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Tag: CIO

  • Hybrid Infrastructure Is a Mess—But It Doesn’t Have to Be

    Hybrid Infrastructure Is a Mess—But It Doesn’t Have to Be

    If you’re a CIO who is managing hybrid infrastructure, you’re like the peace-keeper in a dysfunctional family. On one side, you’ve got the old-school on-prem team—practical, cost-conscious, maybe a little stubborn. On the other hand, the cloud team is fast-moving, quickly adopting the latest tools, and sometimes a little dismissive of “legacy” infrastructure. And just like a family that doesn’t get along, they barely talk to each other.

    I see this all the time. A CIO will tell me, “I need to unify my infrastructure strategy,” but when I speak with their teams, it’s like talking to two different companies. The cloud engineers don’t know (or care) what the on-prem team does, and the on-prem team sees the cloud people as reckless spenders who don’t understand “real” infrastructure.

    Hybrid Isn’t Going Away—So We’d Better Get It Right

    The thing is, both sides have a point. On-prem infrastructure is more predictable in cost, often more secure, and sometimes just makes sense for certain workloads. And the flexibility and scalability of cloud infrastructure are real.

    This means hybrid is the future. But right now, it’s a future filled with inefficiency, wasted budgets and unnecessary complexity.

    The Reality: Two Worlds That Don’t Talk

    Here’s a real example. I was on a call with a large financial institution, and the goal was to show how to manage both on-prem resources with Ansible and cloud infrastructure with Terraform. But the on-prem person didn’t show up for some reason. It was a wasted meeting because the cloud team hadn’t a clue what the on-prem team did, so talk of cohesion between the two siloed departments was impossible.

    A week earlier, I had spoken to their CTO, who was practically begging for a solution to bring these teams together. His teams were using completely separate toolchains, paying over $1 million annually for tools that didn’t even integrate. He had no visibility, no way to make informed decisions, and worst of all, no real collaboration between his teams.

    This is very bad for business. It prevents the company from scaling, optimizing costs, and, most importantly, moving fast without breaking things.

    Hybrid Is the Future, Whether We Like It or Not

    In my opinion, hybrid is here to stay. Some workloads will always belong on-prem due to security, compliance or cost reasons. Others will thrive in the cloud, where elasticity and managed services make life easier. The problem is most organizations haven’t figured out how to make this coexistence work smoothly.

    Right now, hybrid infrastructure feels like owning two cars but having no idea which one to use on any given day. Imagine having to change the tires, handle maintenance, and refuel separately for each—without even knowing how often you’re driving them. That’s what most CIOs are dealing with when it comes to managing a mix of cloud and on-prem workloads. Without unified visibility, decisions get made in silos, costs spiral out of control and teams get stuck in an endless cycle of firefighting instead of innovating.

    Infrastructure as Code Orchestration: The Bridge We Need

    This is where infrastructure-as-code (IaC) orchestration comes in. If hybrid infrastructure is inherently complex, then the answer isn’t just automation—it’s orchestration.

    Automation alone won’t fix the fragmentation. You can automate tasks all day long, but if each team automates in its own way with different tools, you’re just adding complexity at scale. Orchestration, on the other hand, introduces a single layer of control—one set of workflows that unifies deployment and ongoing operational management across on-prem and cloud infrastructure.

    Here’s what this actually means in practice:

    ● Visibility – Instead of scattered tools and isolated teams, you get a single source of truth for your infrastructure.

    ● Efficiency – No more redundant work. Instead of two teams doing similar things in totally different ways, orchestration allows for shared workflows.

    ● Security & Compliance – Unified policy enforcement across all environments. No more guesswork or inconsistent controls.

    ● Developer Velocity Without Losing Control – The ability to move fast while ensuring infrastructure changes are auditable, reversible and compliant.

    I’ve seen companies try to duct-tape their way around this problem. They build custom pipelines with Jenkins or GitHub Actions, but eventually, they hit a wall. One company (who I can’t name, but let’s just say they handle a lot of digital documents) tried to do this with GitHub Actions, relying on one engineer to make it work. His salary alone cost them more than an orchestration platform, and if he left, they’d be completely stuck. That’s not a strategy—it’s a liability.

    The CIO’s Next Move

    If you’re a CIO dealing with hybrid headaches, here’s what you should be asking yourself:

    1. Do I actually have visibility into both my on-prem and cloud environments? (If the answer is no, that’s problem #1.)

    2. Are my teams working together, or are they operating as separate entities?

    3. How much are we spending on redundant tools that don’t integrate?

    4. What’s slowing down our infrastructure deployments, and is it avoidable?

    The companies that solve this problem first are the ones that will be best positioned for the future. They’ll move faster, spend smarter and avoid the kind of growing pains that turn into existential crises.

    If any of those questions made you uncomfortable, it’s time to rethink your approach. Hybrid doesn’t have to be a battleground. With the right orchestration, it can actually be an advantage

  • Why Your Next CIO Will Be a CPO

    Why Your Next CIO Will Be a CPO

    Here’s what the transition to CPO means for everyone in IT

    Over the last 20 or so years, the evolving role of the CIO, or chief information officer, has been a hot topic of conversation in most large enterprises. It’s a topic that doesn’t just affect those breathing the rarefied air of the C-suite but has concrete implications for everyone in the IT organizations these CIOs lead.

