As campus networks continue to evolve, CIOs face a new hurdle in ensuring top-notch security measures. The importance of Wi-Fi technology cannot be understated as visitors and employees rely on it for seamless connectivity while on campus. However, CIOs and their teams are challenged with not only addressing security threats but also troubleshooting an extensive network of personal devices. Protecting enterprise environments has never been more necessary or intricate.

According to a 2021 report by Positive Technologies, 97% of enterprise Wi-Fi networks are vulnerable to attack. The most common vulnerabilities include weak passwords, unpatched software, and the use of insecure protocols.

In a survey of IT professionals conducted by Cybersecurity Insiders in 2020, 84% reported that their organizations had experienced a WiFi-related security breach in the previous 12 months. The same survey found that 60% of organizations do not use encryption to protect Wi-Fi communications, and 53% do not use secure passwords.

The 2021 Verizon Data Breach Investigations Report found that 26% of data breaches involved the use of stolen credentials, which can be obtained through WiFi-related attacks such as phishing or man-in-the-middle attacks.

Overall, these statistics highlight the importance of taking Wi-Fi security seriously in enterprise environments and implementing strong security measures to protect against potential risks.

Thankfully, Passpoint can address some of the top challenges IT leaders are facing today by enhancing security and automatizing time-consuming Wi-Fi management processes.

What is Passpoint?

Passpoint is based on the IEEE 802.11u standard and it is the brand for the Hotspot 2.0 certification program, Wi-Fi CERTIFIED Passpoint®, operated by the Wi-Fi Alliance. It is an industry-wide solution that streamlines Wi-Fi access and eliminates the need for users to find and authenticate a network each time they visit.

Passpoint grants instant, secure Wi-Fi access to users after once-in-a-lifetime provisioning of the Passpoint profile in their mobile device. Then, the enabled devices automatically connect to the organization’s network whenever they arrive at any campus.

Passpoint also enhances security measures without compromising the onboarding process. It uses 802.1X for user authentication and, specifically, the Extensible Authentication Protocol (EAP)-TLS, which supports certificate-basedauthentication —the gold standard of authentication— reducing the risk of cyber-attacks and data breaches.

Finally, Passpoint has the ability to support emerging technologies, such as the Internet of Things (IoT), that are expected to drive the next wave of digital transformation and will require a secure and seamless network infrastructure.

Enabling hybrid work practices

The practice of bringing your own device (BYOD) has been around for years in office spaces and the shift to hybrid work around the world has accelerated the trend. However, employees and visitors face several problems when connecting to traditional enterprise Wi-Fi, such as needing or losing a password, losing connectivity when logging back into a laptop, or onboarding personal devices into the network, thus putting the organization’s network at risk.

The aforementioned onboarding issues can result in a great deal of time wasted—both by users trying to resolve the issues and IT teams trying to help. Fortunately, Passpoint solves these onboarding issues by supercharging the Wi-Fi security and experience in this new highly mobile and agile working environment.

IT teams can quickly onboard all “unmanaged” devices, with peace of mind. By automating Wi-Fi onboarding in a secure way, Passpoint can have a positive impact on IT teams’ morale through improving user satisfaction and increasing productivity, as employees are not wasting time trying to connect to Wi-Fi or troubleshoot connection issues.

Focusing on digital transformation

In today’s fast-paced tech world, it can be overwhelming for CIOs and their teams to stay on top of the latest cloud technologies, virtual reality, and machine learning advancements. They are constantly learning and mastering new skills just to keep up.

By embracing Passpoint, CIOs can safeguard company data while reducing the burdensome tasks of their IT team that can work more efficiently and happily. This way, CIOs can devote their attention to defining and executing higher-value strategic initiatives, aligning their efforts with business objectives.

It is imperative for CIOs to prioritize Passpoint adoption if they wish to expedite their digital transformation journey and prepare their organization for the future.

To find out how Cloud4Wi can upgrade your enterprise Wi-Fi to Passpoint, click here.

Security

Information, according to the mathematical theory that bears its name, reduces uncertainty. If, for example, I tell you I tossed a coin twice, you’ll know there were four equally probable outcomes. But if I then tell you the first toss came up tails, the number of possible outcomes cuts in half: tails/heads or tails/tails.

In this way, the information I have given you has cut your uncertainty in half. Everything we do in IT starts here, with the definition of a “bit.”

And yet when it comes to reading about our industry, content that too often fails to reduce our uncertainty about a subject in any useful way.

Why do I say that, you ask? One reason is that surveys dominate research into IT practices, and their results generally follow the well-worn template: X percent of Y does or is planning to do Z.

Surveys, that is, only reduce our uncertainty about how many people or organizations are doing something we care about (or are supposed to). And even that is clouded by our lack of certainty as to how truthful the respondents are.

You can’t trust the answers

Let’s take a random example in which a CIO’s survey response indicates they’re planning to rationalize their applications portfolio. That doesn’t mean they’ll get the budget to actually rationalize it. Often their “yes” answer to a question is wistful yearning —something they’d like to do, if only they could.

