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Tag: digitization

How DevOps Tools Are Contributing to Automation Initiatives Across the IT Landscape

Prolific advancements in IT, specifically in agile methods and culture over the years, has led to burgeoning needs for a more holistic end-to-end software delivery approach. Agile development is an umbrella term that encompasses numerous incremental and iterative software development practices — including Kanban, SAFe (Scaled Agile Framework), Scrum, Extreme Programming (XP), Lean Development, among others.

Each methodology works on its own unique approach. However, the core commonalities they share lie mainly in their values and vision. The methodologies integrate continuous feedback from iteration to refine and deliver a successful software system. They include various forms of continuous evolution, such as continuous integration, planning and testing, of both software and project. Furthermore, one of the most significant aspects of agile methodologies is their keen focus on empowering workforces to work together and collaborate more efficiently, thus simplifying and speeding up decision-making processes.

Advancement in agile development is what has birthed the DevOps culture. The technology is born from the rising need to adapt to increasing software velocity and throughputs generated through agile methods.

Understanding DevOps

The DevOps market consists of a set of practices, designed to integrate and automate processes between IT and software development teams, enabling them to create, test and deploy software in a quicker and more efficient manner.

The term DevOps, which was coined in 2009 by Andrew Clay Shafer and Patrick Debois, is a combination of the words “development” and “operations.” It is also indicative of a cultural shift in the IT sphere, which bridges the gap between historically siloed teams, such as operations and development.

The DevOps framework essentially adopts a culture where the critical focus is on facilitating collaboration between the business, operations and development teams. Although tools are considered as pillars of the technology, DevOps is designed to deliver continuous value for customers, empower organizations to provide solutions of the highest quality at swift rates, and bring about the automation of the entire business process spectrum, from building to deployment of a product or application.

Shifting Trends Toward Automation in Software Development Processes and the Subsequent Impact on DevOps Adoption in the IT Space

The software development process consists of several integral parts, among which testing is a crucial task. It allows developers to monitor the functionality of the software, monitor and register performance, and detect any aspects that require remediation. However, with software projects becoming increasingly more complex as the years progress, and with project development life cycles accelerating, conventional methods of manual QA (quality assurance) testing fall short in meeting testing objectives within the desired time frames.

Consequently, software developers are shifting their focus toward automated workflows and testing tools, in order to expedite testing routines without compromising on consistency and completeness in QA processes.

DevOps practices are significantly dependent on automation to ensure frequent and timely deliveries across platforms. Studies have shown that nearly 85% of IT leaders claim that automation is a critical aspect of their DevOps strategies. This is attributed largely to the fact that automation empowers infrastructures to successfully field constant changes in codes that are associated with DevOps tools.

Furthermore, automation allows the effortless scaling of environments and unburdens skilled workforces from mundane and repetitive tasks, enabling them to focus on more integral aspects.

Considering a process perspective, automation in testing involves the addition of test automation actions and tools to regular software development regimens. For instance, new builds delivered to a repository can be automatically subjected to automated testing procedures using a number of prescribed tools, with little to no need of developer intervention. The results are recorded with care, then compared to previous test runs and eventually submitted for review to developers.

Depending on the outcome, the software can then be cycled back to the developers for further remediation or approved for deployment. This is especially relevant in terms of the DevOps framework, which relies on continuous integration/continuous delivery (CI/CD) pipelines.

CI/CD pipelines are a prominent outcome of developer operations, allowing developers to validate the quality of the software with minimal intervention, and deploy apps and software to customers in a quicker manner.

CI/CD platform CircleCI, for example, has recently raised over $100 million in Series E funding, in an effort to boost the development of their DevOps product suite. This move is indicative of CircleCI’s proficiency in delivering an automated approach to DevOps practices, including tools for companies to create, test and deliver software.

How Is the Current Pandemic Impacting Digital Development?

The COVID-19 pandemic has asserted a massive influence on the industrial landscape, driving workforces across the globe into remote-only work set-ups. With millions of people working from home for a seemingly indefinite period, enterprises across the globe are rallying to accelerate automation efforts in order to more efficiently deliver digital business applications to engage their employees from remote workspaces.

