Why business demand for advanced weather data is heating up
Data Mining

Why business demand for advanced weather data is heating up

This is a contributed piece by Mark Hoekzema, chief meteorologist and director of meteorological operations at Earth Networks.

“The weather excuse” is a term commonly tossed around by investment analysts when publicly-traded companies blame an earnings miss on the weather. But a growing number of organisations - public and private - are making advanced weather data a core part of their business strategy to improve decision making, grow revenues, reduce risk and ultimately gain a competitive edge - in turn making “the weather excuse” a thing of the past.

Advanced data is critical as severe weather events increase in their intensity, causing billions of dollars in damage annually. Advanced climatological data is just one piece of the puzzle, but an important one that can drive decision making and planning for numerous business applications. There are three emerging areas in particular that hold tremendous potential:


Three ways climatological data can improve telematics & fleet operations

Frost & Sullivan estimates that telematics devices are enabling fleets to reduce fuel costs by as much as 25%, with a 30% reduction in idle time. One of the most appealing areas of innovation for fleet telematics is the ability to leverage advanced weather data to monitor deteriorating road conditions, hail and other weather hazards.

The science of forecasting is reaping rewards for Big Blue, but why is weather data important to companies?

The ability to overlay real-time and forecasted weather data such as lightning, hail, temperature, wind speed, etc. with road surface conditions holds the potential for businesses to significantly improve their fleet operations, routing efficiency, and driver safety. This evolution of fleet telematics from basic “track-and-trace” to more advanced capabilities is driving business demand and extending the benefits that come from better visibility into the fleet.

There are three areas in particular where access to climatological data is enabling businesses to enhance telematics and fleet operations:

ONE: Weather data visualisation

The ability to overlay real-time and forecasted weather data such as snow, hail, temperature, wind speed, lightning, wind gusts, etc. with road surface conditions holds the potential to significantly improve fleet operations, routing efficiency, and driver safety. Fleet managers can have access to visualisation tools with an extensive set of sophisticated weather observation layers with the weather data referenced above, as well as predictive weather alerts from the National Weather Service or commercial data providers such as Earth Networks. The result: the ability for fleet managers to make more intelligent weather-related decisions.

TWO: Seamless integration into existing systems

In many cases, fleet managers already operate a visualisation platform that they distribute to their field staff to help them with routing and decision-making. These platforms may come prepackaged with data such as routing maps, as well as dynamic data that includes traffic congestions on their route - just like many of us see on Google Maps or Waze. Leveraging off-the-shelf APIs that plug weather intelligence directly into existing systems alleviates the hassle of data management and ensures relevant information is distributed to the right people.

THREE: Hyperlocal and time sensitive weather validation

Weather data - in conjunction with vehicle data - can assist businesses when it comes to fleet accidents and other issues for which insurance coverage comes into play. When it comes to accident reconstruction for example, speed and car-sensor measured data is only meaningful with the proper context of both weather (i.e. - heavy rain and lightning) and road conditions (pavement temperatures, road conditions, and road treatment in each area) at the time of the incident. By integrating forecast models with surface observations and road observation, companies can improve fleet routing through enhanced efficiency and safety - while better managing loss prevention that can occur due to hazardous driving conditions.


Three phases of commercial drone operations that need weather data

As Amazon (Prime Air), Google (Project Wing) and others move towards deploying drones for delivery of goods to consumers and businesses - the FAA estimates the fleet of commercial drones could grow from 42,000 in 2016 to 1.6 million in 2021 - it is increasingly clear that advanced hyper-local, real-time climatological data will play a critical role in ensuring drones can fly their missions safely and efficiently. While businesses operating commercial drones face a number of challenges, there is growing demand for more advanced weather data across the three phases of commercial drone operations:

Phase 1: Pre-flight planning

Drone operations require an ability to forecast weather with hyperlocal precision to determine where it will be clear, raining, snowing or of greater relevance, where severe weather is occurring so that drones can be routed around lightning, etc. or grounded until weather clears. Advanced weather data can transform the efficiency and safety of drone and unmanned vehicle operations used for commercial drone activities, particularly for businesses in weather-sensitive industries such as oil & gas, construction, state & local government, and energy.

Phase 2: In-flight operations

Wind speeds are a critical component to deploying smooth drone-based missions; with current regulatory restrictions, most drones will operate in a low-altitude range of 10-400 feet - which means drones fly too high for surface-level wind data to be used exclusively and too low to rely on wind data utilised by airlines operating at much higher altitudes. We are starting to see the rollout of low altitude wind products to address this 10-400 feet gap where it has been historically challenging to gather wind data. 

Phase 3: Post-flight analysis

Advanced weather data paired with data collected from drone missions can help users understand how weather may have impacted sites over time. Infrastructure inspections are just one example that comes to mind here: annual bridge inspections can overlay historical weather data to understand the impact of weather on the health of the bridge’s infrastructure from year to year.


Supply chain forecasting has become big business

Global warming has raised the stakes for businesses with supply chains: extreme weather events are increasing in number and severity. With more dramatic weather fluctuations wreaking havoc with supply chains, some retailers have hired climatologists to assist with more accurate weather predictions.

Short and long-term weather forecasting has played a role in retail and other industries with extensive supply chains for years - whether it’s the seasonal stocking of clothing or diverting shovels to parts of the country forecast to endure a particularly brutal winter. But for further evidence of how weather data is permeating supply chain operations, look no further than a predictive analytics class added at the Fashion Institute of Technology (FIT) in New York City that examines the utilisation of weather forecasting in the fashion industry.

But today, advanced weather data analytics enables a level of precision that can be used to prevent, say a regional drugstore chain from failing to stock enough allergy medicine in advance of a particularly bad allergy season. Advanced real-time and forecast weather data enables businesses to optimise their supply chain as never before.

Advanced real-time weather data in conjunction with detailed environmental outlooks can guide businesses with supply chains that are sensitive to weather disruptions on how to determine how much, where and when product to ship and stock. 


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