Or, as they’re being surveyed by a prestigious analyst firm, they don’t want to admit they have no idea what the question means. Or, if they do, they’re embarrassed to admit that even though the analysts tell them that if they don’t follow this latest industry trend they’ll be out of business, following it just isn’t in the cards this year.

For the most part, survey value comes down to this: You think your company should be doing something. Someone’s survey associates a big bar with that subject. A big bar looks important. But really, using a survey to justify a course of action is little more than playing follow-the-leader.

Whom you measure matters more than what they say

Surveys also fail to reduce our uncertainty when they aren’t accompanied by an account of who responded to it — not only which companies or types of company, but also the specific job title or titles. After all, ask a CIO what they plan to spend on next year and compare it to what information technology the CEO or chief marketing officer plan to pay for and it’s far from guaranteed their responses will sync up.

Error bars offer little more than false precision

Yes, survey perpetrators are getting better about letting us know their survey’s sample size. But does anyone have the time and energy to use this information to compute error bars?

Even if you did, the thing about error bars is that — speaking of uncertainty and the reduction thereof — error bars have an interesting property: They reduce our uncertainty about how certain survey results are.

Error bars are a useful remedy for how so many surveyors indulge themselves in the sin of false precision. They might, that is, “inform” their audience that 53.7% of respondents say they’re doing something or other. This is a bit like the officials at a football game unpiling the stack of players who are all trying to shove the football in a favorable direction, placing the ball in what seems to be a fair spot, then bringing out the chains and measuring, with micrometer precision, whether the team on offense earned a first down.

Those who survey skew results

Which brings me to one final issue: Here in the world of IT many of the most prominent firms that conduct surveys and report on the results also pride themselves as being industry thought-leaders, oblivious to the logical circularity of their branding.

You might think this carping is less than fair to the community of researchers into IT management practices. After all, just getting a decent value of n for their survey is hard enough.

And it is. But.

The point of a typical survey is to inform its audience that something or other, whether it’s a specific product, class of technology, management practice, workforce preference, or what-have-you, is important enough to pay attention to.

Surveys might accomplish this, if your definition of “important” is alotta, as in “Alotta folks say so.”

But the history of the world is filled with examples of the majority opinion being wrong. Here in IT-land many of CIO.com’s readers will remember, with varying degrees of fondness, IBM’s ill-fated OS/2 operating system, whose success was, according to the surveys of the era, assured.

A possible antidote

In principle, I’m violating the principle that nobody should identify a problem without proposing a solution. So if surveys aren’t as useful as they purport to be for helping decide what new technologies are likely to matter; what IT services the enterprise should invest in; what IT management practices should change and how they should change — the question is, what would be more helpful?

My best answer isn’t particularly empirical. It follows this template:

What problem or opportunity are we trying to address? Is it important enough to need addressing?How does the solution we’re researching try to address the problem or opportunity, and is the solution plausible?What’s the plan for overcoming all the forms of inertia the solution will have to overcome?Imagine some strange publisher wants you to write a piece of fiction that tells the story of the solution’s success. Could you imagine authoring a short story or novelette whose average Amazon score would exceed 3 stars, and whose typical review wouldn’t contain the phrase, “Even for fiction this is too stupid to waste time reading”?

No, it isn’t an evidence-based approach. But then, alotta surveys are about the future. And there’s a funny thing about the future — there just aren’t any facts about it to be had.

Yet.

IT Leadership, IT Strategy

Chief data and analytics officers (CDAOs) are poised to be of increasing strategic importance to their organizations, but many are struggling to make headway, according to data presented last week by Gartner at the Gartner Data & Analytics Summit 2023.

Fewer than half (44%) of data and analytics leaders say their teams are effective in providing value to their organization. That’s from a survey of 566 data and analytics leaders globally that Gartner conducted online from September to November 2022.

“It was kind of an eye-opener that one-third of them felt they were not as effective as they could be,” says Donna Medeiros, senior director analyst at Gartner. “There’s so much going on, so many things they are compelled to do versus what they really want to do, know they need to do, know they need to prioritize. They’re spending a lot of time on things like data quality, data management, things that might be tactical, helping with operational aspects of IT. But that’s not helping move the value of the organization as a business forward.”

The responsibilities of data and analytics leaders are many and varied: Sixty percent of respondents cited defining and implementing data and analytics strategy; 59% said oversight of data and analytics strategy was in their portfolio of responsibilities; 55% pointed to data and analytics governance; and 54% cited managing data-driven culture change.

Organizations are still investing in data and analytics functions. Respondents to the survey reported their organizations are increasing investment in data management (65%), data governance (63%), and advanced analytics (60%). The mean reported budget among respondents was $5.41 million, and 44% said their data and analytics teams increased in size over the past year.

Key obstacles to data success

Despite that increased investment, CDAOs say lack of resources and funding are among their top impediments to delivering results, with 13% citing it as their top obstacle and 29% listing resource constraints among their top three hurdles.

The top impediment? Skills and staff shortages. One in six (17%) survey respondents said talent was their biggest issue, while 39% listed it among their top three. And the tight talent pool isn’t helping, Medeiros says. “CDAOs must have a talent strategy that doesn’t count on hiring data and analytics talent ready-made.”

