CIOs get strategic in the cloud: 4 success stories

Enterprise CIOs are gobbling up a vast buffet of advanced cloud services in the post-pandemic era.

In the aftermath of that unprecedented time, the cloud has evolved from a single-purpose compute and storage IaaS that saved business from global collapse into a far more complex platform capable of supporting a new class of advanced applications and dubbed by CIOs as the next- generation engine of innovation.

“Historically, the cloud has been deployed by organizations in a tactical manner, such as through data center consolidation. However, organizations of today view cloud as a highly strategic platform for their digital transformation needs,” says Sid Nag, a vice president and analyst at Gartner, noting that the cloud is now the foundation to all digital transformations.

In this post-pandemic era, CIOs, CTOs, and data scientists have tapped into so many layers of the cloud that it’s clear no three-point checklist will convey the abundance of business benefits gained. Following are several examples of how companies from a range of industries are making the most of the cloud today.

McDermott cloud platform fuels new revenue streams

When a giant contractor of offshore oil rigs and liquid natural gas (LNG) facilities invests heavily in building sustainable, low carbon-footprint structures and products, it’s a sea change.

For oil rig constructor McDermott International, that transformation has been fueled by its adoption of the cloud, where massive data and analytics services have not only enabled the company to build its rigs and LNGs more sustainably and efficiently, they have enabled McDermott to productize these blueprints for partners, adding new business opportunities for the company.

“These were products built for internal use but now software customers are asking for it so that has become a revenue stream for us,” says McDermott CIO Vagesh Dave, noting this internal shift to sustainability is enabling his customers to move away from gasoline. “Now, when engineers are designing an oil platform or LNG facility, they can actually pick one with lower carbon content.”

Dave says IT advancements in the cloud and related services have transformed McDermott — and its industry — into innovation engines. Moreover, analytics on McDermott’s cloud-based data platform provide the company with key insights about business trends and real-time shifts in its supply chain.

“Suppose we’re looking at a large shipment from Italy, and you’re looking at supply chain dependencies, the data predicts there may be a spike there,” Dave says, adding that this information is very valuable to McDermott’s customers.

McDermott is also using AI and visual analytics to detect incorrect configurations or defects in its designs, and it is training AI models to analyze bids from suppliers according to pre-set conditions. Such automations could provide McDermott with a significant productivity boost, Dave says.

Liberty Mutual expedites data science in the cloud

Liberty Mutual is one of the most advanced cloud adopters in the US. And that is in no small part thanks to the vision of CIO James McGlennon, who has built a robust hybrid cloud infrastructure primarily on Amazon Web Services but with specific uses of Microsoft Azure and, less so, Google Cloud Platform.

Liberty Mutual’s cloud infrastructure runs an array of business applications and analytics dashboards that yield real-time insights and predictions, as well as machine learning models that streamline claims processing. In fact, 60% of the insurer’s global workloads run in the cloud, delivering significant savings in hardware and software purchasing, but the big benefit comes in the form of business insights from analytics that are immeasurable, McGlennon says.

Liberty Mutual’s data scientists employ Tableau and Python extensively to deploy models into production. To expedite this, the insurer’s technical team built an API pipeline, called Runway, that packages models and deploys them as Python, as opposed to requiring the company’s data scientists to go back and rebuild them in Java or another language, McGlennon says.

“It’s really critical that we can deploy models quickly without having to rebuild them in another platform or language,” he adds. “And to be able to track the effectiveness of those machine learning models such that we can retrain them should the data sets change as they often do.”

The insurer uses, for example, Amazon Sage Maker as well as Python to build machine learning models. Liberty Mutual’s IT team has also created a set of components called Cortex to enable its data scientists to instantiate the workstations they need to build a new model “so the data scientist doesn’t have to worry about how to build out the infrastructure to start the modeling process,” McGlennon says.

With Cortex, Liberty Mutual’s data scientists can simply set their technical and data-set requirements, and a modeling workstation will be created on AWS with the right data and tools in an appropriately sized GPU environment, McGlennon explains, adding that he is also focused on technologies that will define the next generation of cloud-based applications, including IoT devices and sensors that, in conjunction with the insurer’s cloud-based computer vision models, could help generate more data for its clients’ insurance claims.

Koch Industries embraces multicloud networking

Integrating a new network after an acquisition can be a sizable headache for any CIO. But for Koch Industries, a $125 billion global conglomerate that has acquired five companies in two years, connecting those acquisitions’ networks to its own sprawling network has been a challenge of another magnitude.

Traditionally, to integrate its acquisitions, Koch would flatten the acquired company’s core network, says Matt Hoag, CTO of business solutions at Koch. While this approach makes connecting the network easier, it is a slow, arduous endeavor that gets more complex as more companies are acquired, he says.

“Cloud deployments typically come in the form of multiple accounts, including multiple LAN segments that need to be connected. This encompasses not only VMs but also many other services offered by the cloud provider,” he says.

The major tasks involved range from deploying core IP routing, to enabling connections among virtual workloads within a multitenant cloud, to connecting multiple clouds, to ensuring remote users can connect to the company’s cloud estate. It’s the kind of challenge few, if any, enterprises can take on without a partner today.

Hoag brought in partner Alkira to help tackle the challenge, as using a third-party platform to handle the abstraction of networking into a software service would vastly reduce the complexity for his own IT team, he says.

Hybrid and multicloud networking, such as Koch’s, represents the next level of cloud maturity, says IDC analyst Brad Casemore, who adds that it’s a category in which most enterprises are woefully behind. “While compute and storage infrastructure have largely aligned with cloud principles and the needs of multicloud environments,” Casemore says, “the network has not kept pace. “

There’s little doubt, however, that hybrid, multicloud networking represents the next level of cloud maturity, says Casemore, who adds that it’s a category in which most enterprises are still behind but will likely evolve to as the digital infrastructures of enterprises mature.

National Grid taps cloud to become ‘intelligence connected utility’

The cloud is one of the core ingredients driving National Grid’s digitization efforts, which Global CIO Adriana “Andi” Karaboutis equates to the energy giant’s core goal: To build the “intelligent connected utility.”

Karaboutis is the chief architect of the $20 billion British multinational’s digital transformation in the UK as well as in New York and New England. She is also working with two governments to shore up the cybersecurity of several NATO power grids.

“It’s one of the most stressful, but challenging jobs, securing and transforming critical national infrastructure,” says Karaboutis, who is excited to be a player not only in securing grids against cyberattacks but also in transforming the global energy grid in an era of epic technological advances to slow climate change.

And the cloud is critical to accomplishing these goals, she says. National Grid is a big Microsoft Azure cloud customer making extensive use of the company’s advanced data analytics, cybersecurity, and AI tools.

For instance, National Grid is applying Microsoft machine learning (ML) algorithms to optimize its “vegetation management” effort to prune plans as part of project “Copperleaf” to prevent fires and other catastrophes. It is also using geospatial technologies in concert with Azure artificial intelligence to make the “right decisions” about how to maintain undersea cables and to make routing and investment decisions, she says.

The utility is also exploring ways to deploy ML algorithms to better manage electricity outages that still occur during power surges, such as during commercial breaks from the World Cup or royal weddings.

Not all data will be migrated off premises — just the data that makes sense running in the cloud, she says.

“I call it cloud density in the right way,” Karaboutis adds. “All of our investments are about value. And in so many cases, it’s not pure ROI and cost savings but it’s removing hidden costs and shared costs of managing technical debt, like not having to do upgrades. It’s about increased security for the state. It’s about capacity management and resilience. All of that together is how we’re measuring the value of going to the cloud.”

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