    For these last two decades, most larger companies in traditional industries have vacillated between periods of enthusiasm for technology and so-called “digital transformation”—in which CIOs are viewed as wizards bringing new wonders, changing their entire business models and growth trajectories for the better—and periods of disillusionment, with late projects, missed requirements, user and customer dissatisfaction and cost overruns—in which the CIOs become scapegoats. In these latter times, they often are replaced by CIOs of a different stripe, often moved laterally from finance or general management roles and charged with cost-cutting and predictability as top priorities. Even if the existing CIO keeps their job, they’re often pushed to change the way they operate and lead. When this happens, the entire IT organization finds it needs to change its pitch and priorities to sustain funding for every project and every function, resulting in whiplash. That itself contributes to the perception, and often reality, of late and unfinished projects and unpredictable IT outcomes. It is usually at that point someone realizes the newly efficiency-focused organization is losing market share, brand perception or customers to competitors that are more technically innovative (often digital-first upstarts challenging incumbents in a given industry), and the organization pivots back to “techthusiasm” and a different kind of CIO again. And more whiplash. And so it goes.

    During the periods of techthusiasm, some organizations replace or supplement the CIO title with newly coined titles such as CDO (chief digital officer), CAO (chief analytics officer, an uncomfortable namespace collision with the established corporate title of chief accounting officer), or chief experience officer (no one dares make that into a redundant CEO three-letter acronym).

    In the disillusioned periods, the CIOs stay CIOs as long as they can hang onto their jobs. Title creativity is as suspect as any other kind of creativity.

    Meanwhile the vicious cycle continues: techthusiam -> disillusionment -> retrenchment -> falling behind -> renewed techthusiam.

    As a longtime CPO (chief product officer) for enterprise software companies whose customers predominantly have been these seesawing IT organizations, I’ve been seeing of late the start of a powerful conceptual shift that is the escape route from this vicious cycle.

    So what’s the magic shift in thinking?

    If you’re in a traditional business in which the technology your IT organization delivers merely facilitates people doing their jobs and interfacing with each other and customers, your primary threat in the 2020s—especially with a pandemic interrupting face-to-face interactions—is digital-first, new entrants that conceive of their product as the software and the people as the behind-the-scenes back office and failover when the software doesn’t work. Every business is now a software business, and the software is now the product; some companies in a given industry just happen to be better software companies than others. Such digital-first entrants range from Amazon to Netflix to Workday to Sofi to Wealthfront.

    However, you don’t leap from being ADP to Workday simply through what so far has passed for “digital transformation” led by a CIO, CDO, CAO or whatever another newfangled c-level tech title, as a peer to product leaders whose organizations came from the pre-digital business and look to the CIO, CDO, CAO, etc., to simply execute the technology support.

    What do true software companies in traditional industries have in common? They have CPOs! (Chief product officers, not chief procurement officers or even chief pandemic officers.) Analytics and digital are not in their titles because these are assumed means at their disposal. (I’m thinking of taking on the excesses of our fetish for data in IT and software today in a future column. Send me thoughts if you have them.)

    The role of the CIO was to deploy technology efficiently to support the company’s strategies and plans. The role of the CPO, as inherited from pure technology companies, is to develop and maintain a deep understanding of the customer and market and guide the delivery of products to best meet and monetize their needs, and do so ahead of any and all competition. The traditional CIO derives the why and what from other parts of the organization and supplies the how. Transitional versions of the CIO and the CDO and other neologisms may start to encroach on the what. But the true CPO drives the why and what—and the how if they also have engineering, or collaborates on the how with a CTO or head of development if not. (My friend Kaj van de Loo has an excellent discussion of CPO vs CTO and the trend toward combining the roles here, implicitly focused on digital-first companies, here.)

    Does this sound broad, even encroaching on CEO territory? Well, yes. It’s no accident that former product chiefs are the new CEOs of Google and Microsoft.

    So what does that mean for you if you are in an IT organization?

    Well, first, while your organization may or may not change the actual title to CPO from CIO, it’s important for your career to recognize when the definition of their job becomes that of what a CPO would do in a “pure” software company. If you see the signs that the CPO is guiding the IT organization to become the experts on the market and customers and invent new digital-first products, that shift is underway. It’s good news for those in IT because it means you no longer are simply a cost center to be minimized and even offshored but a driver of the business and value.

    Once you realize you are now in a product organization and not an IT organization, you need to start thinking about what a (software) product actually is and how that differs from what IT delivered before.

    IT traditionally operates on a project and service maintenance basis. Projects have a defined scope and concrete, finite objectives to be considered complete. They have beginnings and ends. Projects either result in the existence of a service that is operated and maintained on an ongoing basis or deliver a discrete set of changes to a service that already existed. Project teams form, deliver the project, and then break up and are reassigned to the next project. Much smaller maintenance teams (usually as low-cost and low-skill as the organization can get away with) make sure that the resulting services stay alive and maintain agreed service levels and consistent, fixed functionality (until the next project to evolve the service is funded).

    True products are quite different. Products have many yearslong life cycles, from inception through launch, constant active enhancements and growth and then eventual end of life. During these life cycles, customers reasonably expect new capabilities to increase and existing capabilities to evolve for better usability and effectiveness.

    Products are not defined by a particular architecture or features but their mission on behalf of the market, users and customers. During a product’s life cycle, the product team may discover new feature ideas or develop new architectural implementations to replace or enhance old ones, all within the umbrella of the same product and mission.

    Product teams maintain staffing levels throughout a product’s life cycle to continue delivering new capabilities and technical enhancements, not just keep the lights on. Every member of a high-performing product team takes the team’s mission as its own and strives to build holistic knowledge of the mission and the product, and contribute new ideas and challenge existing ones—not just a defined role of a product manager or product owner or architect.

    Product teams are acutely aware of competitive and substitute products and strive to become and stay their target customer’s first choice in the face of competitive product teams doing the same. Product teams regard selling, evangelizing and making their products available to their market as being as much a part of delivery as software development and integration. Product teams see opportunities to interact with target users and customers as invaluable two-way dialogue during which they get to show and get reactions to the shiny features they’ve built, as well as discover latent needs that drive ideas for new features and maybe even entirely different conceptions of the overall product.