To counter this, CDAOs need to build a robust talent management strategy that includes education, training, and coaching for data-driven culture and data literacy, Medeiros says. That strategy must apply not only to the core data and analytics team but also the broader business and technology communities in the organization.

Other obstacles to data and analytics success, according to Gartner, include:

Culture challenges to accept change (8%, top impediment; 26%, among top three)Lack of business stakeholder involvement and support (10%, No. 1 impediment; 26%, top three)Not enough authority to execute the CDAO responsibilities (9%, first choice; 24% top three)Poor data literacy (5%, top choice; 23%, top three)

“Their life is very complex,” Medeiros says of the current state of the CDAO role. “They have lots of areas of primary responsibility — implementing data and analytics strategy, oversight of data and analytics initiatives, creating and implementing information systems and data management — and the people side — workforce development, upskilling, making the organization data-driven, artificial intelligence, and centers of excellence. They’ve got a lot of complexity and a lot of people they’re answering to.”

This lack of funding for data initiatives echoes the findings of Foundry/CIO.com’s 2022 Data & Analytics Study, which also found other digital transformation initiatives taking priority and lack of executive advocacy for data initiatives as other key roadblocks to data-driven success.

What it takes to lead data strategy

Strategic missteps in realizing data goals may signal an organizational issue at the C-level, with company leaders recognizing the importance of data and analytics but falling short on making the strategic changes and investments necessary for success. According to a 2022 study from Alation and Wakefield Research, 71% of data leaders said they were “less than very confident” that their company’s leadership sees a link between investing in data and analytics and staying ahead of the competition.

Even in the case where an organization taps a designated IT leader to helm data strategy, whether in a chief data officer or chief analytics officer role, the complexity of the role and how it interfaces with other business leaders needs to be addressed for success.

Medeiros likens the CDAO role to a combination of three personas: an orchestra conductor, a composer, and a performer. The conductor looks across the organization and conducts how data and analytics is done, both across business lines with the help of domain experts, as well as in a centralized function. The composer creates and sells the storyline of the value of data and analytics. And sometimes, data leaders must be performers: helping to implement data management, data quality, data trust, spending time on data governance, compliance, and risk.

“These three personas require juggling soft, people skills and technical savvy,” Medeiros says, adding that “the CDAO serves multiple stakeholders across the organization and cannot operate in isolation. They need to align with organizational strategic priorities, collaborate and sell the overall vision and strategy for data and analytics, and get buy-in for their initiatives.”

The most successful data leaders, according to Gartner’s survey, outperformed their peers by projecting an executive presence while also building an agile and strategic data and analytics function capable of shaping data-driven business performance and operational excellence, Medeiros says. Gartner asked respondents to rate themselves across 17 executive leadership traits. There was a strong correlation between those leaders who said they were effective or very effective across those traits and those who reported high organizational and team performance. For example, 43% of top-performing data and analytics leaders said they were effective in committing time to their own professional development, versus only 19% of low performers.

Prominence matters

How CDAOs are positioned in the organization also impacts data and analytics success. According to Foundry’s 2023 State of the CIO survey, 53% of chief data officers and 45% of chief analytics officers report to the CIO, while just 35% and 38% report to the CEO, respectively. Moreover, only 37% of CDOs and 25% of CAOs report having budgets separate from IT overall.

Foundry / CIO.com

Medeiros concedes that CDAOs who report to the CIO and sit within the IT function can still be effective, but, in general, the higher CDAOs sit in the org chart, the better, she says, as this gives them more visibility and better leverage to work on organizational goals.

“It depends on their roles, responsibilities, and how much time they’re allotted for what we call business enablement — not just enterprise IT but actually helping the organization do what matters,” Medeiros says. “It can be things like cost efficiency, but it’s also new products and services that data and analytics supports and can call out.”

Foundry / CIO.com

Indeed, Rita Sallam, distinguished VP analyst at Gartner, says that by 2026 more than a quarter of Fortune 500 CDAOs will have become responsible for at least one data- and analytics-based product that becomes a top earner for their company.

To get there, though, Medeiros says CDAOs must prioritize strategy over tactics. While tactical elements such as data quality and data security are important, improving effectiveness relies on aligning the data and analytics function with organizational strategic priorities and selling the data and analytics vision to key influencers like the CEO, CIO, and CFO.

“Most CDAOs are delivering on immediate-term business goals, but for around half of CDAOs surveyed, delivery against goals for future-term growth and sustainability is lagging,” Medeiros says.

She notes that the most successful data leaders are focusing on improving decision-making capabilities, monetization of data products, and cost optimization, as well as improving data literacy and fostering a data-driven culture.

Chief Data Officer, Data Management, IT Leadership

Multinational insurance and finance corporation AIA New Zealand’s dream is to help make the country one of the healthiest and best protected nations in the world. That’s no small undertaking, and as CTO for the company, it’s Marc Hale’s core responsibility to help achieve that goal by providing a secure and stable platform on which the business can operate and innovate.

