In the war for talent, sometimes the solution is right in front of you. For businesses struggling to compete for tech talent, investing in your current talent through upskilling and training initiatives can provide invaluable returns, as many IT leaders are finding.

A study from Korn Ferry estimates that by 2030 more than 85 million jobs will go unfilled due to a lack of available talent, a talent shortage that could result in the loss of $8.5 trillion annual revenue globally. While automation may be able to fill some gaps, the study also posits that human capital will be just as important as automation in the future, leaving organizations without robust training programs subject to the whims of a talent market in short supply.

According to the National Bureau of Economic Research, companies have steadily dropped the ball on workforce training and upskilling since the 1970s. Oftentimes, workers are pushed to meet skills gaps without the necessary training, setting the employee and business up for potential failure. But shifts in workforce strategies in recent years have seen more companies developing strong internal training programs to reskill, upskill, and promote employees within the organization.

In addition to helping fill skills gaps, investing in the career growth of your employees can also foster a greater sense of trust, leading to a more resilient and productive workforce that is less likely to quit, according to data from Gallup. The return on investment in internal workforce training and upskilling programs can’t be overlooked, as the successes of the following four companies can attest.

Capital Group invests in careers for the long run

For financial services company Capital Group, the secret to competing in a tight IT talent market is to stay focused on a long-term employee investment strategy. Capital Group leadership believes employee satisfaction is just as important as customer satisfaction, and a key part of that is ensuring that employees have ample opportunity to grow their careers within the company. This includes internal bootcamps, courses for developing subject matter expertise, and an internal talent marketplace that gives employees more mobility within the organization.

Employees can also explore various career paths within Capital Group through its Technology Rotational Experience (TREx) program, a 25-month career development program that places participants across three different IT teams. Through TREx, employees can gain experience in other departments, work with new technologies, and identify whether there’s something new that they might be interested in working on moving forward.

“We focus on the long term,” says Global CIO Marta Zarraga. “Every single decision we make is based on the healthiness of the organization long term.”

And that includes ensuring employees can stay and grow with Capital Group, rather than leaving the organization to move their careers forward. TREx and other internal training programs, which include bootcamps, “learning journeys” for developing subject matter expertise, and mentorships, make employees feel valued and reinforce the organization’s culture of growth and learning, while also meeting organizational talent needs in IT departments.

“I can show up as myself and develop the skills and confidence for my career in software development within the financial industry. From early on my contributions at work have been respected, and I’ve found it very easy to reach out and ask questions to people on different teams,” says Aimee Oz [they/them], a software development engineer at Capital Group who participated in an internal bootcamp.

Progressive bootcamp bridges skills gap

Insurance company Progressive has developed an in-house IT Programmer Bootcamp to reskill non-technical staff for technical roles within the organization to meet skills and talent gaps in the organization. And by turning inward to find qualified candidates within its own workforce, Progressive can also leverage the wealth of knowledge candidates already have about the organization, while “knocking down some of those barriers of eligibility for some of these tech jobs,” says Stephanie Duca, leadership development consultant at Progressive, and leader of the IT Bootcamp program.

The pilot program was launched in 2021 with eight participants who came from non-IT roles such as customer support, underwriting, and claims. Employees attend the 15-week intensive training program full-time and are compensated for their time in the program, ensuring they will be able to focus entirely on the training. Employees do not need to have a background in tech to join the program and they are guaranteed a job placement along with adjusted compensation to reflect their new role. Progressive plans to continue expanding this program to include other areas of focus, such as data analytics roles.

“I just know that it’s sparked some real passion and an appreciation for Progressive — our employees see that we want to invest in them and keep them here and retain them,” says Duca.

Altria’s career development focus reaps rewards

Fostering career development is a key strategy for retaining vital talent. At tobacco company Altria Group, employees are given the chance to engage in upskilling and training, gain experience working in departments outside their own, and utilize the company’s structured career planning process. In fact, Altria’s dedication to investing in employees earned them first place for career development on IDG’s Best Places to Work 2021 survey.

Career development is a focus for all employees, even entry-level workers, and everyone is given several opportunities to grow their skills and learn new technologies. For example, an entry-level code developer at Altria will be thrown into highly technical work right away, so they gain experience fast. And then throughout their first five to six years with the company, they will be moved around IT departments to work on different projects, gaining more experience and potentially finding out what they’re most passionate about.

“In many cases, we’re trying to put them into a role that ultimately is going to make them sweat — it’s going to really challenge them,” says Dan Cornell, vice president and CIO of Altria Group.

Employees also go through an annual talent planning review process to assess where they are in their careers, what they aspire to within the organization, and how they want to shape their career moving forward. Managers can identify areas for growth, what skills can be developed, opportunities for training, and potential experiences in other departments they might benefit from. There’s also a heavy focus on helping employees pave a career path if they aren’t interested in leadership positions. Oftentimes, it can feel like the only way up is the leadership path, but helping employees discover there are other paths within the organization can go a long way for retention.  

Talent development pays off at Capital One

Upskilling and cross-training programs are key factors in improving employee productivity, retaining top talent, and filling skills gaps. Financial services company Capital One focuses on “developing the whole person” by leveraging internal professional development programs, including a full-stack development academy, the Capital One Developer Academy (CODA), and Capital One Tech College.