    In an IT organization that is transforming itself into a product organization, these ideas and this approach apply not just to teams working on “external” products for paying customers outside the organization but also in equal measure to internal products that either serve internal end users, such as a finance or payroll system, or become services that developers on other teams incorporate into their products or platforms on which other developers build, such as a common identity service, customer data pipeline or private cloud. In today’s world, every such official internal service resides in an environment with competitive third-party services and possibly competing internal approaches, and in which what was state of the art yesterday is not viable today.

    Conversely, a well-conceived, designed and managed internal product may turn out to be the basis of a massive external business. Witness AWS and countless DevOps startups that began with the old story, “We built this thing to support our social media/dating/gaming/whatever B2C startup and it turned out to be something other companies wanted to buy more than people wanted what our startup was doing.” Managing internal services and platforms as products is the way to both ensure that the original mission is fulfilled and new opportunities are discovered, too.

    I’ll come back to some of these themes in future columns, but for now, I’ll leave you with this link to a podcast featuring a small Brazilian fintech startup that I believe is one of the best recent examples of a true product team’s approach: Their level of customer intimacy enabled them to identify a new product that solved problems within the scope of their mission and on behalf of their target users that a lesser product team would not have done. How would this kind of product thinking apply to the products in your IT organization?

    Until next time,

    Christina

  • Open Source: What IT Pros Wish the CIO Knew

    Open Source: What IT Pros Wish the CIO Knew

    Using DataOps and open source together, organizations can reimagine the way they deliver data and software-driven projects

    Real-time data is the fuel that powers today’s most critical systems and applications, as well as the digital transformation initiatives organizations need to compete effectively. For the people on the front lines building them, having the right technology alone is not always enough to succeed. To make the most of these game-changing technologies, you also need the right tools and the right strategy in place.

    If you’re not maximizing use of real-time data, you’re at risk of being disrupted by a competitor. For this reason, C-level leaders often adopt cutting-edge open source technologies that come with risks, making real-time data applications complex to build, deploy, operate and govern, and require a major investment in time and resources upfront to unlock their potential. You won’t get the most out of open source unless they can be operated and data can be accessed by a wider range of people outside engineering.

    For example, open source data technology is often lacking, and documentation is sometimes sparse at best. You may need to ask your data and platform engineers to spend weeks or even months building custom management tools before you can get to work on your first streaming application. That kind of delay can seriously impact your time to market.

    How Secure is Your Solution?

    Streaming data projects with multiple open source components can also introduce security and compliance issues into the picture. Even if you’re working with the very latest technology, open source often lacks built-in capabilities for security and compliance—especially if they are industry-specific for use cases such as health care or financial services. In fact, a recent survey by Veracode found that 70% of applications have open source security flaws, and 47% of those flawed libraries end up in code indirectly. If your project suffers from increased risk due to security and compliance issues, it can also lead to additional delays in projects, further slowing your time to market.

    In a world where the threat landscape is constantly evolving, your organization may wish to opt for a commercial offering for some types of use cases, especially if it includes the features you need to align with very specific compliance and governance needs.

    Creating a Culture of Engagement

    Arming IT professionals with the right tools and technologies they need is essential, but organizations also need to be sure they have a strategy in place to retain the best people—and keep them productive and satisfied. Fostering a workplace with the right level of engagement can provide a strong start. A recent Forbes article cited studies finding that highly engaged employees result in 21% greater profitability. On the other hand, the same article reported that 67% of employees reported feeling burned out at work—and were 2.6 times as likely to be looking for a different job.

    Open source tools are a great way to attract talented engineers because people love working with the latest technology. But as you give your IT professionals access to bleeding-edge capabilities, the complexities and time spent working with them increase. The right tooling can help manage the shortcomings of these technologies and help retain the talent you need by encouraging a positive work-life balance and lead to more successful implementations. If your engineering team isn’t spending time fighting fires and consumed by open source technology, there’s more time to focus on bigger picture issues such as a well-defined career path that keeps team members engaged and more valuable to the business in achieving its goals. With the right level of work-life balance and keeping employees involved and satisfied on the job, you can be more confident that your best engineers will become more than technologists and are strategic business partners who won’t be spending their spare time dusting off their resumes.

    Getting the Best of Commercial and Open Source

    How can you enable IT professionals with the tools they need to deliver their projects on time and on budget while empowering them with a more strategic role? Employing a DataOps approach to your initiatives can provide a strong start. Spanning many disciplines and skills across the organization, DataOps encourages an environment where people can collaborate, reduce process complexity and fully optimize the use of their data. DataOps allows teams outside of IT and engineering to operate their data directly, without being dependent on a small engineering team. It enables business stakeholders in your workforce to get closer to data and bring their own knowledge and context to data initiatives and improve business outcomes.

    For example, leading social and mobile gaming company Playtika needed to provide better visibility data streaming across Apache Kafka, its primary platform for the exchange of information between its microservices. Using a DataOps approach and platform, the company provided its analysts, product owners, operations and developers access to a fully audited GUI and CLI to explore and operate data in a compliant way without relying on data or infrastructure engineering. Providing direct access to data enables 600 developers to save 30 minutes a day as they work on delivering new features—which led to faster and more innovation when it came to developing new games.

    When utilized together with a commercial solution based on open source roots, DataOps helps you get your business and technical people on the same page, so your organization can achieve closer alignment to strategic business objectives, with data serving the business. At the same time, you can free up technical staff and developers from tasks such as tooling, and enable them to utilize open source for R&D and other innovative priorities.

    Using a collaborative DataOps strategy, your organization can reimagine the way it delivers data and software-driven projects, while also embracing new open source technologies.