“As New Zealand’s largest life insurer and leading health insurer, our purpose is to help New Zealanders live longer, healthier lives,” he says. “With that in mind, we have a science-backed vitality platform that helps New Zealanders understand the current state of their health, remove barriers to better health, and create incentives to stay motivated to improve health through exercise and nutrition. For us, it’s about enabling the technology platforms that support and deliver on that.”

Of course, those platforms can only perform properly when the strength of the people behind them are optimized. So building a cohesive internal culture is integral to IT success, as well as achieving personal and professional goals.

“That is a really important part of the role,” he says. “What supports our organizational strategy from technology is building an engineering culture, being customer-obsessed and outcome-focused, and simplifying and modernizing our technology stack. We really live and breathe it by building a stronger bench around our talent pipeline.”

Part of those efforts is embracing internships, and encouraging people from more diverse backgrounds to get into tech roles by working with IT training and development accelerator Mission Ready, and TupuToa, which develops talent from the Māori and Pasifika community.

“I think there’s an underrepresentation in STEM fields from school,” Hale says. “As leaders, we can be more involved, and champion our organization when it comes to offering people shifting career opportunities. We live in a fast-changing world as we look after IT, and we’re custodians of systems and businesses that will hopefully outlive us. So it’s important to adapt, keep learning, and be able to drive teams forward through motivating them with new technologies and the right problems to solve.”

CIO.com’s O’Sullivan recently spoke with Hale about developing an ever evolving mindset for digital transformation that equally strengthens the business and engagement with customers. Watch the full video below for more insights.

On the approach to transformation: Each role I’ve had over the last 25 years is really a personal transformation. We take on broader roles, more senior roles, or other roles in the organization as we learn about the business, and each of those comes with its own challenges: language barriers, cultural barriers, acronyms, company culture. There’s a real amount of change that comes with every change in country or role. It’s a personal journey of discovery and a way of getting to know yourself better and deeper, too. There are a lot of challenges we face day to day, as leaders, but in each role we take on, we grow, hopefully learn more too, and become a little wiser. It’s always a worry if we treat transformation as a project with an end date. It’s about continued change. For me, it usually starts with an assessment of the current state—where are we, from a technology, people and skills perspective. That’s the foundation. From there, it’s important to engage key stakeholders. In my role, it’s the rest of the executive team and my boss, the CEO, who make sure we develop a shared vision, and are able to collectively prioritize once that vision has been set in motion. Things change, priorities shift. So you have to embrace change and understand that change management is a continual process. Monitoring progress and having a feedback system is critical as well.

On embracing culture: It’s rare that anyone would step into a greenfield environment and have something to build from scratch. Legacy systems are always there. How legacy they are will somewhat depend on the business and the role that someone stepped into. But legacy systems and processes—often very intertwined—are key things to look out for, and not underestimate in terms of the complexity they can bring. Budget constraints, of course, are ever present and need to be worked through very closely. One of my key relationships is with the CFO. We need to work closely to understand what the implications are of taking or not taking certain decisions in our modernization journey. I think culture is a big piece of this too. As technology leaders, we need to understand where the resistance to change is, and try to face into that early. It’s not an easy conversation. People are generally wedded to the way we’ve done things—I find myself in this group as well. It’s natural to want to be more efficient and more effective at what you do, so changing that dramatically is uncomfortable. And trying to understand whether it’s discomfort because of the fear of change, or through lack of skills is an important differentiator. Either of those can be tackled, but if you get them wrong and try and tackle it with the wrong solution, it can become harder.

On combating change fatigue: We have a high cadence for change. I think there’s no fear of that. But it needs to be balanced with a sense of progress and being able to set milestones for deliveries. Often things will need to run as projects, and other things will live as longstanding products as we adopt more agile ways of working. There’s a real balance to it and no real end date to transformation; it’s a continual improvement journey. Sometimes that needs to be accelerated, and acceleration can fit more naturally with transformation because it feels like a bigger change in a shorter timeframe. But overall, organizations should be comfortable being in constant transformation, and people should feel continuously challenged disrupting themselves. For me, ever present are the changes, challenges, and making sure we have stability and availability of our systems. That plays into change management and being able to address how continuous change is in an organization.

On collaboration with the leadership team: There are a number of stakeholders that the role has and we meet often. I have one-to-ones with each of the other execs and it’s where we can really get into the detail of what’s working, what isn’t, and where some of those priorities might be shifting. Ultimately, it’s about time and being accessible as an extension of the leadership team when they’re having key discussions. It’s also about making sure IT can be pulled into conversations at the right time, and not feel like an isolated part of the business. Being able to show adaptability is key. Setting forward a vision and being too stuck with a direction can often feel like IT is inflexible and not agile. So being able to demonstrate building platforms, and a capability that enables the business to go faster really builds trust. The more conversations I have with my boss and with my peers is always time well spent.

Change Management, CTO, Digital Transformation, IT Leadership

Heading into 2020, there were plenty of predictions about the year ahead (not to mention detailed business plans, economic forecasts, scheduled events, and so on)—and all were rendered worthless by the pandemic.

Looking ahead to 2023, therefore, I do so with a healthy dose of humility, and an acknowledgement that there will be monumental events in the year ahead that I did not see coming. However, with all that said, I do think it’s clear that some current trends are under way that will continue in 2023.