With over 11,000 engineers across more than 2,000 agile teams, Capital One has worked to run individual teams as if they’re each a small business. It’s a strategy that allows the large organization to stay agile, while also attracting and retaining engineering talent through the promise of getting to work on open-source projects, in an agile environment, and on a small team.

“It keeps a big company very nimble, creates that autonomy and then drives a lot of that team dynamic and team culture down into the other groups of folks that are releasing software every day of every week to our customers and our associates,” says Mike Eason, senior vice president and CIO of enterprise data and machine learning engineering at Capital One.

Its CODA initiative is a six-month software engineering program for full-time Capital One employees to learn full-stack development principles. It helps employees inside or outside of IT get the training they need to become a software engineer within the organization. The Capital One Tech College focuses more on upskilling employees through free training and certification courses, with opportunities to attend in-person and online courses on their own time. The investment in employees helps Capital One retain its best tech talent, while also cultivating stronger tech skills and expertise through the ranks.

IT Skills, IT Training 

Contact centers are evolving rapidly. The days of single-channel, telephony-based call centers are long gone. This old model has given way to the omnichannel customer experience center.

In legacy call centers, the customer’s pathway through sales or service was relatively linear. Call in, speak to an agent, and (hopefully) resolve the issue. In this system, the manager’s focus was strictly on ensuring there would be enough well-trained staff to handle every call as efficiently as possible.

Nowadays, however, the customer journey is more complex, and the path to successful customer experience (CX) may weave its way through various channels, touching both human and robot agents along the way. Today’s managers must not only build an adequate staff, but they must also choose the right solutions to effectively meld together technological and human elements to deliver a near-flawless CX. 

Although many solutions have proved important for managers seeking to create successful contact centers, none are more important than the cloud and conversational AI. You might think of these as the twin pillars of success for today’s contact centers. However, as we’ll discuss here, they’re not sufficient on their own. There’s a third pillar to consider: quality assurance, or dedication to ensuring a finely tuned customer experience at every stage in the customer journey.

The cloud makes the contact center omnipresent

It looks like we’ve reached the tipping point for cloud adoption in contact centers. Deloitte reports that 75% of contact centers plan to migrate their operations to the cloud by mid-2023, if they haven’t already done so. IDC forecasts that investments in cloud solutions will account for 67% of infrastructure spending by 2025, compared to only 33% for non-cloud solutions. Genesys, a major contact center provider, recently announced that, going forward, it will focus its efforts on its Genesys Cloud CX software rather than its on-premises solutions.  

Considering the cloud’s potential, it’s not surprising to see that it’s taking over. Fundamentally, the cloud allows contact centers to keep pace with the changing expectations of employees and customers simultaneously.

The pandemic quickly changed what both groups were looking for. Employees came to expect more accommodating remote work arrangements, and those expectations have held strong even in 2022. According to research by Gallup, only 6% of workers who can do their jobs remotely actually want to return to a full on-site arrangement. Expectations for CX, meanwhile, have continued to rise to new heights, whether in terms of omnichannel service or personalized experiences.

The cloud makes it much easier for contact centers to meet these expectations. Without the need to rely on legacy, brick-and-mortar infrastructure, remote agents can deliver service to customers from anywhere at any time. Plus, the cloud more effectively facilitates seamless omnichannel service delivery and efficient software updates.

From setup to ongoing execution, the cloud is simply easier to manage. With no telecom hardware to purchase, installation and setup happen more quickly. And contact centers can rapidly scale up and down as needed, and when needed, allowing them to effectively manage costs.

The net effect of these benefits is that the cloud creates a new kind of contact center — one that’s omnipresent to deliver a modern customer experience from anywhere and to anyone.

Conversational AI transforms CX

One of the key benefits of moving to the cloud is the availability of conversational AI that can power self-service solutions. This technology, which is indispensable to chatbots and IVR, enables bots to interact with customers in natural — even human — ways.

Thanks to powerful components of AI, such as natural language processing and machine learning, bots are increasingly able to provide much of the service customers seek. In fact, in today’s self-service economy, conversational AI allows consumers to solve many of their own issues. Even more, the machine learning capabilities of AI allow it to easily and quickly collect customer data and use it to personalize the service experience. Unsurprisingly, organizations that employ conversational AI see a 3.5-fold increase in customer satisfaction rates.

That boost in customer satisfaction stems not only from offering personalized self-service, but also from organizations making the most of their human service. While bots handle many of the simpler requests, they reserve agents’ time for handling more complex matters. Ultimately, companies that deploy them can improve customer service while also cutting costs by between 15% and 70%.

This AI-powered CX transformation is already well underway in many industries. Banks use conversational AI to power customer self-service with simple tasks, like money transfers and balance inquiries. Hotels employ it to offer streamlined booking and concierge services. And retailers put it to work engaging customers in more personalized ways.

These are only a few of the basic benefits that forward-thinking companies can gain from deploying conversational AI. Its more advanced forms will power a new kind of proactive CX in the years ahead, shaped by powerful tools like sentiment analysis. 

True success requires a third pillar: quality assurance

Although critical for today’s contact centers, those two pieces are incomplete without the third pillar of quality assurance.

