Diana Schildhouse, chief data and analytics officer at Colgate-Palmolive, describes herself as a data storyteller – but what does that mean in terms of day-to-day delivery?
“To be successful in roles like this, you must have a deep connection with the business and understand what you’re trying to solve, what their questions are, and then devise solutions,” she says.
“Those solutions could use advanced analytics. Sometimes, it’s about creating simpler solutions. But success is always about solving that business need.”
Schildhouse joined Colgate-Palmolive in April 2021 as chief analytics and insights officer. She was previously at Mattel for eight years, latterly as senior vice-president for global strategy, insights and analytics. Schildhouse has also worked for Westfield, Merrill Lynch and Disney.
“Most of my experience has been in consumer-facing companies,” she says.
“In terms of my career, I’ve always been in functions like advanced analytics, insights and strategy. When I saw the opportunity with Colgate-Palmolive, I thought about the breadth and scale of the company. It was an exciting opportunity for me to come in and build from the ground up, while leveraging the scale of the business.”
Schildhouse joined the company in a newly created role to develop an analytics and insights strategy for an organisation that operates in over 200 countries and territories globally. After proving her success in this role, she assumed her current position in June 2025, where the breadth of responsibilities increased to include oversight for data and artificial intelligence (AI).
“I had already been running some of those areas, but it made sense for us to bring everything together,” she says.
“You can’t build and scale all the exciting, advanced analytics solutions and everything with AI unless you have data foundations. Many companies are on this journey. They recognise that gaining value from all this data-enabled technology depends on key elements like data strategy, data governance, and a series of related topics.”
Supporting growth
Schildhouse reports to Colgate-Palmolive’s chief growth officer. Her peers include executives responsible for digital transformation, supply chain, innovation, research and development, global marketing, strategy and sustainability. She says the organisational structure makes it easier to tie data to long-term aims.
“The farther away you are from the business, the harder it is to make connections and drive impact,” she says.
“What appealed to me here was the fact that analytics and insights were part of the business and growth area of the company. I thought that would position me well to drive value through the work that I’m doing.”
“You can’t build and scale all the exciting, advanced analytics solutions and everything with AI unless you have data foundations. Gaining value from all this data-enabled technology depends on key elements like data strategy, data governance, and a series of related topics”
Diana Schildhouse, Colgate-Palmolive
Almost five years into her work with the company, Schildhouse says it’s been an exciting and enjoyable ride.
“We’ve had lots of success in what we’ve done with our analytics and data transformations here,” she says. “It’s fulfilling to see that my amazing team is driving a lot of that success.”
Joining the company in a new role meant she had a blank page for analytics and insight strategy. She began by asking the business about its major challenges and exploring the potential of technology to help solve those concerns. As part of her efforts, she tracked and traced performance to ensure success.
“That’s something I’m obsessed with, because if we can’t show the value and impact we’re getting, then we could be building the most brilliant solutions and passing them over the fence to the business, but if they don’t actually use them, then we didn’t achieve what we were trying to do,” she says.
Whether it’s for pricing analytics, revenue generation, cost optimisation, or intellectual property creation, Schildhouse has developed frameworks that ensure the solutions her team creates can be scaled globally to deliver value. She says the general direction of travel for data-led transformation at Colgate-Palmolive is about giving the people in the business tools to make better decisions quickly.
“We want them to have information at their disposal,” she says. “Some of the things we’ve built internally can compute billions of scenarios. So, it’s not just a matter of changing where teams spend their time. Some of the things we can do now, you couldn’t have completed a few years ago. Our work is about helping business teams use data and analytics in predictive, diagnostic and then prescriptive ways to make faster, more informed decisions.”
Embracing AI
Schildhouse’s team conceptualises, builds, deploys and embeds AI-enabled solutions, including machine learning models and predictive and prescriptive analytics, across Colgate-Palmolive globally. One example includes revenue growth management (RGM) analytics, which covers key concerns such as pricing and trade promotions.
She says RGM was identified as one of the areas where her team could have the biggest impact when she joined the company. They developed an in-house diagnostic and predictive tool that helped staff on the ground understand scenarios and make faster pricing decisions. That tool was scaled globally. The team also tracked usage to ensure the technology was effective.
The team used successes in RGM as a platform for developments in other areas. Schildhouse refers to promotion and calendar optimisation technology, which business users suggested was an area that could benefit from better analytics. They piloted, tested and refined this tool and are now pushing it out globally to boost pricing and promotions analysis.
Schildhouse’s team is also exploring generative AI (GenAI) in product innovation. Guided by a business-first approach, her team assessed potential technological solutions. They mapped out how the company’s marketers create and test new product concepts, and considered how AI could be deployed to make that process faster, easier and more effective.