At a high level, I’d characterize these trends as having humanist theme. Fundamentally, I view this as an increasing recognition that people are an organization’s most important asset. While companies are now highly digitized, it takes people to keep these digital services running and delivering value.

The pandemic did a lot to accelerate these digitization shifts, but I’d argue these trends will continue to accelerate. So with that, here are my predictions for strategic portfolio planning in 2023.

#1. The Pressure on Project Management Offices (PMOs) Will Intensify

The stakes for digital transformation continue to grow within today’s enterprises. The PMO’s ability to contribute to that transformation will be paramount, not just in the fortunes of the PMO, but in those of the business. The days of the PMO being an administrative finance function are numbered, if they’re not already past. In many ways, the transition can be viewed as the move to become a strategy realization office.

#2. Workforce Management Will Be a Top Priority

In 2023, it’s widely anticipated that we’ll be encountering a recession. Large-scale layoffs in high-profile technology companies have recently been announced. More than ever, there will be an intensified emphasis on cultivating the right mix of skills, roles, and workforces that will be optimally suited to realizing top strategic goals.

 #3. Investments Will Move from Projects to People

Gradually, teams in an increasing number of organizations are confronting the reality that they need to invest in outcomes and strategies rather than short-term initiatives and projects. Instead of paying for discrete deliveries, they’re investing in people and trusting that they’ll generate value, without knowing up front exactly what they’ll deliver. For a long time, there’s been a desire to gain more flexibility, and this is how we achieve that objective.

#4. Tools and Methodologies Will Converge

In years past, different methodologies and associated tools sprouted up within organizations, and operated in a relatively siloed fashion. In 2023, look for increased convergence in areas such as performance management, including methodologies like objectives and key results, strategic portfolio management, and project and portfolio management; and agile execution, such as Scrum and Kanban. Teams will take a choose-your-methodology approach, while being able to ensure all these different teams, tools, and methodologies are interacting with each other, which is key to maximizing value and insights.

#5. The Society 5.0 Concept May Move Closer to a Reality

Several years ago, then Prime Minister of Japan, Shinzo Abe, announced the concept of a super-smart society, which was dubbed Society 5.0. One of the key characteristics of this concept is the shift from technology-centric interactions to those that are more human centric. Increasingly, people will want and ultimately demand software solutions that are responsive to, and aligned with, who they are as individuals. We’ve started to see this transition in consumer software, and this trend will be moving to enterprise software as well.

Conclusion

While we can’t predict the future, it’s vital to understand trends and how they’ll continue to affect our businesses. As we head into 2023, it’s more vital than ever to have a clear perspective of the people we have on our team and the people we serve.

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Explore ValueOps Value Stream Management, built to manage what you value most. 

Digital Transformation

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 blueprint for partners, adding new business opportunities for the company.  

Cloud Computing, IT Leadership, IT Strategy

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 blueprint 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 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, lesser 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 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 advancements 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 to the state. It’s about capacity management and resiliency. All of that together is how we’re measuring the value of going to the cloud.”

Cloud Computing, Digital Transformation

As transformational IT has increasingly become a business imperative, implementation partners have been looking to strengthen their value proposition for their customers. To differentiate themselves from transactional service providers, the more proactive partners are evolving their offerings and approaches, thereby becoming more strategic than they had been in the past.

While IT leaders can maximize the opportunity arising out of this shift by leveraging the partners’ strategies and advanced capabilities, it’s important for them to maintain focus on the risks. Here’s a look at how implementation providers are evolving and how CIOs should approach partnering with them for mutual success.

Shifting to a transformation approach

There is a perceptible change in the way implementation partners are now approaching their clients as compared to earlier, and it is all about becoming a strategic partner for transformational change.

“A partner now enters an account with a broader area of engagement in mind. The discussions may be around a specific project with a CIO, such as implementing a typical solution like Oracle or SAP ERP, but the partner’s core agenda is to bring about an extensive and comprehensive transformation of the client’s IT infrastructure,” says Harnath Babu, CIO at KPMG.

“As the project progresses, the partner discusses the CIO’s pain points and what could alleviate them. This could invariably lead to the partner’s scope getting expanded into, but not limited to, managing emerging technologies, enhancing cost and operational efficiencies, bringing about automation, application development, or improving the system of records,” he says. “Implementation partners are clearly moving from the earlier point approach to a transformation approach.”

Sharing an example of this as it unfolded at KPMG, Babu says, “We engaged with a system integrator to help us with L1/L2 support. In a short time, we scaled it to L3. We found that we could also leverage the partner for managing our infrastructure. Next, we asked the partner to help us with POD development as it was a big challenge to find skilled resources,” says Babu. “So, what started as an L1/L2 service engagement, eventually led to infrastructure management and resource augmentation.”

The POD, or product oriented delivery, is a software development model that entails building small, self-sufficient cross-functional teams that take care of specific requirements or tasks for a project.