The expanded service capacities enabled by the cloud and conversational AI add new layers of complexity to a contact center’s CX delivery. Cloud migration, for instance, often involves bringing together many disparate legacy systems and remapping the entire customer journey. It requires extensive testing and mapping to make sure it’s done right. 

And as powerful as conversational AI is, it still requires a lot of human guidance to ensure it’s doing its job correctly. Without the capacity for that guidance, IVR or chatbot solutions may cause more CX problems than they solve. They can also be more costly — defects discovered in the IVR or chatbot production environment are much more expensive to undo than they would be when discovered in design.

The best way to provide cost-effective quality assurance is through a robust set of testing solutions that can work with any cloud, IVR, or chatbot solution that a contact center uses. As a platform-agnostic CX assurance solution, that’s exactly what Cyara is designed to do. 

With a powerful solution like Cyara, businesses can speed up cloud migration, correct voice quality issues, load-test IVRs, and performance-test chatbots, regardless of which solutions they use. They can even run more advanced chatbot tests to see how well they follow natural human conversation flows and recognize various speech patterns.

This kind of quality assurance allows contact centers to jump to the cloud and deploy conversational AI with confidence, knowing that both will push their CX forward. Together, these three pillars provide a firm foundation for contact centers of the future.

Ready to get started? Cyara can provide assurance for your cloud migration so you can start building these pillars. Reach out to get started today.

Digital Transformation

This post is brought to you by NVIDIA and CIO. The views and opinions expressed herein are those of the author and do not necessarily represent the views and opinions of NVIDIA.

CIOs seeking big wins in high business-impacting areas where there’s significant room to improve performance should review their data science, machine learning (ML), and AI projects.

A recent IDC report on AI projects in India[1] reported that 30-49% of AI projects failed for about one-third of organizations, and another study from Deloitte casts 50% of respondents’ organizational performance in AI as starters or underachievers.

That same study found 94% of respondents say AI is critical to success over the next five years. Executives see the AI opportunity for competitive differentiation and are looking for leaders to deliver successful outcomes.

ML and AI are still relatively new practice areas, and leaders should expect ongoing learning and an improving maturity curve. But CIOs, CDOs, and chief scientists can take an active role in improving how many AI projects go from pilot to production.

Are data science teams set up for success?

A developing playbook of best practices for data science teams covers the development process and technologies for building and testing machine learning models. Developing models isn’t trivial, and data scientists certainly have challenges cleansing and tagging data, selecting algorithms, configuring models, setting up infrastructure, and validating results.

Leaders who want to improve AI delivery performance should address this first question: are data scientists set up for success? Are they working on problems that can yield meaningful business outcomes? Do they have the machine learning platforms (such as NVIDIA AI Enterprise),infrastructure access, and ongoing training time to improve their data science practices?

CIOs and CDOs should lead ModelOps and oversee the lifecycle

Leaders can review and address issues if the data science teams struggle to develop models. But to launch models and ensure success, CIOs and CDOs must establish a model lifecycle or ModelOps.

The lifecycle starts before model development and requires educating business leaders on their roles in contributing to AI projects. It also requires steps for planning the infrastructure at scale, instituting compliance and governance, creating an edge security strategy, and partnering with impacted teams to ensure a successful transformation.

Here are several factors to consider:  

Educate business leaders about their roles in ML projects. Have business leaders defined realistic success criteria and areas of low-risk experimentation? Are they involved in pilots and providing feedback? Are they ready to transform business processes with machine learning capabilities, or will they slow down investments at the first speed bump?Adopt a build, buy, or partner when developing models. Sometimes, developing proprietary models makes sense, but also evaluate frameworks such as recommendation engines or speech AI SDKs.Think a step ahead regarding production infrastructure requirements. The lab infrastructure used to develop models, and the lower scale required to pilot an AI capability, may not be the optimal production infrastructure. For example, AI in healthcare, smart buildings, and industrial applications that impact human safety may require edge or embedded computing options to ensure reliability and performance.Plan for large-scale AI applications on the edge. Where there are thousands of IoT devices, there are opportunities to deploy AI applications to run on the devices. For example, fleets of vehicles, including delivery trucks, construction tools, and farming equipment, can use device-deployed AI apps to provide real-time feedback to their operators that improve productivity and safety. An edge management solution that deploys the apps to the devices, supports communications, and provides monitoring capabilities is critical.Establish MLOps, ModelOps, and infrastructure-monitoring capabilities. The data science teams will need MLOps to automate paths to production, while compliance should require ModelOps and want model updates to address model drift. Infrastructure and operations teams will want monitoring to help them review cloud infrastructure costs, performance, and reliability.

IT teams don’t just deploy apps. They participate in planning to deliver business outcomes and then institute DevOps to ensure delivery and ongoing enhancements. Applying similar practices to data science, machine learning, and AI will improve successful pilot and production deliveries.

[1] IDC FutureScape: Worldwide Artificial Intelligence 2021 Predictions — India Implications

Artificial Intelligence, Data Science, Machine Learning

For veteran CIO Amir Arooni, the aha moment came during a master’s dissertation deep dive into why there were so many IT project failures. Digging through research examining the impact of standard conventions like siloed teams and staged gate processes, Arooni began percolating ideas for how to shift IT organizations away from the traditional project-oriented culture to something more agile, with greater business accountability and more responsiveness to changing customer needs.

