When IBM acquired The Weather Company in 2015, it was reported that close to 900 employees of the Atlanta-based weather operation would transition into the global enterprise. The strategic acquisition was made to power IBM Watson’s Internet of Things unit and build out more offerings in the cloud and IoT space.
At the time, Cameron Clayton was president of product and technology at The Weather Company. Post-acquisition, he transitioned into general manager of IBM Watson’s Media and Weather team to lead the integration of those employees.
Clayton had been with The Weather Company through its various incarnations since 2004, first helping build the mobile business pre-iPhone era and then running its digital B2B division.
Now, he oversees the creation of data-driven weather forecast models that can affect the businesses and lives of people around the world. He works closely with energy companies, airlines, and farmers and agricultural conglomerates to optimize their day-to-day tasks using IBM Watson’s predictive capabilities.
Over the past three years, he has helped his team “assimilate to their new environment, undergo a big transformation, and embrace AI in a massive way.”
Part of that new environment was working at a much different — and larger — scale. They went from a primarily U.S.-focused business to now, having a presence in 168 countries around the world, says Clayton.
“We’ve always been a purpose-driven company, helping save lives and their properties through weather forecasting. It was foundational to who we were. Now we have expanded access to mapping the atmosphere and that means for our businesses, enterprises, government and people,” says Clayton.
And while most newly-acquired teams must realign their business goals with the bigger company, he says that this wasn’t the case for them.
“At the time of the acquisition, IBM and The Weather Company were actually moving along a parallel journey toward a more open, transparent culture,” Clayton tells Hypepotamus.
“IBM was supportive of that overall journey, and there were no changes in our goals. We are still focused on growing users, doubling our enterprise revenue and expanding globally.”
While business goals aligned, the work culture was a little more challenging, says Clayton. He worked with IBM to elevate the focus on company-wide transparency.
Part of the challenge was with modernization. Prior to the acquisition, The Weather Company worked in a sequential fashion when building software, from 20-year-old cubicles, says Clayton. The IBM acquisition introduced agile processes and an open-office setup, but the adjustment period was tough for many of the employees.
“People went from having their own space to different noise volumes in an open environment. [Due to feedback,] we’ve adjusted that over time and refitted the space twice,” he says. The final setup ended up being a mix of open office, conference rooms, and small quiet pods.
Most of the feedback was delivered directly to Clayton in the form of workplace communication tools and all-hands meetings. He held an “Ask Cameron” session to submit feedback on the ongoing changes and transitions.
He also randomly selected 15 employees on a weekly basis to meet with and ask, “What do we need to do better to be the best place to work? What do we need to change?”
“I listened for an hour, took notes, and as a team, we found ways to implement those changes,” says Clayton. The feedback could be about anything — for example, that the office now recycles after an employee brought up that having non-recyclable or biodegradable supplies went against the company mission to protect the planet.
One of the big global problems The Weather Company is currently tackling is the concept of improving agriculture to feed the world’s growing population. If there is widespread hunger with a world population of seven billion, what will it look like in less than two decades with 9-11 billion?
The Watson Decision Platform for Agriculture is one of the innovative ways that IBM is applying artificial intelligence and data analytics to the farm-to-fork ecosystem. The platform allows farmers to film their fields with a drone and upon uploading the video, uses visual recognition analysis to identify crop diseases or pest infestations.
When a disease is identified, the platform suggests the best way to tackle the problem. Other data points that farmers can access include soil temperature and moisture levels, crop stress, predictions on yield, and more.
In another agriculture-related project, the team worked with the largest utility company in Texas to develop a predictive platform to monitor vegetation growth across their entire territory and identify branches that could cause an issue with power lines.
The division continues to grow after moving to a larger office that spans three floors, and Clayton doesn’t see that growth slowing down. “We just had the most successful quarter we’ve had in the company,” he says.