  • Coronavirus Economic Shutdown: Analysts Hit the Brakes on Global IT Spending Estimates

    Coronavirus Economic Shutdown: Analysts Hit the Brakes on Global IT Spending Estimates

    By most accounts, 2020 was set to be a pretty good year for U.S. gross domestic product and enterprise IT budgets. That was before the novel coronavirus, and the subsequent economic shutdown that is designed to blunt its spread and avoid overwhelming the nation’s health system. Analysts are now slashing their economic growth rates and enterprise technology spending estimates.

    Previously, research firm IDC estimated that real GDP in the U.S. would reach 2.4%, but downshifted that to a “pessimistic scenario” of 1.4%. While IT spending dropped from an expected 5.1% year over year growth to a pessimistic scenario of 1.3%. The base scenario for GDP growth is now 2.0% and for IT spending 4.3%.

    “The pessimistic scenario is not a worst-case scenario,” said Stephen Minton, vice president in IDC’s Customer Insights & Analysis group. “Things are moving so quickly that we need to constantly recalibrate our assumptions and expectations, but the pessimistic scenario reflects an IT market in which weaker economic growth translates into weaker business and consumer spending across all technologies over the next few quarters. Things could get worse, but hopefully not.”

    Earlier this month, Forrester analyst Andrew Bartels wrote in this post that the U.S. and global technology market spend will slow to 2% this year.

    “That assumes the U.S. and other major economies have declined in the first half of 2020 but manage to recover in the second half. There is also a 50% probability that U.S. and global tech markets will decline by 2% or more in 2020 if a full-fledged recession hits,” Bartels wrote.

    Not all areas in technology will be impacted equally. Forrester expects there will increased demand for cloud infrastructure services, specialized software, communications equipment and telecom services for remote work and education.

    However, Forrester expects computer and communications equipment to potentially decline 5% to 10%, while technology consulting and systems integration services spending could be flat to down 5%, should companies really belt-tighten.

    “Software spending growth will slow to the 2% to 4% range in the best case and will post no growth in the worst case of a recession. Tech outsourcing and telecom services will hold up better, though contract revisions could cause spending to go down, as well,” stated Bartels.

    S&P Global Ratings also predicts slowing IT spend. According to its update, Global IT Spending Set To Slide As Coronavirus Hits Hardware Sales, S&P Global economists cut their global GDP growth rate by more than half to 1% to 1.5% from 2.8%—in just two weeks.

    “We believe the spread of the coronavirus will hurt enterprise and consumer IT spending across the globe with particularly bleak ramifications for the hardware and semiconductor segments. However, we expect some of the deferred spending to return gradually in the latter half of this year through heavy government stimulus in the U.S., China, and elsewhere,” wrote S&P Global Rating Analyst Andrew Chang.

    S&P Global Ratings anticipates IT spending to decline 3% year over year, compared their prior estimate of 2% to 3% growth. S&P Global Ratings expects some of the biggest hits to hardware, with smartphone revenue falling to negative 9% from up to 2% growth, and PCs to negative 9% from a previous range of negative 3% to a positive 4% growth.

    While enterprise technology budgets are being slashed, the need for business-technology isn’t going away. In fact, it’s accelerating as more knowledge workers shift to working from home, more remote collaboration and keeping legacy systems running and moving forward with digital transformation efforts.

    — George V. Hulme

  • 7 Big Digital Transformation Trends

    7 Big Digital Transformation Trends

    As enterprises continue their rush to digitally transform their organizations, they’re investing big in retooling their software development pipelines, new artificial intelligence (AI) and robotic process automation (RPA) technologies and low-code development platforms, as well as putting considerable money into customer engagement software. Yet, the extent of success following these investments remains unclear and varies significantly from industry to industry.

    To shine a light on the digital transformation efforts currently underway, as well as the degree of their success, we’ve collected a number of fascinating trends in the most essential areas of digital transformation.

    Investment in AI, Machine Learning and RPA Technologies Hitting an Inflection Point

    According to the consultancy KMPG, enterprise investments in AI, machine learning, and RPA will rise to $232 billion by 2025 from $12.4 billion in 2018. “Nearly two-thirds of respondents indicate plans to fully implement RPA within three years. Another 18% plan selective use. As for cognitive automation, nearly half noted intentions to use these approaches at scale within 3 years, while 29% indicated selective reliance on cognitive automation capabilities. Some 10% said they would launch pilots and proof of concept projects,” according to the report.

    DevOps is Just Getting Started

    While we’ve been writing about the enterprise move to DevOps for years now, the investment in DevOps is just setting itself up to truly soar. According to the market research firm Market and Markets, the DevOps market will grow 24.7% annually, to $10.3 billion by 2023 from $2.9 billion in 2017. “The demand for DevOps solutions and services among enterprises is expected to gain huge traction, due to the increasing need for fast application delivery with high quality,” the firm said.

    Digital Transformation Spending to Top $1 Trillion This Year

    In research firm IDC’s “Worldwide Semiannual Digital Transformation Spending Guide,” global digital transformation spending will reach $1.18 trillion this year, rising nearing 18% from 2018. “Worldwide DX technology investments are expected to total more than $6 trillion over the next four years,” said Eileen Smith, program vice president with IDC’s Customer Insights and Analysis group.

    For 2019, the two industries expected to invest the most into digital transformation are discrete manufacturing and process manufacturing, which will invest roughly $222 billion and $124 billion, respectively. According to IDC, the top digital transformation spending will be in smart manufacturing, which will be supported by autonomic operations, manufacturing operations and quality. The retail, transportation and professional services industries will follow closely behind.