“We came to the conclusion that the way we do things in IT is outdated,” says Arooni, now executive vice president and CIO at Discover Financial Services. “If you want to increase the success of IT projects, you need to create a team that is responsible for what they make and takes ownership over what they do.”

Since that 2011 revelation, Arooni has been doing just that: redefining IT organizations and service delivery models to embrace agile ways of working, including creating product-centric structures with persistent teams responsible for the entire lifecycle of a product.

Amir Arooni, executive vice president and CIO, Discover Financial Services

Discover Financial Services

Arooni is joined by scores of industry leaders across segments such as retail, financial services, healthcare, even government entities moving in this direction. Forrester estimates about a third of organizations have either made or are in the process of orchestrating the shift to product-centric structures with more to follow as cloud migration gives IT a platform to retool for greater business agility, according to Charles Betz, vice president and research director for enterprise architecture at Forrester.

“There’s been a fundamental hunger for the responsive creation of new digital capabilities through the dawn of computing and now there’s actually an ability to deliver systems at the speed of business,” Betz says. Cloud delivery is part of the solution, but product-centric teams help build trust and continuity of expertise. “Organizations don’t want fractional allocation — people rolling on to a project and rolling off,” he explains. “They want to bring work to a team … and make a team more responsible for outcomes as opposed to deliverable activities.”

Arooni, along with his CIO counterparts, have made a variety of structural changes and initiated a range of best practices to ensure a successful transition away from legacy-style project management to an IT operating model architected around product centricity. Following are their most significant shared strategies for making the shift successful.

Establish product ownership

Traditional IT project teams are no match when the goal is all about building solutions quickly and being hyper responsive to customer needs. At JP Morgan Chase, the approximately 12,000-person IT organization is being completely revamped to build solutions quickly with teams encompassing product owners along with technology, data, and design leaders.

Gill Haus, CIO for Consumer & Community Banking, JP Morgan Chase

JP Morgan Chase

Consider this product structure in the context of the account opening process. Instead of each business line, such as checking accounts or mortgage applications, employing a different team to design different account opening flows, account opening becomes the product backed by its own multifunctional Chase team. That team manages the account opening function throughout its lifecycle, from architecting the experience to managing backlogs and making tweaks to reduce friction for customers. The end result is that the account opening process remains consistent across channels. It can be reused by any other lines of business or Chase groups, streamlining software delivery while also ensuring a seamless customer experience across the Chase portfolio.

“The teams are responsible for the product and have the autonomy and wherewithal to make changes,” says Gill Haus, CIO for Consumer & Community Banking (CCB) at JP Morgan Chase. “No matter how agile you are, you are solving different problems for customers in different ways unless you are organized by product and are customer backed.”

TruStone Financial is also knee deep in transforming its IT organization and operating model, transitioning away from a program management office (PMO) to a product-centered organization. Leadership worked to identify process owners within the business to become product owners within product families that are essentially owned by IT, according to Gary Jeter, TruStone’s executive vice president and chief technology officer. 

“This helps us respond quicker and identify the right project to execute, delivering business value quicker,” Jeter says. Establishing technology and business owners also drives collaboration. “It gets people closest to the work helping to prioritize and drive deliverables,” he explains.

While it can be a challenge to identify the right product owners within the business, the changes, which have been implemented in phases since last September, are already increasing TruStone’s business agility, Jeter says.

Gary Jeter, EVP & CTO, TruStone Financial

TruStone Financial

Last December, the firm was presented with an opportunity to expand its portfolio by a fintech specializing in automotive refinancing — a set of services that weren’t part of its offerings or IT stack. Because of the IT organization transformation, TruStone was able to integrate the new auto refinancing capabilities into its digital banking platform in just shy of two months.

“This was not in the budget for the year nor was it on our roadmap, yet we were able to initiate cost-benefit analysis, do demos, and get it deployed as a two-month project,” he says. “In the old PMO model, it would have been added to the project backlog, taken a month to get in front of EVPs, then approved and probably double that time to get it across the finish line.”

Embrace agile practices

Few associate a government agency with a fast-track to business value, but Jamie Holcombe Jr., CIO at the United States Patent and Trademark Office (USPTO), would beg to differ thanks to the agency’s wholesale transformation to a product-oriented IT organization and agile culture. Along with replacing project teams with product teams and reimagining its PMO to be more of a coaching resource, USPTO adopted agile practices in earnest, including daily scrums, working in sprints as opposed to project plans, and embracing DevSecOps processes, Holcombe says.

Jamie Holcombe Jr., CIO, USPTO

USPTO

Changes were implemented on a small scale, among two or three teams at first, then scaled up.  Ongoing communications emphasized that the new patterns of working and team structure were being made for the long haul, not just a passing fad. Soon, Holcombe says, people began to see results and wanted to be part of the transformation. “We were delivering all this stuff we never delivered before, and everyone wanted to be part of it,” he explains.

As part of its journey Align Technology, which manufacturers the Invisalign orthodontic devices, also reorganized its teams around products, processes, and experiences, not systems. Instead of a backend ERP team and front-end UI/UX team, the company now has a single “payments team” that melds people with expertise from the relevant ERP platform and UX designers, in addition to product owners, all driving towards the same goal: delivering a seamless payments expertise for customers, according to Ema Patki, vice president of software engineering at Align.