Takeaways for CIOs from this trend: Leveraging one partner instead of many frees up CIOs and their teams from more boilerplate deployments, allowing them to focus on what is core to the business. “An implementation partner looks at the total value generated from an account. Therefore, if a CIO gives value to the partner, the latter will reciprocate. This will give CIOs the confidence of having a strong partner behind them. There can then be a project director to manage the project on a day-to-day basis and the CIO can intervene only when there is budget or strategy involved,” says Babu.

 

Building Centers of Excellence 

With the aim of adding value to their customers, implementation partners are increasingly realizing the importance of building technological expertise.

“To keep pace with the market and stay relevant, implementation partners are building on human capital and expertise. For instance, most partners lacked competency in cloud as there wasn’t much requirement related to it in the past. However, as cloud is gaining a strong traction, they have also upped the ante,” says Subramanya C, global CTO at business process management company Sagility (formerly HGS Healthcare). 

So, when Subramanya decided to move the company’s SAP, SharePoint portal, intranet, and other applications to the cloud, he roped in a partner who had a Center of Excellence on cloud and 12 to 15 subject matter experts (SME) on the technology.

“Partners with such capabilities were not seen in the past,” he says. “More than 100 servers had to be migrated in a few weeks. Immense planning, resources, and mitigation of risk were involved in the project. However, the partner’s strong technical expertise, which formed the basis of the center of excellence, made sure that the project got completed smoothly and as per the scheduled plan,” says Subramanya.

Takeaways for CIOs from this trend: Although implementation partners can provide deeper expertise than they could in the past, IT leaders should not be complacent when enlisting it. “For complex projects, like ours, strong governance is required from the enterprise technology leader’s end,” Subramanya says. “IT leaders can outsource a task or an activity to a partner and their SME, but they can’t outsource their responsibilities. Therefore, we ensured a strong governance framework was in place while implementing this project. We also had our own SME working in close collaboration with the partner’s experts.”

 

Collaborating with other partners

The evolution of technology, driven by modernization of applications and services, is catalyzing collaboration among system integrators.

As Archie Jackson, head of special initiatives, IT, and security at digital transformation company Incedo says, “I have seen system integrators coming together to offer solutions, a trend that wasn’t visible in the past. Today, products don’t work in silos. One product has multiple linkages with other products, and it orchestrates and expands into other areas. For instance, a security solution today is not limited only to the network. It is connected to end point and applications, too. Therefore, one project could spill over to another. A partner, however, may not have the expertise or the bandwidth to execute everything, which leads to collaboration with other partners.”

Incedo was in talks with a partner some time back for implementing managed links for connectivity. The end-to-end managed service would have offered remote connectivity to access corporate network from anywhere in the world.

“During the conversations, the partner suggested he could bring another implementation partner to enhance the cybersecurity of the links. It came across as a logical fit because the links had to be secure, but I had not seen a partner collaborating with another one like this in the past,” says Jackson. Takeaways for CIOs from this trend: One implementation partner bringing another partner may help a CIO, but it could also increase the cost of the project. “This is a good option only if a CIO wants to build capability. The primary partner will build his margin into the project for which he is getting the second partner, thereby increasing the cost for the CIO.  If CIOs have the capacity to architect a solution more efficiently, they should do so in-house,” says Jackson.

IT Strategy

Cutting costs by optimizing IT, scaling networks to deliver business value and growth, and changing the direction of the business itself are among the top 10 technology trends Gartner predicts for 2023.

There is growing uncertainty on how to move past the most recent challenges resulting from supply chain issues, war in Ukraine and Eastern Europe, difficulty finding talent, and the evolving financial crisis. To overcome those, some businesses will cut costs, others will continue with existing expansion plans, and some will change the direction of their business strategy completely.

With three central themes—optimize, scale, and pioneer—Gartner has predicted 10 top strategic technology trends for 2023 that can help enterprises see through the current economic and market challenges.

Scale industry cloud platforms vertically

In order to scale their business, organizations are adopting vertical-market clouds, which are increasingly being offered with industry-specifc data sets by a variety of vendors for sectors including healthcare, manufacturing, supply-chain, agriculture and finance.  These days, enterprises are focused on extracting business value from cloud technology, and don’t want to worry about the underlying infrastructure, according to Padraig Byrne, Gartner’s senior director analyst.

“What we’ve seen has been the rise of industry specific modular components, dedicated to particular industry segments that allow businesses to rapidly build differentiated offerings without having to fully develop the underlying technology,” Byrne said.

Reduce friction between development teams and complex infrastructure

Once the cloud environment is ready comes the urgency of getting products to market, and to scale delivery the focus must be on platform engineering.

“But we have complex architectures, or we have hybrid systems and some of the applications on premises and some in the cloud. We also have a lack of skills—a developer that doesn’t know how to build a scalable network,” Byrne said.

The solution is to look at the difference between where the development team sits and the infrastructure layer and look to reduce the friction between the two.

This can be done by building engineering platforms that have reusable components for developers with their tools—such as integrated development environments (IDE), monitoring tools, and CI/CD—all delivered in a self-service development portal. These would be pre-approved tools so developers have access to them when needed rather than having to ask for approval to use this or that tool.

