Customer ’ s preference for same-day delivery is last-mile carriers are being called
Precise maps , with information about parking , access , and exact location data will become essential . Today ’ s Maps aren ’ t designed for deliveries . The biggest drawback is that they show the wrong location for about 30 % of addresses . In addition , the maps represent each address with a single pin . A driver can ’ t tell if that pin is on the 37th floor of the Salesforce Tower in San Francisco and that the delivery entrance is towards the back of the building , 15 mins away from where Maps navigated you . Industry-leading mapping services like Google Beans solved the last 100 feet by adding missing critical components that can help a new driver complete delivery without delay or failure . Important waypoints like :
• Parking : street , lot or underground
• Building entrance : main or service entrance , elevator location
• Delivery Policies : delivery lockers , doorstep or doorman
• Security : visitor badge , TSA , Prior security authorization
Information like this can reduce delivery times by a few minutes per delivery , lower failure rate by over 25 %, and cut down driver time .
Customers will move to retailers who can provide better ETAs . Eighty percent of customers want a specified time of delivery . But only 40 % of retailers offer delivery ETAs or time windows . Improved cloud computing and AI allows routing systems to estimate the time of arrival for each package far more effectively without draining the battery or cellular data on the driver ’ s phone . Forty percent of online shoppers say that products took longer to get delivered than they were told at the time of purchase . And 41 % of all shoppers switch to retailers who meet their delivery needs . Better ETAs allow customers more flexibility . They in turn help carriers reduce failed deliveries or re-deliveries . Customers who want accurate delivery time windows will find retailers who offer them , which will result in all carriers having to offer precise ETAs for their service .
Software systems that leverage AI to improve every day and help users build their own data will replace static software systems . Routing applications have the potential to collect data points such as order details , addresses , proof of delivery , delivery geocode , address geocode , address notes , pictures , customer notes , timestamps , driver ratings , driver tips , etc . Machine learning , coupled with the proper feedback mechanism can power modern systems to learn from historical data continuously . Every order delivered allows the system to :
• Improve upon delivered location
• Make better dispatch recommendations
• Learn traffic patterns for better ETA calculations
22 customized logistics & delivery Magazine FALL 2022