“The pivot from systems to processes and products has changed the focus of the discussion, from which applications we need to integrate to what is the process and experience we want to deliver and what capabilities do we need to build to realize those experiences,” Patki says. “These capabilities are then delivered using Scrum/agile methodologies in frequent, low-risk deployments to production, eventually leading to the launch of an end-to-end product.”

Establish metrics to incentivize teams

One of Align’s critical success factors was finding ways to incentivize teams to define their operating and governance models.

Ema Patki, vice president of software engineering, Align

Align

For example, the platform teams — which manage an overall platform like ERP or CRM and are responsible for best practices, uptime, and system hygiene — give engineers performance feedback specific as to how well product teams met the platform teams’ specific goals. At the same time, the product teams — which manage customer experience across multiple platforms — evaluate their counterparts on the platform side, providing input on the timeliness of code releases or assessing whether there were appropriate levels of coordination.

“This gives everyone a sense of ownership and allows people to hold each other accountable to collective goals,” Patki says.

Talent and culture are essential

Arooni came to Discover in March 2020, during the height of pandemic shutdowns with a primary mission to transform the technology organization, improve alignment between IT and business, and steer the organization to deliver better and faster results.

On Arooni’s watch, Discover launched Runway, a three-pronged program to transform IT by shifting to a product-centric way of working, automating as much as possible, and upleveling its talent bench, both by hiring more seasoned experts and by nurturing internal team members.

Central to the upskilling strategy is the Discover Technology Academy, a hub for training led by internal experts, along with learning journeys that provide clear guidance and pathways for advancement. There is also a slate of internally run hackathons and bootcamps.

“In the past, people came to the technology function as novices and built up expertise within Discovery,” Arooni says. “We needed to have better talent so we created a way to educate our own people as well as hire from the outside at a higher level of proficiency. Someone wants to know what an excellent API looks like — now they go to Discover Tech Academy because the standards and education are there.”

Listening to employees and understanding what’s working and what’s not is central to the change management exercise, and to winning collective hearts and minds. Employee feedback surveys, one-on-one sit downs, all-hands meetings — anything that helps the organization understand why you are doing what you are doing, including the pain points the change will resolve, is a worthwhile approach, Arooni says.

So too is sharing success stories and showing team members what success looks like. Doing so will motivate people and engender broad organizational support.

“You need to show leadership believes in the new direction and that you’re able to scale the changes,” Arooni says. “Tech people need to learn how to be thought leaders instead of order takers, and their business colleagues need to learn to deal with technology. You need to educate everyone about what you are doing.”

Even though agile is at the heart of this transformation, reorienting an IT culture to be product-oriented, not project-focused is a marathon, not a sprint.

“There isn’t a done,” says Chase’s Haus. “You will continue to be doing this going forward. Being an agile organization means being agile forever, learning and adapting as you go to provide better experiences for customers.”

IT Leadership, IT Strategy

Since its beginnings in 1914 to what it is now as a global consultancy firm with nearly 30,000 employees,  Booz Allen Hamilton has been able to evolve through the ages by helping to redefine the industry through advancements in technology and sourcing the right talent. Brad Stone, who has been with the company for over 25 years but recently became its CIO in 2021, had deep knowledge of the brand, its structure and ambitions, but understood that in his new role, there was a lot to learn, especially where improvements could be made.

“It was interesting joining this team and becoming the CIO at an organization that I knew well,” he says. “But what I did see despite the tremendous talent was that service delivery was often fractured and not fully integrated to a set of outcomes, and at times driven by different corporate priorities that were all important, but not seamless against an integrated outcome. So we had great parts, but our sum was not greater than our parts.”

From this staring point, Stone hit the reset button, mapping out five core organizational principles that have accelerated growth and helped strengthen the business. Ongoing and unpredictable disruption also led to a focus on simplification with staff and customers, and has changed the way the IT team thinks about strategy and taking informed risks, with a focus on a DevSecOps lifecycle, for example, to pipeline things and get aligned to improve accountability and transparency.

“We defined a clearly set service catalog against an ITIL framework, and were able to set portfolio leads around the capabilities we’ve developed,” he says. “What it enabled us to do is get more of a centralized purpose to accelerate growth and enable business success, which ties back to the idea of attracting staff and giving them some autonomy or ownership while still being part of the greater good. You change the world one individual at a time, and the way we’ve organized it, I’ve seen that cultural feel.”

Stone recently spoke at a recent summit on Leading in Disruptive Times with Julia King, contributing editor at CIO, about key leadership methods to fuel success, and how being “client zero” has enabled Booz Allen to inspire and retain talent while continuously learning and embracing technology to build trusted relationships.

Here are some edited excerpts of that conversation. Watch the full video below for more insights.

