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Maximizing fleet operator resources as competition for drivers heats up again

Perhaps surprising no one, Schneider recently announced a pay increase for its drivers – on the homepage of its website no less. Many smaller companies have increased driver per mile rates for a while now, but with many carriers forecasting demand that edges ever closer to pre-pandemic levels, driver costs are on the rise.

A quick scan of the truck manufacturing numbers bears this out. In a recent article, American Trucker looks at Class 8 truck production as a strong economic indicator for the industry, and saw that net orders surged in September, hitting 32,000 units — the most since October 2018. September order activity is up 55% compared to August and 160% compared to September 2019.

With all that, the competition between carriers for drivers was bound to heat up. Freight Waves is openly speculating, with probable cause, that this opening salvo by a major operator is sure to spur its competition to match or even exceed the $0.61 a mile Schneider is saying its drivers can make.

Once the large carriers all join the pay fray, they will once again be forced to find other ways to retain drivers as well as rationalize and optimize schedules to increase driver utility. This means filling more orders and generating more revenue to cover additional per mile expenses, all while continuing to maintain other cost structures, as well as service and safety parameters.

Here at BoldIQ, we have seen that customers describe one of Solver’s chief benefits is its ability to maximize utilization of existing assets and personnel, and to do that in real-time. Solver’s preference-based scheduling harnesses the power of operational AI to optimize resources, loads and routes while considering regulations and business rules in real time. In the end, they push more orders through the same or even fewer fleet resources.

For example, in a recent case study we completed with an industry leading supply chain solutions provider, Solver improved order fulfillment by 11%. For carriers this means less spot market activity, clearly a cost saving measure, and for those with large dedicated and for-hire fleets, it also contributes to increased revenue.

Another carrier we worked with wanted to optimize an existing schedule by employing rules that prioritize giving drivers more nights at home as part of a driver retention strategy. This scenario will come likely into play in the new year as it becomes a “drivers” market.

Solver’s operational AI optimized resources, loads and routes while considering regulations and business rules in real time, increasing the total number of miles driven in the same duty shifts by 18.5% and the actual drive time by 18.7%. Preferred drivers were granted their preferred duty shifts and were able to pack more miles into each of those shifts. The result was more pay for valued drivers, and of course more nights at home if so desired.

The bottom line is that with AI optimization, carriers can balance duty hours for drivers evenly if that is the business priority or provide more duty hours to preferred drivers to increase driver satisfaction and retention. Additionally, Solver can prioritize company drivers and owner operators based on the fleet operator preference.

Importantly, Solver’s AI optimized scheduling generates an immediate increase revenue by deploying existing assets to fulfill a greater number of orders. Over a longer period, this results in a corresponding increase in revenue and profitability, and most critically, an edge in this increasingly competitive market beyond just a few cents more a mile.

Read the original article on LinkedIn

Work-life balance for truckers is key as driver shortage takes its toll

Breakthrough AI optimization technology for real-time scheduling shows that carriers are prioritizing drivers work-life balance while helping manage costs, service and safety for the company.

With over 70% of all freight tonnage being moved on the nation’s highways, most of the goods you eat, wear, walk on, live in and otherwise consume are transported on trucks. However, within the trucking industry, and increasingly beyond it, alarm bells are going off.

A driver shortage has been getting more severe over the last few years and is predicted to worsen. The American Trucking Associations (ATA) produced a study recently showing a shortfall of approximately 60,000 current qualified drivers in 2018. More critically, the average driver age is now at 46. While the industry is making efforts to attract a younger and more diverse workforce, success in this area has been limited. If the current aging driver workforce trend holds, the shortage will more than double to over 160,000 in ten years.

Importantly, the ATA study outlines how “qualified” means more than just a Class A license. The carriers continue to maintain stringent hiring processes, with safety and reliability being prime concerns. Moreover, traditional approaches for attracting and maintaining the best drivers, such as sign-on bonuses, increased compensation and premium rigs, are now mere table stakes. As a result, carriers struggle to find enough qualified drivers, which makes the impact of the shortage feel worse. Enterprising logistics executives are beginning to realize that these perks are just not going to be enough in the long haul. All the while these same executives need to consider costs, safety and service as well.

Interestingly, a quick survey of some of the threads in driver forums such as the TruckersReport shows that drivers place high value on more nights at home. A recent article in SupplyChain 24/7 backs this up, going on to say that providing an acceptable home-life balance for long-haul drivers is “no easy trick” .