Along with technology partner Market Logic, the data team created an insights hub. Marketers can use natural language to query data and receive instant insights from the hub.
“That was the first step that helped us understand unmet consumer needs,” she says.
As a second stage, they developed a tool to help support the creation of product concepts that fit these consumer needs. As part of an innovation funnel, Schildhouse says marketers can test their ideas rapidly in a digital twin. Developed in-house, the twin allows professionals to test their concepts cost-effectively for specific demographic groups.
“This multi-stage approach has been one of our most successful applications of GenAI to an important business area,” she says. “It’s about ensuring there’s a human in the loop and helping our innovation teams get to faster insights and to develop many more concept ideas.”
Establishing priorities
Schildhouse says one of her team’s main priorities is to innovate in an area known as omni-demand generation, which she explains is an approach that helps the company meet its consumers with the products they need. This work will incorporate progress in key areas, such as RGM, plus media, marketing and e-commerce analytics.
“We have some exciting things planned there,” she says, referring to her team’s aims. “Then I would just definitely say AI – so, continued experimentation, and moving to scale on many of the things that we’ve already piloted within that area.”
Schildhouse says her team considers AI initiatives via a framework that explores both horizontal and vertical elements. The horizontal elements are the underpinning tools and foundations that allow the company to scale its successful AI initiatives globally and effectively. The vertical elements, meanwhile, are the company’s priority areas for GenAI.
“Our plans for the next couple of years are very closely tied to that framework, but innovation always starts with our strategy – that’s key in helping us know where to focus,” she says.
Over the next 24 months, her internal team will continue to focus on the data strategy and governance foundations that she says are crucial to scaling analytics and AI initiatives.
“We’ll be putting a lot more focus on data transformation, and we’ve already made really great strides in that area, as well as building and launching data products that are reusable and governed. We’ll also be looking at AI and what’s the next generation for us,” she says, including developing data-enabled services for the company’s customers.
“There’s always a portion of what we’re doing that’s focused on exploring those edge cases of what could be the next most impactful area for the company. We want to create products that delight customers, meet their needs and provide the benefits that they’re looking for.”
Learning lessons
Schildhouse feels positive when she considers the future of the data leader role. There’s no doubting, she says, that information and insight continue to be increasingly important for modern companies. However, she reasserts that data leaders must ensure their AI and analytics initiatives are built on strong foundations.
In a world where companies are looking to get actual, tangible value from all their analytics and AI solutions, if your data is not in the right place and it’s not organised, and you don’t have the right datasets, that slows down the whole process Diana Schildhouse, Colgate-Palmolive
“In a world where companies are looking to get actual, tangible value from all their analytics and AI solutions, if your data is not in the right place and it’s not organised, and you don’t have the right datasets, that slows down the whole process,” she says.
“One of the reasons we were able to scale the RGM analytics tool that we built in-house is because, at the same time as we were creating that, we also started working on the data foundations.”
Schildhouse says her team consolidated and harmonised data from 500 sources in a global view for the RGM project. Lessons learned in this initiative have helped inform others. Yet, regardless of the project, she says one thing remains constant – data leaders must be guided by enterprise demands rather than technological features.
“You must have a business lens,” she says. “Data leaders need to bring that focus and understand how the work of their team translates to something meaningful for their organisation and their industry. That awareness is so key in the role, and that’s where you see the more successful data leaders when I look at some of my peers.”
Since 2018, a group of researchers from around the world have crunched the numbers on how much heat the world’s oceans are absorbing each year. In 2025, their measurements broke records once again, making this the eighth year in a row that the world’s oceans have absorbed more heat than the years before.
The study, which was published Friday in the journal Advances in Atmospheric Science, found that the world’s oceans absorbed an additional 23 zettajoules’ worth of heat in 2025, the most in any year since modern measurements began in the 1960s. That’s significantly higher than the 16 additional zettajoules they absorbed in 2024. The research comes from a team of more than 50 scientists across the United States, Europe, and China.
A joule is a common way to measure energy. A single joule is a relatively small unit of measurement—it’s about enough to power a tiny lightbulb for a second, or slightly heat a gram of water. But a zettajoule is one sextillion joules; numerically, the 23 zettajoules the oceans absorbed this year can be written out as 23,000,000,000,000,000,000,000.
John Abraham, a professor of thermal science at the University of St. Thomas and one of the authors on the paper, says that he sometimes has trouble putting this number into contexts laypeople understand. Abraham offers up a couple options. His favorite is comparing the energy stored in the ocean to the energy of atomic bombs: The 2025 warming, he says, is the energetic equivalent to 12 Hiroshima bombs exploding in the ocean. (Some other calculations he’s done include equating this number to the energy it would take to boil 2 billion Olympic swimming pools, or more than 200 times the electrical use of everyone on the planet.)
