The process of recruiting independently-contracted drivers is essential and time-consuming for any business that operates a fleet of vehicles, especially in the last-mile delivery space. This includes screening, interviews, training, and an evaluation of drivers’ skills and qualifications. These actions guarantee that the company contracts the most qualified drivers to represent its brand and provide superior customer service.
Oftentimes, the general onboarding process can be costly and time-consuming, with a lot of churn. Traditional methods require extensive documentation, manual data entry, and in-person training, which can be inefficient, especially for smaller companies. This is where artificial intelligence (AI) technology plays a major role in the efficiency of onboarding tasks.
By implementing driver onboarding solutions powered by AI, such as Workstream, or Paradox, businesses can streamline the process and save time and money. By analyzing data such as driving history, qualifications, and background checks, AI can automate the screening process using these parameters. This enables recruiters to focus on the most qualified candidates while reducing the time and resources required for manual screening.
AI can also be used to tailor training programs to the capabilities and experience of individual drivers. This ensures that each driver receives the proper training to carry out their duties in a safe and efficient manner. At dlivrd, potential driver partners are required to successfully complete knowledge checks that determine which delivery opportunities they are qualified for. AI contributes to scoring, automating the subsequent onboarding sequence, and tracking metrics to understand completion rates.
Moreover, driver telematics, powered by AI, can provide real-time feedback and coaching to drivers in order to improve their driving abilities and reduce the risk of collisions. This reduces the likelihood of accidents and insurance claims, providing considerable cost-savings.
Lastly, driver onboarding solutions powered by AI can provide organizations with valuable data and analytics to optimize their fleet management strategies, saving time and money. This information can assist businesses in identifying areas for enhancement and making data-driven decisions to improve operations and the bottom line.