On 5 organizational principles: It starts at the top with operational excellence—actually living it, not just saying it. So that’s accountability of what the metrics are, how the company is faring and celebrating overcoming hardships, like decommissioning something. I love to clean stuff up and when we turn off a service to simplify it, we make the other services we provide even better. Second, there’s having a resilient enterprise that is risk-informed. We have to recognize that things will go bad, and it’s about our ability to recover those. The third one ties back to providing innovative service and solutions to our users. If you don’t, people will find it for themselves and run it in your shadows. The fourth is about being a data-driven organization. We need to make sure we have a single source of truth across organizations. We have multiple platforms to run our business and to perform that, we need to not only have that central source of truth, but it needs to be future-proofed to scale with our organization. And the last one is we want to attract staff. We’re lucky to attract and retain some of the best in the industry, and we set the goal of being a premier organization for IT and cybersecurity professionals. So what we do across all five of these is hold ourselves accountable to them, drive metrics against them, and define critical success factors, and, again, celebrate it and tackle areas we need to improve.

On handling disruption: Disruption provides a lot of opportunities to rethink why we do things and how we do them. We are a professional services organization at our core due to trusted relationships. The pandemic challenged that because we were a culture that wanted to shake hands and let people know in person how we connected with them. And the disruption over the past couple of years has made us have to change that. We’ve had to embrace technology not only as an enabler, but ultimately as a foundation by which we build those trusted relationships. It has challenged us and changed our different clients. Fortunately, our people are unbelievably resilient. The other part is to have a core infrastructure team that can respond. But as we come out of the pandemic, that disruption has to lead to simplification and balancing of what we had with a remote hybrid model for our nearly 30,000 global employees, so it meets their needs. The key is to simplify that down so we can give them something to connect with their fellow employees, our clients, and their communities. If you’re able to identify some archetypes, look for the greatest good, and then handle those exception cases—as what we deem specialized services—it allows us to continue providing foundational services that are important to that connection. But budgets aren’t increasing, so you need to be efficient.

On leadership: Over the past few years, I think any CIO or technology leader has been marked by agility, capacity to learn new things, and taking informed risks, and the pandemic only accentuated those characteristics as a leader. Your ability to adjust to unplanned events, and your capacity to handle different demands has only been magnified through this. But one thing I’ve noticed is the need as a leader to simplify things down, whether that’s with your stakeholders and customers who are leveraging your services, or, most importantly, with your staff. Simplifying it down to them about what we do empowers our business. We’re fortunate to be challenged by our clients to solve complex problems, and running an institution like Booz Allen’s IT and cybersecurity is an amazing mission. So if I can simplify things down for our set of leaders, and then empower them in a culture of accountability, it makes you feel you’re part of a greater good. That’s a big reason why a lot of people join the company as it provides a calling to do something for the nation, community, and the globe. By leading that way and maintaining that agility and capacity, but simplifying down, it can be inspiring to our all our employees.

On innovating the IT culture: In the role before this at Booz Allen, I was in the Innovation Group, leading a lot of our enterprise cybersecurity and IT innovation, so I knew what products and services we had. So one of the first things I did as CIO was make ourselves what we call client zero. We leverage out solutions internally, like with a next-generation data lake that allows us to make data-driven decisions and not just go by the intuition that dominates large corporate cultures. In the nature of professional services, we constantly spin up and spin down new environments, consuming new data for our AI experts to solve, from healthcare missions to NAV security missions. They need an agile set of infrastructure that is able to support that, so we’re able to adopt that ourselves internally as client zero. It saves money and gives a feedback loop where we can rotate staff between our client delivery side and our internal business. I’m proof of that myself as somebody who spent many years doing client delivery, and now I’m enjoying a corporate role.

CIO, Innovation, IT Leadership

Listening to customers is a strategy that often sounds good on paper but is soon overshadowed by other areas of business or trends. Hyland, however, remains laser-focused on making sure customer success is the key to product improvements and a core component of the company’s culture. We spoke with Drew Chapin, CMO at Hyland, to learn more.

How would you describe Hyland in six words or less? How does Hyland help customers create a better experience for end users?

Hyland helps customers deliver better experiences. We do it by automating manual and complicated processes, which allows people to focus on their purpose rather than a manual task or process.

Customer expectations have changed with the convenience of things like Amazon where they do amazing things at the click of a button, and now expect that same experience from their work technology. Hyland strives to take many of the manual and complicated tasks off their plates so that physicians can treat patients better, educators can teach students better and insurance agents can process claims better.

What sets Hyland apart from other players in the industry?

There is confidence that we’ve earned from 30 years in this space, and our ability to deliver consistently. What also differentiates us is the breadth of product features, flexibility and the ability to configure our solutions. We give our buyers options, such as low- and no-code options, open-source through our Alfresco platform and innovative solutions, like our digital asset management offerings through Nuxeo.

We have a customer- and employee-centric culture, with which we have been able to attract and retain a very talented and deeply experienced workforce. We learned a long time ago that happy and engaged employees deliver amazing experiences to customers, and believe that investing in our employees will deliver value to our customers in a meaningful way.

Tell us about the X factor and Hyland’s partnership with Xander Schauffele.

We started our partnership in 2019. We view X factors as the things – sometimes they’re big, sometimes they’re small – that give you an edge over the competition to help you win.

The story for Xander is that he’s looking at all aspects of his game – driving, tee-to-green, bunker work and putting – to get any little edge he can earn to help him win. Our customers are doing the same thing. They’re looking at business processes and trying to optimize those to better serve their customers.

To learn more, visit Hyland.