    IT and Business Leadership Chasm Widen

    According to research firm consultancy Capgemini, there appears to be a growing disconnect between the CIO and senior business executives. Capgemini’s research found that while in 2012, 65% of organizations believed that the CIO and senior business executives possessed a shared understanding of the role of IT in their organization. In their most recent survey, that figure dropped to 37%. Additionally, Capgemini found, 59% of enterprise respondents in 2012 believed that the CIO and senior business executives had a shared understanding of how IT could be used to increase organizational productivity. That figure also declined precipitously, hitting 35% in 2018.

    Low-Code Development Continues to Gain Higher Ground

    The demand for enterprise software seems to have no bottom. And no matter how hard they try, developers can’t code software quickly enough. This is why more enterprise software needs are being met by low-code development platforms.

    According to research from ResearchandMarkets.com, the global low-code development platform market will grow to about $27 billion by 2022, up from $4 billion in 2017 and at an annual compound growth rate of 44%.

    Digital Transformation, Customer Engagement Software Grow

    Digital transformations don’t mean much if they don’t reap increased revenue, land new customers and improve relationships with existing customers. And how enterprises engage with their customers is one of the most rapidly evolving aspects of enterprise technology today, from AI and machine learning to IoT devices and ubiquitous adoption of mobile devices. Customer engagement software ranges from staid CRM systems to customer self-service software. This class of software was a nearly $13 billion market in 2017, but will likely reach $22 billion by 2023, an annual growth rate just shy of 10%, according to market research firm Mordor Intelligence.

    Digital Transformation Success Grows Harder to Come By

    The success rate for digital transformation efforts is persistently, and dismally, low. According to research from McKinsey and Company, over time fewer than 30% of digital transformations succeed.

    And that failure rate appears to be growing worse, not better. McKinsey’s 2018 survey results show only 16% of enterprises believe their digital transformations will improve organizational performance over the long term. “Even digitally savvy industries, such as high tech, media and telecom, are struggling. Among these industries, the success rate does not exceed 26%. But in more traditional industries, such as oil and gas, automotive, infrastructure and pharmaceuticals, digital transformations are even more challenging: success rates fall between 4% and 11%,” McKinsey found.

    While enterprises are clearly investing into their digital transformation efforts and the desire to succeed is high, the high digital transformation failure rate says enterprises either aren’t taking the right approach to these efforts or they are not executing properly.

    Whatever the reasons for the high rate of failure, with the vast amount of business capital on the line and the increasing risks upstart businesses pose to those established in their markets, more enterprises better figure out soon how to get their transformation efforts right.

    — George V. Hulme

  • Digital Transformation: Digitally Resilient Organizations

    Digital Transformation: Digitally Resilient Organizations

    While some are growing weary of the term “digital transformation,” the reality is, it’s here to stay. Digital transformation isn’t just a buzzword or a transient phenomenon. Enterprises are digitizing themselves as rapidly as they can and automating what can be automated, improving customer experiences, leveraging data for machine learning and improving customer experiences.

    These levels of transformation are underway across vertical industries—manufacturing, retail, transportation, health care, telecommunications and government. Research firm IDC, expects worldwide spending on digital transformation products and services to reach $1.8 trillion in 2019, a rise of 18% from 2018. IDC expects that figure to rise to more than $6 trillion over the next four years.

    “Strong DX technology investment growth is forecast across all sectors, ranging between 15% and 20%, with the financial sector forecast to be the fastest with a compound annual growth rate (CAGR) of 20.4% between 2017 and 2022,” said Eileen Smith, program vice president with IDC’s Customer Insights and Analysis group.

    The two industries that will invest the most, according to IDC, are expected to be discrete manufacturing, at $222 billion, and process manufacturing, at $125 billion. IDC said the top priority is smart manufacturing, supported by significant investments in autonomic operations, manufacturing operations and quality. Retail will follow closely behind, which in turn will be followed closely by transportation and professional services.

    As hard as it may be to believe, the four pillars of transformation—DevOps, cloud, AI and IoT—are still in the nascent stage of deployment. The most popular digital transformation use cases this year, according to IDC, will be freight management ($60 billion), autonomic operations ($54 billion), robotic manufacturing ($46 billion) and intelligent and predictive grid management for electricity, gas and water ($45 billion). Additional use cases that will see investments higher than $20 billion in 2019 include root cause, self-healing assets and automated maintenance, and quality and compliance.

    Those organizations that excel in their digital transformation efforts will find that they’ll reap tremendous benefits. However, excellence here isn’t about short-term wins or one-off projects. Excellence in digital transformations is about properly tooling the enterprise for digitization so that the organization is as productive as it can be, cost-efficient and technically agile enough to seize new business opportunities as they arise and successfully endure or even thrive through market, geopolitical or other adversity. It’s about building an iterative, generative, agile digital platform that positions the business for long-term success. This is digital resiliency.

    Most enterprises aren’t close; according to the 2018 Global CIO Survey from Deloitte, about 70% of the 1,400 executives they surveyed don’t even have a digital enterprise strategy.

    The digitally resilient enterprise has built a business-technology platform that is elastic and agile and can position itself correctly depending on current business demands; it’s reasonably secure from cyberattacks that threaten data. The digitally resilient organization is also continually learning from its data and making adjustments as markets, its workforce and its customers demand. The digitally resilient organization has eliminated the bulk of its technical debt, and it innovates, so competitors don’t disrupt it with a better idea, execution and understanding for what customers want.

    In the weeks and months ahead, I’ll be sharing more stories, case studies and insights on how organizations can build the digitally resilient organization that positions them for success over the long term.