According to various studies, nearly 73% of IT operations and DevOps teams are working toward maintaining and expediting initiatives for digital transformation throughout the current crisis, holding the belief that the value of digital offerings is set to witness a positive growth trajectory in the social distancing era.

DevOps industry players such as JFrog are working toward providing enterprises and teams with access to cloud-based DevOps technologies, free of cost, particularly those which are undertaking active research and response efforts to combat the COVID-19 pandemic. These DevOps technologies include Pipelines, Xray and Artifactory, among others.

While the exact impact of the global crisis on the DevOps environment in particular and the IT space in general is yet unclear, it is becoming more prominent that the strong focus on the prevention of such crises in the future — both in and out of the IT realm — is likely to set a great precedent for the growth of the DevOps industry in the years ahead.

June 16, 2020
How DevOps Powered by AI and Machine Learning Is Delivering Business Transformation

The use of artificial intelligence (AI) and machine learning (ML) is fundamentally changing the way we think about DevOps. Most notably, it is delivering a new form of DevOps that recognizes the need to have systems that are intelligent by design and underpinned by comprehensive security (DevSecOps). For many, this will be the crucial next step if DevOps is to shorten the software development lifecycle for all connected intelligent systems, ensuring the continuous delivery of secure high-quality software.

By now, most organizations understand DevOps is a substantial discipline that they must adopt – according to Deloitte, organizations adopting DevOps see an 18%-21% reduction in time to market. By breaking down the silos between business and IT operations, DevOps can ensure consistent levels of productivity, efficiency and service delivery, all of which hold weight in these times of heightened uncertainty.

To put it simply, DevOps can help businesses compete in already congested marketplaces. Through a foundation of continuous integration (CI) and continuous delivery (CD), organizations can ensure the customer receives the product they demand in the fastest time possible, while mitigating any elongated frustrations experienced from a lack of harmony between systems engineers and operations teams. Incorporating AI and ML into that DevOps strategy will take things to the next level.

AI and ML Are the Next Evolutionary Step for DevOps

Today’s companies are data-driven and being built as digital platforms. However, just 28% of organizations are currently succeeding in their digital transformation journeys. Increasingly, corporations are looking at what AI and ML can do to help them realize their transformative ambitions.

Both the AI and ML markets are expected to experience huge growth over the next three to four years. Analyst firm IDC, predicts worldwide spending on AI systems will reach a href=”https://www.marketresearchfuture.com/reports/machine-learning-market-2494″>42.8% by 2024.

What AI and ML reveals for these companies, and the increasing value of what Al, ML and devices can do together, are changing the way organizations view the world as they digitally transform. Coupling AI and ML with DevOps will lead to a significant shift in what DevOps gets involved with.

Primarily, it sets DevOps front and center of an organization’s wider digital transformation ambitions. If digital companies run on living data, then the development of these intelligent systems is an enticing environment for DevOps to prove its wider value to the organization like never before.

Security Takes the Center Stage

According to a TechTarget survey of key IT decision makers, cybersecurity and risk management were found to be the number one area for spending this year, with more than 53% of respondents saying they saw budgets increase in this area. And security is a crucial element that any organization employing a DevOps strategy should be considering.

DevSecOps is the simple premise that everyone involved in the software development cycle is responsible for security. In fact, the saying “security is everyone’s responsibility,” is a mantra that has been repeated often, and just as often ignored. Embedding security within every part of the development process, ensures security and compliance monitoring tools keep pace with the speed and agility that DevOps offers. It is a common understanding that security is the biggest block to the rapid and seamless development and deployment of systems, as security solutions have not traditionally been built to test and code at the speed DevOps requires.

Ultimately though, more automation from the start, reducing the need for manual configuration from security architect is where DevSecOps shines. This reduces the chance of misadministration and occurring faults, which can lead to downtime, and potential breaches or attacks. Quite often, the best ways to secure your organization is through simple hygiene factors, such as regular patching and software updates.