Scale everywhere with Wi-Fi

The wireless trend is based on Gartner’s prediction that by 2025, 60% of enterprises will be using five or more wireless technologies, which among other things means additional use of office Wi-Fi.

That prediction isn’t far-fetched—as Byrne said, consumers are already using up to three wireless technologies daily.

But wireless networks go beyond individual tools. Western Australia mining company Albermale created a private 5G network that allowed scientists and engineers to access systems remotely when needed rather than having to be onsite.

“What this means though, is that your network is not just a cost to the business but if you think differently, it may become something which actually adds value or differentiation to what you do,” Byrne said.

Create digital immune systems

Seventy-six percent of teams responsible for digital products are now also responsible for revenue generation, according to Gartner. Traditional approaches to software development make it hard to create systems that are scalable, secure and stable, therefore hindering the opportunity to generate revenue.

This is where the research firm’s concept of digital immunity comes in, as it brings together multiple modern practices around the application development lifecycle, like observability, to improve what organizations can see, and site reliability engineering and chaos engineering, to improve the resiliency of applications, Byrne said. “It brings together analytics and AI to improve the testing of these tools and then also encompasses end-to-end security across your supply chain. And what this delivers then is applications that are more resilient and will help you avoid outages,” he said.

Gartner predicted that companies have the ability to reduce downtime by up to 80% by adopting some of these technologies—which translates into revenue.

Applied observability for better operations

The concept of applied observability isn’t new, but has implications in the context of optimization, and goes hand-in-hand with the practices related to digital immunity. Byrne explained it as collecting data from decisions made, then collecting data on the context in which decisions were made and applying analytics to the context in order to create a feedback loop to make more business-value driven decisions.

Trust, risk and security management for AI

AI TRiSM—trust, risk and security management—is, simply put, making AI trustworthy. Even among the most experienced enterprises, Gartner has found that only 50% of AI models ever hit production and that the reasons behind this are lack of trust in the data, and problems with security and privacy.

First, to improve the adoption of AI, organizations must be able to explain the reason why a computer came to a decision. This is accompanied by modelops, which is a Gartner term for the governance and life cycle management of a wide range of operationalized AI and decision models, including machine learning, knowledge graphs, rules, optimization, and linguistic and agent-based models. The result of using modelops, according to Gartner, is that models get into production faster and with less friction.

Next comes the use of advanced techniques like adversarial AI, used to generate one model to train another “and we see this already being used in areas like image generation as well as games like chess,” Byrne said. And finally, ethics guidelines and strong data protection are needed.

“All of this means that these models will have enhanced trust and therefore, you will likely, at the development effort, make it into a production environment,” Byrne said.

Start creating superapps

Gartner suggests that enterprises can pioneer news ways to engage customers by developing superapps. Superapps combine some of the functionality of a regular app with the attributes of an app platform and an ecosystem, according to Byrne. Superapps not only have their own differentiated features, but also the ability to build out third party applications with a shared common data model between the core app and the third-party software.

Moving into this early on will give enterprises an advantage, Byrne said, and he sees opportunities around finance and health, among other verticals.

Adaptive AI to respond to organizational change

Once problems with trust, production, and generation of personalized analysis have been dealt with, enterprises can jump onto adaptive AI, which uses real-time feedback and adaptable learning algorithms to gain a sense of the business and provide response to changing environments.

It enables enterprises to create and access new data for testing in these environments as well as the ability to personalize the output of the algorithms for the user in a continuous manner that provides dedicated individualized offerings to users. “This is adaptive AI and it’s a very different mindset from traditional AI,” Byrne said.

Metaverse will combine different technologies

For those skeptical of the metaverse, Byrne said that it comprises a number of different technologies and is related to business problems like lack of trust in data, or how to improve customer service. One way to use it could be through avatars and chatbots to improve customer delivery. Other ways include use of gamification for training and augmented reality for shopping experiences. Gartner found 51% of Gen Z expects some form of augmented reality to come to fruition in the next two years.

Technology will have a role in sustainability

Gartner’s top trends wrap up with sustainability and the role IT can play. Byrne warns that it is not just about the environment and climate change but also about the people behind the business, the social aspects of an organization, improving work culture, improving diversity, equity and inclusion for employees, and improving training.

But technology has an especially important role to play when it comes to environmental sustainability, particularly around solutions for energy reduction for IT services, and the use of analytics and traceability of renewable energy. Enterprises can take these into consideration, define what is applicable to their business, and then work on a roadmap.

“And then you build your own roadmap and realize that not all of these technologies need to be delivered at once. Once you determine the timeframe that these can be delivered, you can set your own path through this and build your own organization-centric action plan,” Byrne said.

IT Strategy

C-level executives are most interested in strategic assets and initiatives that will advance, transform, and grow their enterprises. They continually want to make “cost centers” more efficient and more cost-effective, while investing in what will accelerate, empower, and protect the business operations and its customer base.

Because data and digital technology have become so integral into any enterprise’s lifeblood, senior leadership teams must differentiate between the strategic aspects of IT and the tactical parts of IT cost centers. Storage has emerged in 2022 as a strategic asset that the C-suite, not just the CIO, can no longer overlook.

