that he wanted to join the family trucking ranks.
Brad Peterson joined OOIDA seven years ago, because he wanted to belong to an organization that helps in all aspects of trucking. Brad reads Land Line religiously to stay informed on industry issues as well as follows trucking news and listens to Road Dog radio. He believes education is one of the keys to succeeding in trucking.
Senior Member Danny Schnautz’s love for trucking and his passion for the industry started much earlier than most. Danny’s father was a trucker, and the truck was Danny’s first daycare. He took his first truck ride at just 2 days old, and trucking has been in his blood ever since.
Carl Smith first joined OOIDA in 1983 and has been in trucking most of his adult life. Carl knew he wanted to be a truck driver at age 12. After high school, he joined the Army and learned to drive as part of his training. Carl bought his first truck in 1983 through a lease-purchase program with Riss International in Kansas City, paid off that truck and bought a new one in 1985.
The new alternates will be sworn in by OOIDA President Todd Spencer at the spring meeting of the OOIDA Board of Directors.
This is a great informational video that you can listen to with good information that needs to be circulated to all the drivers out on our roads.
If you combine this with the efforts that “Jason’s Law” you can see that things are going in the right direction on parking safety.
Trucking fleets of today are looking at far better margins than what they would have bargained for a few decades back – a scenario made possible in part by bolstering operations with technology. For shippers, terms like visibility and transparency get thrown around more often, which is in line with the meteoric rise of e-commerce and the consumer expectations that surfaced in its wake.
However, there does exist a disconnect in the rhetoric between shippers and carriers, as carriers struggle to keep up with demanding levels of customer service while also having an eye out for operational efficiency. Wise Systems, a startup based in Cambridge, Massachusetts, is working to bridge the gap by developing machine learning systems that automates dispatch and routing.
“Wise Systems builds a fully automated system that lets teams manage their entire fleet with cloud-based machine learning and artificial intelligence software,” said Allison Parker, Vice President of Marketing at the company. “We are getting deliveries done on time and as per plan, even if you’re managing fleets with hundreds of drivers with 20+ stops per day. Autonomous dispatch routing lets you plan, manage, and coordinate all aspects of deliveries with complete visibility.”
Parker mentioned that Anheuser-Busch, one of the staple clients of Wise Systems, has decreased late deliveries by as much as 85 percent after implementing the technology. “This is because the company now plans and manages all the challenges on the day of delivery that it might encounter – like traffic delays, weather delays, or something as location-specific as a blocked loading dock, would mean the driver can’t get in and make the delivery quite as planned,” she said.
“These are examples of factors that Wise Systems manages around, as it does not look only at individual deliveries and all the constraints associated with them, but also looks at the entire day plan of the driver, as well as fleets.”
Parker contended that the edge Wise Systems has over similar applications is its perpetual push to implement machine learning algorithms to every data set that is gathered onboard, helping predict and plan operations better. In addition, the company understands distinct roles in the operational construct, having an eagle-eye view over the delivery chain and focusing in particular on the role of the driver.
“Our system functions a bit like a relationship management platform for the driver, so that he or she can capture all the key bits of information about the locations they drive to. So, if someone is covering a location on a different day or when the regular driver is on vacation, the fleet owner knows everything about what’s going on there,” said Parker. “Based on this, we can understand a given driver’s performance at a given location, and if there’s variation, we can recommend over time which driver might be the optimal choice for future deliveries depending on how you’re building your schedule.”
Although at the core of its functioning lies a real-time data feed, the company also banks on historical data and third-party data streams that could help dissect an individual order. For instance, if a driver is delivering beverages to convenience stores, every store would have a different specification with regard to delivery time windows, and it is critical for the truck to deliver freight within the time constraint to avoid being penalized.
To be mindful of this is to understand the times when loading docks would be busy, the traffic flow within city boundaries, and personnel work schedules at the convenience store to have a seamless delivery process in place. “The system understands all this – when the driver arrives on site, how long it takes while he is there, and when he departs from the site,” said Parker. “This is where machine learning comes in, taking in all the different variables to not just be predictive but also be prescriptive by telling the user the exact outcome of a specific schedule.”
Wise Systems has recently raised $7 million in Series A funding from Gradient Ventures, the artificial intelligence-focused fund for Google. Parker remarked that the company has been very modest with its capital needs to date, which is indicative of it switching gears from research and development to growth of late. “We are now looking at product expansion as well as other operational roles that will help scale the company for the next few years,” she said.
Could this be the future for trucking? Something to think about& we will discuss soon.