    — George V. Hulme

  • 5 Practices That Will Help Drive Successful Robotic Process Automation Deployments

    5 Practices That Will Help Drive Successful Robotic Process Automation Deployments

    Enterprises have begun to invest considerably in robotic process automation (RPA) in recent years. RPA is one of the critical technologies that enterprises now are leveraging to automate their business processes to make their businesses more agile and efficient. When properly deployed and managed, RPAs can automate everything from mundane tasks (such as organizing files) to more significant functions, such as user provisioning to resources and more.

    While RPAs do promise to help businesses move more quickly and with more agility, a company’s RPA strategy needs to be executed effectively across the organization. In my recent discussions with CIOs and others implementing RPA, the following practices repeatedly were mentioned as essential to RPA success.

    Understand the Process Being Automated and How RPA Impacts Other Operations

    One of the most common mistakes made is not thoroughly understanding the process being automated and the potential implications of automating the process. An example would include a business process that is time-sensitive and automated, which throws off the workflow timing. It’s possible the automation moves things along too quickly.

    Another example would be not taking into consideration the nature of the data being accessed. If it’s regulated or sensitive data, there are security implications that must be managed. If the bot potentially will process sensitive or regulated information, the bot should be controlled appropriately. RPA technology is an IT function, and at the very least IT and security should be made aware of and potentially involved in the oversight of the bot. It’s much better to inform them and bring them in early than them finding out later about an army of bots managing and manipulating information.

    Consider Refining the Process Before Automating

    After the process being automated is understood, evaluate the process for potential optimization. Sometimes processes that have been underway in organizations for years are more than just inefficient; they’re actually antiquated. Look for ways the process can be made more effective; consult all stakeholders when necessary or warranted; and consider refining the process if possible. There’s no sense in automating an inefficient process.

    Document, Test and Catalog Your RPAs

    After the RPA is built, make sure to document its functionality and how its code works and examine its functionality. The RPA is now ready to be used. It’s important to continually monitor the RPA for potential abuse or something gone wonky. Send all the documentation relating to the bot to the IT department.

    As the Bot Owner, Know You’re Responsible for Your Bot

    Should the bot do something unexpected or unwanted, prepare to answer for it as the bot, or business process, owner. Make sure the bot is managing risk within its acceptable scope and that it’s not given too high a level of access. While you as process owner may have administrative rights to an application, does it make sense for those rights to be transferred to the bot? Perhaps it does, and perhaps it doesn’t. It’s a risk management call and will vary from situation to situation. Just be aware that, as the owner, you also own the risk.

    Remember Your Bot May Live Beyond Your Tenure

    In one, two or five years from now you may not be in your current job position. It’s essential that the bot is constructed for this eventuality. Beyond the proper documentation and cataloging of the bot mentioned previously, put into place the appropriate identity and entitlement management of the bot. Down the road, someone may want to enhance the bot with machine learning or AI capabilities. For when this happens, it’ll be essential to have the bot well-documented as well as its entitlements well-defined.

    Consider Centralizing the RPA Deployment Process

    While some enterprises have chosen to undergo organizationwide automation efforts, others are dipping their toes in tepidly with small RPA pilots. Others still haven’t decided on how to incorporate bots within their organization, so it’s happening organically and haphazardly as individuals and departments decide to make a go of it on their own.

    If an organization is large enough, it may make good sense to put into place an RPA center of excellence. It will provide a repository of policies and strategies for RPA deployment, help catalog bot capabilities and dependencies and help drive overall RPA efficiency as the organization becomes more and more automated.

    These bots are here to stay—in fact, they are going to grow in numbers. Technology research and advisory firm Gartner expects global spending for RPA to reach $2.4 billion in 2022, up from $680 million last year. That’s an increase of 57 percent annually. RPAs help drive efficiencies and remove mundane, low-risk tasks and workflows so that humans can focus on higher value and higher cognitive tasks.

    — George V. Hulme

  • Enlisting the C-Suite in Disaster Recovery Initiatives

    Enlisting the C-Suite in Disaster Recovery Initiatives

    When disasters make headlines, corporate executives often have knee-jerk reactions and call for business continuity solutions to be implemented immediately. However, when push comes to shove, those very same executives tend to put up roadblocks with concerns over budget, priorities, vulnerability assessments and security.

    Perhaps more concerning, according to a June 2015 Ponemon Institute report, there are “a large portion of companies who remain vulnerable as a result of lack of executive interest in preparing for worst-case scenarios.” This creates a precarious situation for DevOps professionals that understand the severity and breadth of threats that can trigger downtime—from human error to power outages, cyberattacks and natural disasters.

    To expedite disaster recovery initiatives, IT teams must enlist top executives that influence budgeting directly. This often calls for varied approaches that speak to specific executive concerns and issues.

    Understand Your Options: Disaster Recovery vs. Backup

    It’s very common for companies to confuse disaster recovery and backup solutions. Both are available via cloud, giving teams access to capabilities that were once only available to enterprises with huge IT footprints. When you approach any executive, it’s critical to understand various services and how they can work in tandem to deliver the most cost-effective protection.

    Backup ensures companies do not completely lose data because it is backed up with copies. While it is important to have copies of data, accessing and restoring backups can take some time. Therefore, for workloads with important but not extremely time-sensitive data, backup can be sufficient while satisfying budget restrictions. In the fast-paced DevOps world, backup usually falls short.

    On the other hand, cloud-based disaster recovery ensures minimal—if any—downtime. Applications can fail over and be up in running in seconds. Further, testing can be done at will without any impact on production environments. For workloads that demand continuity of service and aggressive recovery point objectives (RPOs), disaster recovery solutions are the better option and can also deliver cost efficiencies.

    For many operational and regulatory compliance reasons, companies may require a mix of both backup and disaster recovery. When evaluating service providers, check into how easy it is to apply backup and disaster recovery based on your development and application requirements. Take a close look at pricing models associated with each—including any support fees.