The reality is that every organization employing DevOps should really be approaching it as DevSecOps. Security is of ever growing importance to each and every organization and, through empowering it with AI and ML processes, it can be enhanced too, simplifying the processing of data to easily identify threats or potential vulnerabilities in the security makeup.

Reaching Beyond Human Capability

The future will be made up of connected intelligent systems that span the intelligent edge, all the way to the cloud. The expectations of these systems are based on the lifecycle of a typical mobile application with constant feature enhancements. But, how do you know what to deliver next, especially when things are moving so quickly, and as developers are inundated with information and data from a number of different sources? This data deluge can be powerful, but it can also be overwhelming.

Crucially, this is where the power of AI and ML comes into play. AI and ML will aid developers in making sense of the information housed across various data warehouses. In DevSecOps, there has always been an approach to automate everything, and AI and ML will be instrumental in automating the analysis and processing of data – a task that is now far beyond the capabilities of humans.

Incorporating AI and ML will enable developers to better understand and use the data at hand. This will see developers understand not only the error, or the occurrence of a fault, but the detail of what happened in the run up to the fault – vastly reducing the chances of incurring that fault again. AI and ML will also be responsible for enabling the transformation from diagnostics to prognostics across any and all tools and systems, making it easier for developers to anticipate, identify and resolve faults or errors.

Increasingly, we’ll see organizations benefit and drive value from real-time insights. They’ll do this through AI and ML frameworks deployed on active systems to deliver optimizations based on real-time development, validation and operational data. This level of real-time actionable insight bolsters DevSecOps’ ability to achieve CI and CD, through improved, reduced mean time to resolution, easing the impact on operations and, ultimately, enhancing the end-user experience. It remains to be seen if incorporating AI and ML into the DevSecOps cycle will achieve the delivery of self-healing systems that can detect and resolve issues without the need for human intervention. With true AI, however, this might well be possible.

The benefits and potential use cases of AI and ML are widely acclaimed, and while we are still some way from seeing their full potential, the capabilities they currently possess are revolutionizing many sectors. The fact is, if DevSecOps is to continue to keep pace with the vastly growing digital data economy, then it will become reliant on advanced technologies such as AI and ML. Data is powerful if used correctly, but with so much of it to process and analyze, that can be a challenge.

A move toward secure automated processes is the progressive step that many organizations need to consider if they are to realize their digital transformation ambitions. Organizations cannot continue to do things the traditional way and expect to get the results that the new world is looking for.

June 3, 2020
The Next Frontier for Enterprises: Moving to a Product IT Operating Model
In the world of technology, there are few things as dramatic and impactful as enterprise IT’s recent ascent from an enabler to a strategic business driver. Tasked with powering next-gen digital business models, IT teams today are fast realizing the harsh truth that they must make a pervasive strategic shift from traditional project-based operating model to a product-centric one.

Traditional project-based operating models focus resources on a specific application or project, leading to fragmented experiences and a disconnect with the rest of the IT organization or company. For instance, in many cases, one team may be working on a back-end system, while entirely different teams work on the front-end application or updating databases. A product-based operating model takes a more holistic approach to ensure projects are integrated and teams work concurrently toward a uniform goal.

The days of plan/build/run are numbered as digitization forces IT leaders to act fast, think outside the norm and embrace the blurring boundaries between the digital and physical worlds. A product-centric operating model, sometimes also referred to as a DevOps operating model, accelerates organization-wide digital transformation and consolidates a business’ competitive standing. Companies must transition to a product-centric model to scale-up their agile programs to support end-to-end innovation and reduce siloed operations and projects.

The companies that have embraced a product-centric operating model are quickly realizing the benefits, but for many IT departments, they have yet to experience or fully understand why the shift is imperative.

What’s Driving the Shift to Product IT Operating Model?

