With our weather becoming more volatile every day, major weather events can severely disrupt business operations. Despite this, many companies still take a reactive approach when dealing with weather risks, lacking effective systems to leverage weather insights.
In a recent interview, Dan Slagen, Chief Marketing Officer at Tomorrow.io, and Bill Claflin, Director of Sales at Tomorrow.io, discussed how enterprises can move from chaotic weather response to proactive planning and mitigation.
They outlined organizations’ key challenges and how Tomorrow.io’s integrated platform enables customers across industries to forecast outcomes, align teams, and build resilience.
The Complex Challenge of Decision-Making at Scale
“What makes decision-making at scale so difficult?”
According to Slagen, most enterprises today have very manual, fragmented processes for dealing with weather risks, with little centralized coordination. As he described, it’s largely “getting hit with weather and trying to figure out what it means for them.”
Claflin expanded on why making decisions at scale is so difficult for large, complex organizations:
- It requires immense alignment on data, thresholds, protocols, and desired outcomes across the organization
- There is a major risk if the decision made is wrong, from safety incidents to business disruptions
- There is an opportunity cost if competitors manage weather better
Slagen adds that with such large, distributed workforces and assets, it’s impossible for human teams to monitor the weather at all locations 24/7/365 manually.
He emphasizes, “There’s just too many weather factors that can happen. No team can actually keep track of the forecast everywhere. By not having an automated system in place, you’re at risk of getting something wrong.”
Without automated systems, organizations face a constant risk of mistakes leading to accidents, costs, or lost revenue.
The Perils of Inconsistent Manual Interpretation
Another important point made was that relying purely on human interpretation of weather data is unreliable. If our teams can’t track data at all locations every moment of every day, we can’t expect them to consistently interpret the data the same way every time.
As Claflin discussed, human interpretation opens the door to inconsistencies, errors, missed events, incorrect decisions, and poor communication. One person may look at a forecast and make a certain call, while another person may look at the same data but reach a different conclusion.
“You could miss things, you could completely miss a weather event, you could miss an opportunity to communicate that weather event. Maybe you made the wrong decision,” he says.
Across an enterprise, these inconsistencies result in organizational misalignment, delayed reactions, safety issues, and unmitigated business disruptions. Claflin noted the downside risk includes failure to execute business plans and customer commitments. The opportunity cost is lost efficiency, productivity, and competitiveness compared to industry peers.
Forecasting Outcomes, Not Just Weather
While companies seek out solutions for combatting high-impact weather and the pitfalls that come with a lack of automation in day-to-day operations, Tomorrow.io is doing all it can to bring weather intelligence to the organizations that need it.
What sets Tomorrow.io apart is moving beyond basic weather alerts to forecast business impacts. As Claflin explained, “We’re not just forecasting the weather – we’re forecasting weather’s impact on our customers’ desired business outcomes.”
The platform is highly customizable to each client’s specific operations, assets, risk thresholds, and business goals.
As Claflin said, Tomorrow.io speaks to clients “in the context of their own business” to drive smarter decisions. The science behind the platform is cutting-edge, with satellite data and AI/ML built in, but the key is making those insights actionable.
“What Tomorrow.io is doing is building an end-to-end solution,” Slagen adds, “We’re even sending satellites up into space, but the forecast aside, you need to be able to take that forecast and understand it and automate what your teams going to do in a predictive way.”
Diverse Industry Applications, Measurable Results
The good news is that organizations already see success with predictive automated workflows in their daily work operations.
Slagen and Claflin discussed real-world examples of automation supporting aviation, rail, mining, construction, events, and more.
In one case, Tomorrow.io helped an airline selectively de-ice planes during a winter storm when wind speeds dropped below safety thresholds. This optimization for a single morning avoided nearly $2 million in costs.
In rail, the platform predicted wind risks that could cause derailments on certain sections of track. By delaying trains, clients prevented what could have been disastrous accidents. Across customers, the results have included major improvements in safety, costs, customer service, productivity, and efficiency.
“Those organizations are very different. We work with a multitude of different industries, from aviation and rail to broader logistics organizations, construction, and mining — all of those organizations have different outcomes in mind that they’re driving to yet still use [Tomorrow.io] because of how customizable it is for their particular needs,” says Claflin.
Unified Platform Drives Proactive Planning
Tomorrow.io goes “beyond the forecast” to help enterprises stop weather from disrupting their operations. Their weather intelligence platform enables customers to set goals, develop protocols, automate response plans, and provide predictive guidance. This transforms reactive processes into proactive strategies – making businesses smarter, safer, and more resilient.
It’s clear the impact that weather intelligence can have on businesses across the world. Check out the entire conversation:
Learn more about how organizations can turn weather data insights into business outcomes and book a call today.