IT Leadership

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

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

By Milan Shetti, CEO Rocket Software

As a leader, setting the culture of an organization is a massive undertaking, especially if the task is to change the culture at a company that has been around for decades. How a culture is implemented in an organization oftentimes comes down to the idea of the company having a “fixed mindset” or a “growth mindset” – one will help the company get ahead, while the other can create a hostile, stagnant organization that falls behind the competition.

As the name would imply, a growth mindset leads to a better work environment and a better work product than a fixed mindset brings. To have a growth mindset in business means that challenges are enjoyed, people stive to learn new things and employees see the immediate and long-term benefits of continuing to learn and develop new skills.  

Defining a growth mindset

The phrase “growth mindset” was coined by Carol Dweck, a psychology professor at Stanford, who spent several decades studying how people react to challenges they face. Dweck’s original quest was to study how students in a classroom learn and perform, but her research has shaped how business leaders think about training employees and the culture of their organization.

Simply put, someone with a growth mindset views intelligence, abilities, and talents as learnable and capable of improvement through effort. People who adopt a growth mindset are more likely to take risks, channel their skills to face new challenges, and are hungry to learn more. On the opposite side of the spectrum, someone with a fixed mindset views their traits as stable and unable to change over time.  

Leaders within an organization often set the culture of that organization. Business leaders that adopt a growth mindset, and encourage their employees to do the same, will foster innovation, growth, and collaboration in their business.

How a growth mindset propels businesses

There are countless reasons why a growth mindset is important for business. There are several iconic brands that have adopted a growth mindset, including Apple, Bloomberg, and General Electric, and are known as innovators in their space. A fixed mindset can hinder growth and stops innovation from flourishing – a major problem for companies looking to get ahead of the competition.

One of the world’s most well-known and successful companies, Microsoft, switched its culture to a growth mindset when CEO Satya Nadella took over in 2014. In his words, prior to this mindset shift, “Innovation was being replaced by bureaucracy. Teamwork was being replaced by internal politics. We were falling behind.” Once Microsoft consciously started examining its work culture and implementing the attitudes of a growth mindset, including valuing innovation even if there’s failure along the way, the company truly transformed. As one employee put it, “The culture at Microsoft changed from ‘know-it-all’ to ‘learn-it-all’.” This ultimately helped Microsoft continue to lead in the technology space.

A growth mindset dramatically improves a company culture, but it must be practiced by senior leadership before junior employees will feel comfortable taking on the same mindset.

Educating employees on the growth mindset

According to one study, employees that are in a company that values a growth mindset are 47% likelier to say their colleagues are trustworthy, 65% likelier to say that the company supports risk taking and 49% likelier to say that the company fosters innovation.To sum it up, employees value working at a company that fosters a growth mindset.

Companies that encourage a growth mindset must communicate what that mindset entails clearly with employees, so they know it’s okay to take risks, try new things, and potentially fail. According to the NeuroLeadership Institute’s Idea Report, “Growth Mindset Culture,” support from top leadership is critical for success in an organization. Sixty-nine percent of organizations used top leaders to communicate, teach, and role model growth mindset throughout the company.

Instilling a growth mindset into company culture is a worthy cause for organizations looking to continue to innovate and stay ahead of their competition. When top leaders within a company embrace a growth mindset, the entire organization will follow suit.

To learn more about Rocket’s culture and growth mindset, visit the careers page on our website.   

IT Leadership

Data is the lifeforce of modern business: It accelerates revenue, fuels innovation, and enhances customer experiences that drive small and mid-size businesses forward, faster. Yet while data-driven modernization is a top priority, achieving it requires confronting a host of data storage challenges that slow you down: management complexity and silos, specialized tools, constant firefighting, complex procurement, and flat or declining IT budgets.

To truly modernize today, you need more than a faster and more powerful box. You need to break away from legacy infrastructure and elevate your storage experience with a platform that simplifies and automates everything, ensures apps are always on and always fast, and unlocks agility by delivering the cloud experience everywhere.

Sound intimidating? When your next mid-range storage refresh rolls around, here are five key strategies to successful modernization:

1. Go faster with a cloud experience everywhere

Public cloud has set the standard for agility with a cloud operational model that enables line of business (LOB) owners and developers to build and deploy new applications, services, and projects faster than ever before. Now, extending that idea further, small- and mid-sized organizations are racing to bring the benefits of the cloud operational experience to wherever their apps and data live, from edge to on-prem to colo.

Simplifying operations and moving faster with a cloud experience everywhere is critical to organizations: According to ESG, 91% of IT leaders identify mature cloud operations on-premises as the single most important step to eliminating complexity. The same survey reported that more than 4 in 5 IT leaders are under pressure to deliver more cloud experiences to end users, which is a challenge when up to 70% of enterprise apps and data remain on-prem due to data gravity, latency, application dependency, and compliance requirements.

Simplifying and automating on-prem storage with the self-service agility of a cloud operational experience changes the mid-range storage game entirely. Leveraging AIOps, a cloud-managed, on-prem mid-range storage platform makes underlying data infrastructure invisible — eliminating silos, complexity, and the burden of day-to-day storage administration while shifting operations from an infrastructure-focused to an app-focused model. Unlike traditional storage management, a cloud operational experience delivers the self-service storage provisioning agility that your LOB owners and developers need to accelerate app deployment while also freeing IT resources to work on strategic, higher-value initiatives.

