For Sensos, supply chain visibility isn't the finish line—it's just the start
Louis Boroditsky — 27 May 2025
4 min read
23 August 2023
Customers today expect fast, seamless deliveries — and businesses are under pressure to perform. Delivering on time is essential for customer satisfaction and business profitability.
However, numerous challenges can arise along the way, causing delays and making it difficult to provide precise estimated times of arrival (ETAs). That includes road conditions, last-minute pick-ups, and unforeseen delays.
Thankfully, advancements in location data and dynamic maps have enabled delivery services to tackle these obstacles and provide accurate ETAs, ensuring happy customers and efficient businesses. Here are four ways location data can improve your ETAs.
One of the major hurdles in estimating delivery times accurately is the unpredictability of road conditions and traffic congestion. Heavy traffic, crashes, or road construction can significantly impact delivery schedules.
Traditionally, static map data couldn't account for real-time changes. However, dynamic maps powered by location data now allow delivery services to monitor and analyze traffic patterns in real time.
By using this information effectively, they can recalculate ETAs based on current road conditions, providing more accurate delivery timeframes.
Another challenge that affects ETA accuracy is last-minute pick-ups or changes in delivery schedules. Businesses often require quick response times and flexibility when it comes to pick-up requests.
These sudden modifications can disrupt the planned delivery route and impact ETA calculations.
However, with the integration of dynamic maps and real-time location data, delivery services can swiftly adapt to these changes. They can optimize routes on the fly and update ETAs accordingly, ensuring minimal disruption and maximizing efficiency.
Augment your algorithm |
HERE Routing leverages rich truck-specific map information to calculate routes between two or more locations, factoring in truck type, load restrictions, turn penalties, toll times and ferry journeys. |
Machine learning comes into play here too, helping to estimate journey times and the impact of traffic incidents with greater precision. |
Delays caused by external factors, such as extreme weather conditions or unexpected incidents, can significantly affect delivery timelines. For instance, a sudden storm may lead to flooded or blocked roads, making it impossible to adhere to the original ETA.
To counteract such challenges, delivery services rely on location data and dynamic maps to receive up-to-date information about weather conditions, road closures, or other potential obstacles. By constantly monitoring these factors, they can adjust ETAs in real-time and keep recipients informed about any delays.
Accurate ETAs play a vital role in ensuring the recipient is ready to receive the delivery upon arrival. When a customer is prepared, it reduces waiting times and enhances overall satisfaction.
By employing location data and dynamic maps, delivery services can provide customers with precise ETAs, allowing them to plan their day accordingly. Recipients can be notified of the updated delivery timeframes, ensuring a smooth and hassle-free experience.
There are various challenges associated with delivering goods on time, from unpredictable road conditions to last-minute changes and unforeseen delays. But advancements in location data and dynamic mapping technologies like those from HERE, have revolutionized the way ETAs are calculated.
Ian Dickson
Contributor
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Ian Dickson
Contributor
Louis Boroditsky — 27 May 2025
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