As digitization takes hold and becomes more and more pervasive, CIOs are realizing that intertwining IT and business objectives is quintessential to respond to market changes quickly and remain competitive. Since 2018, volatility has returned to global equity markets in a big way. With the economy in a constant state of flux, coupled with rapid globalization and unprecedented disruption from technology, the average lifespan of a company is 20 years, compared to 60 years in the 1950s, according to Credit Suisse. Overall, the changing business environment makes few things as abundantly clear as this–agility, an appetite for new markets, new products, bias for action and a fail-fast approach will be the new mandates for IT leaders going forward.

To this end, most CIOs are replacing portfolios of discrete, siloed projects with product lines that enable a specific business capability. The key factors driving the shift toward a product IT operating model include:
- Need for Holistic Transformation: Siloed functions have no place in the digital business world that thrives on integration of data and information across structure, culture, processes and technologies. To enable holistic transformation, organizations must draw a balance and establish cross-collaboration between organizational guidelines versus autonomy of teams for process, architecture, technology, tools, etc.
- Lack of Alignment in Traditional IT Operating Models: Lack of alignment across large teams and multiple organizational groups (such as IT, finance and business) prevents organizations from executing an end-to-end digital strategy. Shifting to a product IT operating model can help steer organizational units toward a common goal. It can facilitate greater collaboration between different DevOps teams that support different products and domains. Recognizing the failure of existing IT governance and the pressing need for a shared digital transformation vision, IDC predicts 40% of CIOs will adopt new digital governance models.
- Need for Speed: Most companies cited that their digitization efforts were hindered by inflexible or slow processes with a traditional IT operating model. Adopting a product-oriented management approach for IT can help organizations define and agree on a pace of change congruent with their readiness and appetite. According to IDC, 65% of CIOs will expand Agile/DevOps practices into the wider business to achieve the velocity necessary for innovation, execution and change by 2021.
- Lack of Integration Between Old and New Technologies: Lack of integration between new and existing technologies is a key factor that keeps organizations from realizing the full potential of digitization. Modern companies need to balance innovation, experimentation, adoption of new technologies and tools with the enterprise’s need for business results, cooperation, risk management and compliance. Because a product-centric model takes a holistic, end-to-end approach, it is ideal for integrating technologies, processes and teams at scale.
Embracing a Next-Gen Operating Model

To compete with newer, nimbler companies such as Facebook, Uber, Spotify and others, traditional companies that are serious about continued growth are leaving no stone unturned and embracing a product IT operating model. From being providers of reliable IT services, CIOs have emerged as strategic partners in driving business transformation. Modern day CIOs are driving business innovation and identifying opportunities for competitive differentiation, not delivering ad-hoc, siloed services. As cloud-first and AI-first become the new mandates for organizations, re-engineering the IT operating model is quickly becoming central to creating value, competitive advantage and growth.

— Rohit Nand
December 6, 2019
IT Enables Scale in Digital Transformation

Few corporate functions have seen their role disrupted as much as IT these last few years. The help desk days are long gone. As digital transformation accelerates, IT is becoming less about outright technology and more about creating capabilities that enable the overarching business strategy. As such, IT is the engine behind any company’s digital transformation.

Here are three ways IT can advance today’s digital journey by empowering the business from a consultative, strategic position.

Going Digital While Digitizing

First, let’s agree on digital transformation’s foundational terms, which understandably elicit some ongoing confusion: “digitization” and “digital,” which the MIT Center for Information Systems Research has described as two discrete yet complementary things. In short, digitization is about leveraging technology to improve or enhance business processes, operations and offer development. By contrast, going digital is about giving customer value to digitization—with the goal of revolutionizing the customer experience and creating new digital business models. What’s the point of digitizing a process or product if the user experience is poor?

Balancing these complementary efforts is essential. It is the role of IT to ensure that digitization and digital can happen at the same time.

Rethinking the Economic Model

To keep up, IT must move away from traditional demand-based models, enabling capabilities with a product mindset instead of a time-bound project mindset. The concept of capability (that is, a business area enabled by a consistent set of IT products) is quite critical to avoid creating one-off or point solutions that are just the means to answer to a specific demand. Instead, looking to IT as the enabler of corporate practices that are always evolving and improving (e.g., cybersecurity) is imperative. Embracing Agile methodologies will bring this approach to fruition.