“Last year was a bonkers, crazy warming year—that’s the technical term,” Abraham joked to me. “The peer-reviewed scientific term is ‘bonkers’.”
The world’s oceans are its largest heat sink, absorbing more than 90 percent of the excess warming that is trapped in the atmosphere. While some of the excess heat warms the ocean’s surface, it also slowly travels further down into deeper parts of the ocean, aided by circulation and currents.
Global temperature calculations—like the ones used to determine the hottest years on record—usually only capture measurements taken at the ocean’s surface. (The study finds that overall sea surface temperatures in 2025 were slightly lower than they were in 2024, which is on record as the hottest year since modern records began. Some meteorological phenomena, like El Niño events, can also raise sea surface temperatures in certain regions, which can cause the overall ocean to absorb slightly less heat in a given year. This helps to explain why there was such a big jump in added ocean heat content between 2025, which developed a weak La Niña at the end of the year, and 2024, which came at the end of a strong El Niño year.) While sea surface temperatures have risen since the industrial revolution, thanks to our use of fossil fuels, these measurements don’t provide a full picture of how climate change is affecting the oceans.
“If the whole world was covered by a shallow ocean that was only a couple feet deep, it would warm up more or less at the same speed as the land,” says Zeke Hausfather, a research scientist at Berkeley Earth and a coauthor of the study. “But because so much of that heat is going down in the deep ocean, we see generally slower warming of sea surface temperatures [than those on land].”
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Jonathan Ross, the Immigration and Customs Enforcement officer identified by multiple news outlets as the federal agent who shot 37-year-old Renee Good in Minneapolis on Wednesday, is a veteran deportation officer in ICE’s Enforcement and Removal Operations division, according to sworn testimony from the federal district court in Minnesota obtained by WIRED. A member of a Special Response Team, ICE’s version of a SWAT team, he’s had duties as a firearms trainer and led teams drawn from multiple federal agencies including the FBI, Ross testified.
The testimony stems from a December 2025 trial related to a June incident with parallels to the interaction that led to Good’s killing.
In June according to Ross’s testimony, he led a team seeking to apprehend a man named Roberto Carlos Muñoz-Guatemala, who was on an administrative warrant for being in the United States without authorization. Because the man’s home was across from a school and immigration agents had no authority to enter his home, Ross testified, they instead trailed him in unmarked vehicles.
Muñoz-Guatemala’s attorney did not immediately reply to a request for comment.
According to the December testimony and a New York Times account of an FBI agent’s affidavit associated with the case, Ross approached Muñoz-Guatemala and asked him to roll down his window and open his door. Ross, who testified that he had been driving an unmarked vehicle, was dressed in ranger green and grey, and wore his badge on his belt, broke the driver’s side back window and reached into the vehicle, at which point Muñoz-Guatemala pulled away.
While being dragged at a speed he claimed seemed like “40 miles an hour at least, if not more,” Ross pulled out his Taser and fired it at the driver. Muñoz-Guatemala continued to drive, and succeeded in shaking Ross from the car. At trial, Ross testified that he suffered injuries that required 33 stitches.
According to the affidavit, Muñoz-Guatemala called 911 to report that he’d been assaulted by ICE, which led to his arrest. Last month, he was convicted of assault on a federal officer with a dangerous weapon.
Reports from the Minnesota Star-Tribune and The Guardian identified Ross as the shooter who killed Good, a mother and recent transplant to Minneapolis, during an immigration enforcement action in the city. Video of the incident appears to show a federal agent firing shots into Good’s vehicle as she attempted to leave the scene. The officer did not appear to have been struck by the vehicle, and Good appeared to be turning the wheel to avoid contact, video analysis by The New York Times and the Washington Post shows.
At Thursday’s White House press briefing, vice president JD Vance answered questions about the incident, and his responses included numerous identifying details about Ross, mainly relating to his interaction with Muñoz-Guatemala. “That very ICE officer nearly had his life ended, dragged by a car, six months ago, 33 stitches in his leg,” said Vance, “so you think maybe he is a little bit sensitive about somebody ramming him with an automobile?”
Department of Homeland Security secretary Kirsti Noem has repeatedly described Good’s actions as an intentional act of “domestic terrorism.” An FBI investigation into Good’s killing is ongoing.
DHS spokesperson Tricia McLaughlin told WIRED in a statement that the department is “not going to expose the name of this officer. He acted according to his training.” McLaughlin added that federal immigration agents “are under constant threat from violent agitators” because of “doxxing” and that the Minnesota Star Tribune, which first published Ross’ name, “should delete their story immediately.”According to Ross’ December testimony, he served in the Indiana National Guard and was deployed to Iraq from 2004 to 2005 as a machine gunner on a patrol truck, then joined Border Patrol in 2007 after finishing college, working near El Paso, Texas.
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