    CEO/COO – Chief Executive Officer and/or Chief Operations Officer

    While CEOs and COOs generally delegate detailed budget decisions to their teams, they are still ultimately responsible for overall company performance and reputation. Anything that threatens ongoing conduct of the business is their purview. Be prepared to discuss risks in real terms, and clarify that a “disaster” can be triggered by something as simple as human error.  They will care most about considerations such as:

    • Time to business resumption [e.g. near-zero recovery time objective (RTO)]
    • Capital investment via pay-as-you-go options
    • Ability to prioritize data and workloads, both for budgetary and business continuity purposes
    • Data loss estimates, in the case of a disaster
    • Testing flexibility, to ensure an operational, reliable solution
    • Independent validation from similar customers or analysts that a solution is reliable, proven and cost-effective

    CIO – Chief Information Officer

    Theoretically, this should be the easiest executive to convince because the CIO has a personal stake in recovery, but remember CIOs have a tough balancing act between controlling budgets and limiting exposure. The 6 Disaster Recovery Doppelgangers quiz and e-book can help CIOs approach their disaster recovery challenges across the organization. CIOs generally focus on:

    • Ability to see and manage the recovery process
    • Scalability of resources with on-demand access, often honing in on flexible terms
    • Security and compliance capabilities and support
    • Testing at will to ensure solution performs despite configuration changes to the day-to-day operational environment

    CFO – Chief Financial Officer

    Everything boils down to financials for CFOs, so they should be approached from a fiscal angle that demonstrates value backed by metrics. Be prepared with unbiased, independent information that appeals to their risk averse nature. What other financial benefits might come from leveraging cloud-based disaster recovery? For example, in some cases DevOps teams are beginning to use the failover cloud as a load testing environment that would otherwise require significant on-premise investments. Disaster recovery-as-a-service (DRaaS) environments with advanced security can also be used to check for possible vulnerabilities to cyberthreats.

    CFOs often care about:

    • Flexible pricing options that can be tailored at a granular level based on services required
    • Pay-as-you-go pricing models that avoid upfront capital investment
    • Geographic constraints on their data, particularly if backups or failovers need to be maintained in a specific location due to jurisdiction requirements
    • Extended DR use cases that could offset other costs like security testing and quality assurance

    CMO – Chief Marketing Officer

    On top of branding, advertising and public relations responsibilities, CMOs have key objectives that pertain to customer loyalty and overall corporate reputation. They may not be interested in the details of services, but can be a powerful advocate that can speak to the need for business continuity solutions that will protect brand image, reinforce messages about your technology innovation and maintain excellent customer support. Familiarize yourself with real-world stories that demonstrate how media—both traditional and social—cover outages and their negative impact to business. One need not look further than the recent Delta and Southwest outages.

    The concept of DevOps is about culture as much as it is about technology, and communication and collaboration are key. By understanding the needs and responsibilities of all stakeholders involved, teams can cut through politics, efficiently protect business and begin to leverage cloud-based DR technologies for initiatives far beyond recovery, alone.

    About the Author / Lilac Schoenbeck

    iLand Head Shots 4/22/14

    Lilac Schoenbeck is vice president of Product Management and Marketing at iLand. She has nearly 20 years of experience with product management, marketing, strategy, business development and software engineering in the grid, virtualization and cloud domains. She is currently vice president of marketing at iland, a global enterprise cloud hosting provider. Prior to this role, she led cloud and automation marketing for BMC Software and has worked for IBM, Fortisphere, Innosight and the Globus Alliance. Lilac holds an MBA from MIT Sloan School of Management and a Computer Science degree from Pacific Lutheran University.

  • The Persistence of Enterprise Tech Failure Rates

    The Persistence of Enterprise Tech Failure Rates

    During a recent dinner conversion with a CIO friend, I was surprised to learn that his organization was having challenges delivering the applications and IT services on a timely enough manner that the business needs. The business is taking too long to approve the budget for major tech projects to start, then develop and deploy, and the CIO expressed frustration how it is always behind the demand curve and following where it should likely be in the market. His level of frustration as he described the situation was painted all over his brow.

    Hearing this was surprising to me; after all, we’ve been writing about how such problems delivering with speed and agility are challenges that are designed to be solved by DevOps, agile development methods, microservices and all of the things we focus on here at devopsy.kinsta.cloud and Container Journal.

    The discussion we had got me wondering how common this situation remains. How many companies are still struggling with their ability to retool themselves into more agile developers? In the late ’90s it was common for tech projects to fail. I recall surveys I reported on that found 60 percent, or higher, failure rates of large projects. But back then software rollouts were truly big bangs. There were years of development time and hundreds of physical servers and thousands of endpoints that had to all be managed. There existed layers and layers of committees and bureaucracies between the developers, IT admins and business leadership. IT is supposed to have moved beyond all of that.

    Unfortunately, however, if recent surveys are any indication, it still seems very common.

    A survey conducted last year by portfolio management provider Innotas found that more than half of tech projects are not well aligned with the goals of the business. The survey, the annual “Project and Portfolio Management Landscape survey,” also found that more than 61 percent of IT professionals questioned did not think that they have adequate resources to manage demand for tech projects in their organization.

    Part of the challenge may be that there’s inadequate project management in place at many organizations. The survey found that 38.7 percent of respondents didn’t have a project management office at their organization; however, 16 percent are building such offices. Additionally, 25 percent of those surveyed said they don’t have a formal methodology to prioritize projects.

    Other areas of concern ranged from project prioritization (26 percent) and alignment (13.8 percent). Attaining benefits and finding the appropriate budget were also challenges at 12 percent or fewer of organizations surveyed.

