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AI and Machine Learning for Transportation organizations

AI and Machine Learning for Transportation organizations

In a 2020 SPEDSTA survey of 150+ organizations providing transportation services to the elderly, special needs, and disabled community the #1 problem encountered was recruiting and retaining drivers and service providers. In the post-COVID era, this problem now impacts every part of the organization – from coordinators, managers, dispatchers, and volunteers. The figures are striking – wage inflation of up to 5%, staff demands to work remotely, multiple job offers for candidates to choose from, staff demands for skills development, and erosion of interest in service work –  finding and retaining staff is hard.  New techniques and tools will have to be invented for this new workforce to proactively recruit, retain and engage them. One very promising candidate is AI (Artificial Intelligence) and Machine Learning which can help organizations learn and proactively take actions to not only retain their staff but get even more out of them.  Take a peek below at how SPEDSTA’s AI and Machine Learning software is helping organizations better engage with their community.

Recommendations and referrals from existing staff are a low-cost way to be able to refresh and recruit new drivers and service providers. Given your best-performing drivers, it is a high probability that they will also recommend or know other drivers that would be similar in culture fit, work ethic, etc.  SPEDSTA’s machine learning software helps by analyzing key profile data, messaging patterns, and statistics to help organizations identify those service providers and drivers that would be ideal candidates for referral campaigns. An example referral campaign would be to email or SMS to those targeted candidates with offers of awards, points, Starbucks gift cards, or other incentives to refer people they know to your organization. 

Once you have recruited and trained new staff, the task now goes to retaining these recruits for the long term. Losing staff is a sure way for your organization to reduce overall effectiveness to your community, to use your hard-earned dollars in non-value-added ways, and to experience service disruptions for your clients. To monitor the health of your staff’s attitudes toward their work, the pre-modern day approach is to have one-on-ones, quarterly reviews, and meetings to assess their attitudes. Although these are valuable processes, they tend to have 2 flaws: the 1rst is that gathering this information takes time and is usually not done in real-time when problems are happening and the 2nd problem is that what people usually say is different than what they usually do. A more modern approach to keep a pulse on staff attitudes is to use already available real-time data that is being generated daily by your operations.  SPEDSTA helps by performing sentiment analysis on communications data and analyzing key performance metrics to gauge whether staff is happy, neutral, or in need of intervention. Using AI in this way, organizations are most proactive in keeping staff happy and with the least time, effort, and cost.

Most organizations that provide transportation services to the elderly, special needs and disabled population have limited budgets and use each dollar in the most efficient way to provide rides. In most cases, these rides provided are subsidized, free, or at a cost that is affordable given the client’s needs. Most clients though given a good service will tend to have an affinity to that organization and will want to give back in some way to these organizations. By using SPEDSTA’s Machine Learning software to analyze ride data, routes, locations frequented often, and communication messages a host of new ways to attract new revenue can be experimented with. By using anonymized client profile data and communication patterns we estimate a client’s probability to donate, and messages are created to ask for donations. By analyzing locations most frequented by clients, marketing messages are generated to those businesses to help them understand some of the services that you are providing to the community. Awareness like this leads to businesses donating to your organization. 

The data already exists to better engage with your staff, service providers, and clients. Now with AI and Machine Learning, it is becoming simpler to leverage that data to make sure your services are becoming better and better