Pivoting to this kind of a capability-based model requires a modern API-based architecture, which fundamentally is the way out of building and/or replacing monolithic systems. As today’s world requires a fine balance of speed and frugality, a mastery of resource allocation, and a prioritization rigor, we must unburden resources aimed at replacing systems that are working just fine.

To that effect, Amazon Web Services has a great architecture principle referred to as “two is better than zero.” In other words, it is better to have two similar IT components emerge from fast-paced, parallel development than nothing due to project bottlenecks and unmastered interdependencies. Even if we want to drive re-use every time we can (and have mechanisms for that), we should not bog down overall transformation due to one weighty project. So thinking in terms of not just tolerating diversity, but enabling it, is a good way to built an architecture that can empower both agility and resiliency.

Addressing Technical Debt Continuously

Technical debt is perhaps every incumbent company’s biggest challenge when going digital. The cost of maintaining legacy and outdated systems is high, and heavy technical debt is another obstacle to achieving full digital transformation. Accenture consultants see this every day, describing this burden as a price that “hinders [companies’] ability to innovate and adapt in the digital age.”

This is where IT can come to the rescue by having a structured approach and engagement model designed to streamline systems and processes in order to free up resources for reallocation. First focus on eliminating legacy custom-built applications and localized tools based on criteria that are well known and shared (think of a scoring system). Here, again, resource allocation can play its part by ensuring the full cost of those legacies is being recognized by the organization.

A huge added advantage of a continuous effort to remove technical debt (beyond cost, the reduction of obsolete systems and a simplified IT landscape) obviously relates to security. Especially at a time when the average cost of a single data breach globally is $3.9 million. In fact, potential cybersecurity and IoT-related physical safety concerns “will pressure CIOs at G2000 companies to increase IoT security spending by up to 25%, temporarily neutralizing business productivity gains” by 2020 (IDC). Redirecting technical debt can offset part of this essential spending on security.

Accenture notes that 79% of CEOs report that their organization is adopting new and emerging technologies faster than they can address related security issues. IT teams therefore must carry the security torch, determining and implementing ways to make security easier for employees while also protecting the end-to-end digital ecosystem. A continuous effort to reduce the technical debt is one way—among many others—to improve posture.

A Place at the Digital Transformation Table

Indeed, these are exciting times for every business. Digital is all about creating customer value, guided by a better understanding of customer needs deeper in the enterprise. Since providing a great experience is not only about the user interface but also about the ability to mobilize the internal systems in order to deliver at scale, IT experts now have a major seat at the table for revolutionizing the customer experience at scale.

The essential ingredients to full digital transformation are clear: digitizing and going digital, being able to embrace emerging technologies with an architecture that makes diversity efficient when required and creating cyber citizens that continuously reduce the corporation’s technical debt. Behind the scenes and now front and center, IT is pushing forward the transformation strategy for companies staking a competitive claim in today’s digital economy.

— Hervé Coureil

November 15, 2019
Legacy Systems Prove to be Digital Transformation Headwind
In a survey of 450 digital transformation leaders, a sizable 73% of respondents said that, through digital innovation, they have made significant or better improvements to the end-user experience. Twenty-two percent report much more significant results than that, they self-reported as having transformed or completely revolutionized end-user experience. That’s considerably higher than the 15% in the same survey in the previous year.

These results, from the Couchbase 2019 Digital Transformation Report conducted within the U.S., U.K., France and Germany, are in stark contrast to results of a recent Kony survey which found, despite $5 trillion having been spent by enterprises on digital transformation, the vast majority of digital transformation initiatives fall short of customer expectations. Still, when it comes to digital transformation success, at least as far as its impact on customer experience, success is in the eye of the beholder.

Of the $5 trillion spent over recent years, much of it has been invested in backend system improvements. If the Couchbase survey is any indication, there remains considerably more spending on back end and legacy systems. Despite the feeling of success cited in the survey, 86% of respondents said they are prevented from pursuing new digital services or transformation projects.