    This is concerning, as more enterprises are doing everything they can to move more swiftly (or, at least say that they are). As we covered in “Digital Transformation Strains Traditional IT,” according to a recent report published by Salesforce’s “2016 State of IT,” IT leaders are focusing on mobile apps, migration to the cloud, building adequate cybersecurity/incident response, customer-facing digital apps and productivity apps.

    The Salesforce report found that 68 percent of respondents are increasing their tech budgets on mobile apps, cloud and security. The majority (63 percent) of respondents also said they plan to increase their budgets allocated to cybersecurity, while 62 percent will spend more on employee productivity apps.

    Some of the things that has come up, repeatedly, in my conversations with other CIOs is that those companies that are struggling have poor business-to-IT relationships and ongoing feedback. This creates a lot of distrust and poorly aligned priorities.

    We covered a lot of this earlier in a number of posts, which are available here:

    Five often expressed obstacles to enterprise IT innovation

    Enterprises still struggle to leverage IT as a tool to innovate

    The IT mandate: Be a catalyst of business innovation

    Driving Innovation with DevOps

  • Digital Transformation Strains Traditional IT

    Digital Transformation Strains Traditional IT

    It’s hard to believe, but it’s almost been 13 years since Nicholas G. Carr wrote his famous essay, “IT Doesn’t Matter.” In that column Carr argued that IT had become so pervasive in enterprises and so widely used that it had essentially become a commodity and was no longer useful as a tool for business differentiation.

    “Behind the change in thinking lies a simple assumption: that as IT’s potency and ubiquity have increased, so too has its strategic value. It’s a reasonable assumption, even an intuitive one. But it’s mistaken. What makes a resource truly strategic—what gives it the capacity to be the basis for a sustained competitive advantage—is not ubiquity but scarcity,” Carr wrote.

    If that sentiment was accurate then, and I wasn’t convinced it was at the time, it’s not accurate anymore. Today, how enterprises are building and implementing IT is a clear differentiator when it comes to delivering apps business users and customers need and want, built and designed in ways they want to interact, and delivered in a timely manner.

    According to a recent report published by Salesforce, “2016 State of IT,” IT leaders are focusing on mobile apps, migration to the cloud, as well as building adequate cybersecurity/incident response, customer-facing digital apps and productivity apps. The report found that 68  percent of respondents said that they are increasing their budgets on mobile apps, cloud and security. The lion’s share of respondents also plan to increase their budgets allocated to cybersecurity (63 percent) while 62 percent will spend more on employee productivity apps.

    The report survey, conducted at the end of 2015, is based on responses from 2,255 CIOs and IT leaders from within the United States, Canada, Brazil, Australia, Japan, France, the United Kingdom and Germany. One of the first things to leap out at me from the results is, based on my interviews with many enterprise users, this increased focus on mobile apps and employee productivity apps will certainly be welcome in most enterprises—mobile app backlogs are a problem in many organizations today, as we covered in “Make ‘Mobile First’ an Innovation Strategy,” “Mobile App Development Will Soon Grow More Enterprise-Focused,” and “For More Mobile Wins, Enterprises Must Find their MVPs.”

    As IT leadership had to do in every other transformative period (and cloud, mobile, data analytics are all transformative) such as the displacement of mainframes by PCs in the 1980s, the rise of the local area network and the arrival of the commercial web in the 1990s, IT is at the center of business strategy. CIOs and IT leadership need to make sure they get themselves out in front of these trends and align the services technologies they are delivering with what their users need. According to the report, this need for IT to drive innovation is forcing leadership to rethink their IT organizations. And, as a result, according to the “State of IT” report, to help address this, 60 percent of enterprises now have a relatively new position in the chief digital officer.

    Of course, as this push by enterprises continue, the competition for talent heats up. According to the “State of IT” report, the IT skills demand gap is widening: there just isn’t enough talent to go around. I expect this to grow worse as these enterprise budgets for mobile apps only continue to grow in the years ahead. And one-third of those surveyed in this report said that they are having a painful time keeping skills relevant with emerging trends in cloud, mobile and data analytics. Seventy­-two percent say talent/IT skills development and training will be absolutely critical or very important for their team in the next five to eight years.

    According to this eWeek story, “How the Skills Gap Is Threatening the Growth of App Economy,” while nearly 80 percent of respondents of a CA-sponsored study, “The Battle for Competitive Advantage in the App Economy,” said that becoming a “software-driven enterprise” is a top priority, the biggest challenge they have in realizing that goal is the skills shortage. The top four critical skills in that survey close resemble the findings in the “State of IT” survey: data science, collaboration, DevOps and APIs.

    The research firm Gartner predicts that by the end of 2017 demand for mobile app development services will grow no less than five times faster than the capacity of internal IT organizations’ deliver mobile apps. With steady mobile phone sales continuing to fuel demands for enterprise mobile apps, the result will be, according to Gartner analyst Adrian Leow, that enterprises will have a hard time rapidly developing, deploying and maintaining mobile apps to meet demand because of the scarcity of developers with good mobile coding and development skills.

    “Organizations increasingly find it difficult to be proactive against competitive pressures, which is resulting in their mobile apps becoming tactical, rather than strategic,” Leow said in this statement. “We’re seeing demand for mobile apps outstrip available development capacity, making quick creation of apps even more challenging.”

    IT leaders are also seeing demand outstrip supply of those with skills in IT security and data engineering and data science—and there’s no sign of a letup in any of these disciplines. Considering all of that, and what Carr write 13 years ago, parts of IT may very well have become commodities—especially at the infrastructure layer of the IT stack. Just don’t try and sell that view to anyone trying to clear their mobile app backlogs or get the most value out of their data today. They’re too busy trying to keep up and hopefully innovate a little to have time to listen.