The Challenges for Logistics Technology Platforms Building Their Own Geofencing DataSets

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In Arthur Conan Doyle’s A Study in Scarlet, Sherlock Holmes says, “It is a capital mistake to theorize before one has data.” Although modern logistics companies may not solve crimes, the statement still holds. Accurate data can mean the difference between success and failure.

For logistics companies, the concern is not so much the ability to theorize as it is to plan, make sound decisions, and communicate effectively, all of which rests on the quality of the data at hand. Polygon geofencing technology, which plays a prominent role in today’s logistics landscape, is directly tied to data quality. Logistics technology companies that build their own data sets may be wasting resources and relying on imprecise geofences‚Ķ. And missing out on the collective benefits/network effect of subscribing to an available data standard

Why Logistics Companies Use Geofences

Geofencing is a critical tool in modern logistics systems. It serves multiple purposes and allows for enhanced accuracy in terms of:

  • Tracking shipments and assets from beginning to end, providing a mechanism to manage by exception and stay on top of costly issues.
  • Replacing timecards for drivers and decreasing dwell or dead time.
  • Monitoring for delays in delivery times to stay ahead of late shipments and communicate proactively with providers and customers.
  • Updating interested parties about the status of a delivery, keeping everyone informed and on the same page.

Generally, geofencing technology allows logistics companies to increase efficiency and improve decision-making processes, but only when the geofences are precise and accurate, and the data is easy to ingest by tech platforms.

How LogTech Platforms Create Geofences Today

Although geofencing data sets are integral to creating valuable information, they can be laborious and costly to build. The data value creation rests on automation and accuracy.

Circular Geofences

A user can generate a circular geofence simply by entering a radius into the system. However, these geofences are highly inaccurate, creating confusion and poor understanding. This inaccuracy leads to delayed shipments, lost assets, longer dwell times, and overall slower supply chain throughput – an economic detriment for all participants.

Manual Polygon Geofences

In an attempt to move toward utilizing the more accurate polygon geofence, LogTech platforms have turned toward manually building these polygons. Unfortunately, they are susceptible to human error, which can negatively affect the data. Additionally, creating polygon geofences is incredibly time-consuming, with a high probability of duplication. As a result, businesses waste valuable time and resources when creating geofences.

The Problems with Logistics Technology Platforms Building Their Own Geofences

A geofence aims to improve business processes, outcomes, and profits. Still, when logistics technology platforms build their own geofences, they often create more problems than they solve. Logistics companies with inadequate geofencing solutions can experience:

  • Bad information from bad data = expensive bad decisions
  • The increased cost of labor
  • Impaired decision-making
  • Reduction in daily load transfers (shipments), reducing overall revenue and profit margins
  • Increase trucking costs, detention fees
  • Lost or stolen shipments and assets
  • Lack of standardization
  • Customer dissatisfaction harms the ability to grow market share

These effects have a substantial financial cost and can, over time, negatively impact a business’s reputation, causing customers to move to competitors.

The Benefits of Tapping into Existing Geofence Data Sets

Rather than relying on imprecise circular geofences or burdensome manual polygon geofences, logistics companies can instead turn to other available resources. For example, logistics teams can improve their operations by tapping into Kestrel Insight’s pre-existing polygon geofence data lake.

Accuracy and Detail

Automated polygon geofences are more targeted than circular geofences, allowing for greater detail and accuracy when tracking shipments. This results in fewer fence breaks and improved planning for delivery times, potential delays, and customer updates.

Frequency and Volume

Tapping into geofencing data sets can save a logistics team precious time. For example, rather than spending hours laboring over manually generated polygon geofences, a team can create a higher volume at a greater frequency with automation.

Cost Reduction

Using a geofence data lake can have a positive financial impact in two respects. First, it significantly reduces costs associated with:

  • Headcounts
  • Inaccurate data
  • Poor decisions
  • Overbilled detention

Automated polygon geofencing can also increase profits by improving efficiency and customer satisfaction, ultimately promoting business growth.

Other Improvements

There are many other advantages of automated polygon geofencing. These include improvements in:

  • Brand equity
  • User experience
  • Customer value
  • Team member experiences
  • Decision timelines
  • Speed
  • Standards of measure

In each case, using existing data sets like those from Kestrel Insights allows logistics companies to reap the full benefits of geofencing. Most importantly, they can avoid the damaging pitfalls of using circular or manually generated geofences.

Build Better Geofences with Kestrel Insights

The logistics industry is an enormous part of the global economy. For example, in the United States alone, the revenue of the trucking industry is over $732 billion. With so much money at stake and with such a pivotal role in the ability of businesses, governments, and everyday citizens to function, logistics systems must operate at maximum capacity with the best possible data.

With Kestrel Insights, logistics companies can rely on extremely accurate and precise automated polygon geofences to strengthen their KPIs and decision-making. Reach out to the experts to learn more about the role that high-quality data can play in optimizing efficiency and reducing costs in your logistics operation.

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