As the shortage of qualified drivers intensifies, carriers look for more and different ways to attract and maintain these key business resources. An innovative approach sees leading carriers looking at advanced planning and scheduling solutions to give drivers more nights at home while maintaining cost structures, service, and safety parameters. Such preference-based scheduling harnesses the power of operational AI to optimize resources, loads and routes while considering regulations and business rules in real time.

Advanced planning and scheduling (APS) is rapidly becoming a key element of an overall ERP strategy for many mission-critical industries, where optimizing resources in real-time and on-demand amounts to smart business. In trucking, APS begins with preference-based planning, with all available trucks, drivers, depots and goods and their respective locations, enabling straightforward fleet, platoon, lane and leg-level optimization. This means more orders are pushed through the same or even fewer fleet resources.

As the usual day-to-day unfolds, unplanned maintenance, sudden cargo limitations, and even last-minute customer changes get a speedy response, all while considering traffic, weather, and of course, driver nights at home, in real-time.

We are just starting to feel the impact of this worsening driver shortage. Visionary trucking companies recognize the clear and present need to manage the challenges of attracting and maintaining drivers, a key business resource. Advanced planning and scheduling not only enables a good work-life balance for their drivers, but reduces costs, improves service and maintains safety regulations.

This article originally appeared on LinkedIn

Why surgery is so expensive

The latest developments in operational AI mean advanced scheduling and planning in real time and on demand is becoming a key element in the delivery of cost-effective surgical procedures with better patient outcomes.

Within the $3.65 trillion healthcare system, surgery is one of the highest cost centers, accounting for as much as 30% of that total, around one trillion dollars. This is a lot of money, but let’s consider all the aspects of a typical surgery: highly skilled physicians, nurses and support staff operating state-of-the-art equipment, requisite tests, medications, and surgical supplies, possibly implants too. Reliable pre-op and post-op transitions and care are key elements of every surgical procedure.

A health care center’s systems for case management, staff scheduling, lab, supply, and imaging all play an important role. Unfortunately, these systems are often disparate, and so data is gleaned and transferred manually from system to system. The surgery scheduling system is included in this mix, with its hourly, even minute-by-minute updates. And while some scheduling applications include staff skills criteria and equipment maintenance schedules, these are sometimes maintained on a simple spreadsheet. In the end, the actual live schedule may be posted on a whiteboard, requiring the daily surgery scheduling team to bounce between the various systems and sources, ensuring that all resources and processes are in place for each surgical procedure.

However, especially for large surgery centers, priorities are dynamic, and disruptions occur regularly. Emergencies arise. Procedures run late and so on. These not only have a cascading effect on the ongoing surgery schedule, but add overtime pay to the ballooning costs. Moreover, the operational staff are in a continuous catch up process, adjusting the various systems to reflect the dynamic situation. This leads to situations where surgeons, anesthesiologists and surgical nurses are waiting to enter the operating theater, as another procedure has run longer than expected. Delays like this are costly and negatively impact pre- and post-operative room assignments. And as the pre-op and recovery rooms fill up, the quality and consistency of patient care suffers too.

When the schedule is over-burdened, much needed breaks for the front-line medical professionals are often the first sacrifice. This despite the overwhelming evidence showing a rested, alert and coordinated team correlates strongly with better post-operative outcomes and shorter hospital stays, not to mention more satisfied employees.

It should come then as no surprise then that surgery is a major expense item in our health care system’s books. Skilled physicians and nurses and state-of-the-art operating theaters are premium assets. The business of healthcare demands that these critical resources be fully and optimally utilized, with a keen eye on improving patient outcomes every step of the way.

With the latest advances in operational AI, service optimization for surgical scheduling and planning sees the intricate operating room logistics iterated automatically as the schedule develops during the days leading up to the procedure. Throughout a day, as long-running operations and emergencies crop up, AI-optimized scheduling navigates the complex resource realignment in real-time and on-demand, while ensuring processes including mandated breaks are protected.

The paradox here is while science and medicine push the boundaries of what is surgically possible to save and improve lives, the complex set of resources and processes required to deliver these procedures lag behind. However, visionary organizations are beginning to recognize that AI optimization of these costly and critical resources with advanced scheduling and planning, they not only serve their bottom lines, but contribute to improved employee satisfaction and most importantly, better patient outcomes.

This article originally appeared on LinkedIn