Enterprise storage can be used to improve your company’s cybersecurity, accelerate digital transformation, and reduce costs, while improving application and workload service levels. That’s going to get attention in the board room. Here’s how to equip yourself for that discussion with C-level executives. The following are three practical ways to make enterprise storage a strategic asset for your organization.

1. Make storage part of the corporate cybersecurity strategy

According to a Fortune 500 survey, 66% of Fortune 500 CEOs said their No. 1 concern in the next three years is cybersecurity. Similarly, in a KPMG CEO survey, CEOs also said cybersecurity is a top priority. The average number of days to identify and contain a data breach, according to security analysts, is 287 days. Given these facts, changing the paradigm from an overall corporate security perspective is needed.

Too many enterprises are not truly equipped and prepared to deal with it. Nonetheless, companies need to ensure that valuable corporate data is always available. This has created an urgent need for enterprises to modernize data protection and cyber resilient capabilities. The answer that CEOs, CIOs, CISOs and their IT teams need to take is an end-to-end approach to stay ahead of cybersecurity threats.

You need to think of your enterprise storage as part of your holistic corporate security strategy. This means that every possession in a company’s storage estate needs to be cyber resilient, designed to thwart ransomware, malware, internal cyber threats, and other potential attacks. Cybersecurity must go hand-in-hand with storage cyber resilience.

It’s prudent to evaluate the relationship across cybersecurity, storage, and cyber resilience. Both primary storage and secondary storage need to be protected, ranging from air gapping to real-time data encryption to immutable copies of your data to instantaneous recovery. 

What should you do? Perform a comprehensive analysis of your corporate data, determine what data needs to be encrypted and infused with cyber resilience and what doesn’t, and figure out how the protection needs to keep your company in compliance. You also need to decide what to do for modern data protection and you need to figure out what to do from a replication/snapshot perspective for disaster recovery and business continuity.

2. Use a hybrid cloud strategy to accelerate digital transformation

More than 75% of CIOs identified digital transformation as their top budget priority of the last year, according to Constellation Research. Companies are leveraging digital capabilities to better serve their customers, accelerate new products and services to market, and scale their operations. The growth and importance of data continue to proliferate exponentially.

The role of hybrid cloud infrastructure – part of your data on-premise – as the key enabler of this megatrend is at the forefront. A core value of cloud services is the support for digital transformation. Digital transformation is enabled and powered by hybrid cloud computing, offering increased flexibility, rapid application development and deployment, and consumption-based economics. This is essential to competing and remaining relevant in today’s world of data-driven business.

Data is the lifeblood of all modern enterprises. How to collect, manage, store, access, and use the data determines the level of success that a company will have. Enterprises can either innovate their data, or be strangled by the data, or even be held hostage for the data. This is why you need the strategy and the infrastructure to drive the future of data for your business.

As businesses evolve themselves digitally, a hybrid cloud strategy orchestrates all the different aspects of it in a mixed computing, storage, and services environment, comprised of on-premises infrastructure, private cloud services, and a public cloud such as AWS. Just in the last 18 months, advancements have been made for “on ramps” between private cloud and the public cloud. This hybrid cloud infrastructure becomes the cornerstone for an organization’s ability to be agile and accelerate business transformation.

3. Reduce IT costs

It can be challenging to identify areas in IT to reduce costs, while maintaining the level of service or capacity. But here’s a practical tip that can be a quick win for an enterprise: CIOs, CISOs and their IT teams can lower IT costs by consolidating storage arrays.

Because of the advancements in storage-defined storage technology, an enterprise can replace 50 arrays with two arrays, while still getting all the capacity, performance, availability, and reliability that are needed. This strategic consolidation saves on operational manpower, rack space, floor space, power expense, and cooling expense. In short, dramatically reducing your CAPEX and OPEX.

You can consolidate storage while, simultaneously, improving access to data across a hybrid cloud and a container-native environment for greater resilience, lower application and workload latency, and higher availability. For today’s enterprise requirements, 100% availability is a must.  

A hybrid cloud approach with a strong private cloud configuration creates the opportunity to consolidate storage arrays for maximum efficiency. Furthermore, with a private cloud, you have better, more exact control over cost structure and service level agreements (SLAs). Essentially, this strategy enables you to match an SLA, such as application performance and availability, with a higher level of control. 

Switching to consumption-based pricing models for storage is another way to reduce costs. Organizations can choose to flex up or flex down based on fluctuating needs for storage, utilizing storage-as-a-service. The worldwide analyst firm Gartner predicts: “by 2023, 43% of newly deployed storage capacity will be consumed as OPEX, up from less than 15% in 2020.”

Alternatively, companies can choose capacity on demand and seek out elastic pricing. All of these options have made storage more cost-effective. There are options across OPEX and CAPEX. You can even get a mix of OPEX and CAPEX to realize those cost savings.

Key takeaways

Think of your storage as part of your holistic enterprise security strategyA hybrid cloud infrastructure should be the cornerstone for your organization’s ability to be agile and accelerate business transformation.Strategic consolidation of storage arrays reduces CAPEX and OPEX.

To learn more about enterprise storage solutions, visit Infinidat

Data Management