2. Put storage on autopilot with an AI-managed service

A true cloud operational experience should be powered by the data-driven insights and intelligence provided by advanced AI for infrastructure. Why is that important? Because AI-powered autonomous operations ensure apps are always on and always fast — which means your organization can say goodbye to endless firefighting.

With an AI-managed service, you can predict and prevent disruptions before they occur across the stack, pinpoint issues between storage and VMs, and identify underutilized virtual resources. Your admins can rely on AI-driven recommendations to take the guesswork out of managing data infrastructure, and you eliminate time-consuming escalations through predictive support automation and direct access to experts.

3. Get optimum price performance for general-purpose workloads

As small- and mid-range organizations continue to experience flat or declining IT budgets, hybrid storage solutions have become increasingly efficient at delivering the performance companies need for their mix of primary workload, secondary backup, and disaster recovery workloads while helping to contain the cost of rapidly growing data volumes. Hybrid storage solutions balance performance and cost by storing active and frequently accessed data on flash storage while storing inactive or less important data on more affordable media.

The most advanced hybrid arrays combine flash performance with disk economics. They feature ultra-efficient architectures designed from the ground up to deliver fast, consistent performance and industry-leading data efficiency. Look for a hybrid storage solution that accelerates your apps with sub-millisecond latency, writes to cost-optimized disk at flash speeds via write serialization, and offers dynamic flash caching to speed your reads even as workloads change in real time.

Modern hybrid flash arrays can also help you increase storage efficiency while lowering costs and footprint. They do this with advanced, always-on data reduction — encompassing deduplication, compression, zero-pattern elimination, thin provisioning, and thin clones — which can deliver up to 5x the space savings without performance penalty.

4. Depend on a resilient, proven platform

Mid-size organizations increasingly rely on applications to handle everything from back-end operations to the delivery of products and services. That’s why proven availability, protecting data, and ensuring applications stay up are more important than ever before.

Advanced, AI-driven arrays eliminate the anxiety and disruption of unexpected downtime by guaranteeing resilient six-nines data availability based on real, achieved values (as opposed to theoretical projections) and measured across an entire installed base. Paired with advanced AI for infrastructure that predicts and prevents problems, your arrays should get smarter, better, and more reliable every day.

Don’t accept trade-offs between data resilience and performance. Your mid-range storage array should deliver Triple+ Parity RAID as standard, with zero performance impact. Triple+ Parity RAID can sustain three simultaneous drive failures without data loss and provides additional protection through intra-drive parity.

Ensure your recovery SLAs with fast, simple, and integrated app-aware backup and recovery — on premises and in the cloud. Natively replicate from all-flash arrays to hybrid arrays and leverage a SaaS-based backup and recovery service to simplify hybrid cloud data protection with instant restores, rapid recovery on premises and cost-effective, long-term retention in the cloud.

5. Consume as a service, on demand

Finally, you should be able to choose how to consume your mid-range storage array with either Capex or pay-per-use options. A flexible as-a-service consumption model enables you to avoid over- and under-provisioning concerns, Capex budget constraints, and complex procurement cycles.

How so? First, by easily getting the storage resources needed with workload-optimized storage tiers delivered in days. Second, by scaling on-demand and as necessary, with buffer capacity for unexpected workloads or usage demands. And third, by moving from heavy up-front costs to transparent, predictable monthly payments based on actual metered consumption — with complete visibility into your storage utilization at any time.

It’s time to rethink mid-range storage

Taken together, these five strategies point to a mid-range primary storage solution that makes it easy to focus on data-driven modernization and accelerating innovation — without having to deal with legacy storage headaches, disruptions, or high costs.

At HPE, we’re delivering exactly that: simple, reliable, and cost-efficient hybrid storage, adaptively designed for both general purpose and secondary workloads. Built from the DNA of the HPE Nimble Storage Adaptive Flash array, HPE Alletra 5000 brings the cloud experience to your on-premises storage and simplifies operations across the lifecycle, from deployment to provisioning to upgrades.

HPE Alletra 5000 speeds time to value by delivering 99% operational time savings via intent-based provisioning, which enables line of business and database admins to self-provision storage for faster app deployments. It also eliminates app disruptions and firefighting thanks to HPE InfoSight, the industry’s most advanced AIOps for infrastructure. You get absolute resiliency with guaranteed six-nines data availability, Triple+ Parity RAID, and simple hybrid cloud data protection — and optimal flash price performance for your general-purpose workloads with a unique, ultra-efficient architecture. Even better, you can consume HPE Alletra 5000 as a service via HPE GreenLake, enabling you to shift from owning and maintaining data infrastructure to simply accessing and utilizing it.

If your next storage refresh doesn’t offer capabilities like these, it’s time to rethink your mid-range storage and aim for true data-driven modernization.

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About Simon Watkins

Simon Watkins is a Worldwide Senior Product Marketing Manager with HPE Storage. The 20-year veteran of the storage industry started his career in data protection, and spent the last few years working in primary storage, most recently helping drive the transformation of the HPE Storage business from a hardware vendor to a cloud data services provider.  He holds an Executive MBA from the London Business School as well as a Bachelor of Arts Degree from Cambridge University in the UK.

Data Management, HPE, IT Leadership