Here’s why:
- That 86% said factors including reliance on a legacy technology, complexity of implementing technologies and lack of resources and skills had prevented them from pursuing a new digital service or other transformation project their organization wanted.
- A total of 55% said their reliance on relational databases somewhat limited their ability to implement digital transformation projects, while 17% said “severely.”
- An 81% have had a digital transformation project fail, suffer a significant delay or be scaled back in the last 12 months.
- A total of 42% said they were behind schedule, or at risk of falling behind, on their most significant digital transformation project.
- A 73% said, while the huge potential of digital projects is often talked about, most of the time they fall short of being truly transformational or revolutionary–albeit a fall compared to the previous two years.
Perhaps part of the challenge enterprises face is they are reacting to market pressure and not being led by business needs or visions for the business’s future created inhouse. According to the Couchbase survey, 52% have their digital transformation strategies set by IT and not business leadership. The drivers for these transformations tend to be, the survey found, reacting to business pressure such as customer demands for new services or responding to regulatory mandates. Surprisingly, the survey found, only 8% of transformative ideas executed are brainstormed from within the organization.

Perhaps part of the reason why organizations are so reactive is because the rate of disruption is accelerating. According to the survey, 91% of respondents believe the speed of disruption in their industry has accelerated. In fact, 40% of respondents categorized that acceleration as rapid. Moreover, survey respondents plan on spending more on digital disruption this year over last, $30 million compared to $27 million.

— George V. Hulme
September 18, 2019
Digital Transformations Fall Short, Survey Claims

What is the nature of digital transformation? Is it a permanent shift in the digitization of business processes, or a race to a known destination? Should organizational investments in data analytics, continuous software development, business processes, culture, machine learning and shifting enterprise technology from a perspective of ownership and control to consumption be judged from the eye of the consumer?

The answer seems straightforward. Eventually, the market is the ultimate arbiter of digital transformation success. However, many organizations today are busily investing in technologies they hope will serve them well in the years ahead, and some of the largest investments are not immediately visible to consumers.

According to the Kony Digital Experience 2019 Index Survey report, businesses are “still missing the mark” with consumers despite nearly $5 trillion in digital investment. The report didn’t distinguish how the $5 trillion was being spent and in what areas of the business the investments were made.

“As companies race toward digital transformation, their leaders might want to hit the pause button and reassess their efforts. The significant investments by companies around the world to transform their business to become more digital has had very little impact on consumer experience,” according to the report.

Perhaps—or, perhaps, many organizations are laying their groundwork and it’s way too early to make such a call.

According to the survey, customers (65%) are more satisfied if their digital experiences feel effortless (who wouldn’t?) and 63% of customers said they would spend more money if their digital experiences feel effortless. Of course, history is full of surveys detailing consumers stating how they’d act but consequently end up acting entirely differently; people are notorious for answering surveys how they think they should answer or how they wish they would act rather than how they do act. Famous examples include surveys on privacy, security and personal finance.

The findings of this survey are based on 1,600 respondents across the U.S., Europe and Asia. According to Kony, 800 were participants or leaders of digital transformation initiatives in organizations with 500 or more employees.

The study focused on business investments and customer experiences within the banking, retail, utilities and healthcare industries.

Interestingly, respondents said organizations in banking (54%), retail (59%) and utilities (51%) are keeping pace with their expectations but are not delivering differentiated digital experiences. The big laggard was health care, with only 48% keeping pace and 20% being behind respondents’ expectations.

The study concludes businesses are not listening to—or understanding—the evolving needs of their customers because only 28% of enterprise digital transformation initiatives are started specifically with customer needs as the priority.

“Improvements in costs and efficiencies are always welcomed and clearly important to project funding, but the real returns and real impact of digital starts and stops with its impact on the customer experience,” said Thomas E. Hogan, chairman and CEO of Kony Inc.

That’s an incomplete way of looking at what is happening when it comes to digital transformation and the scope of technological change underway. That figure and comment are based on the survey findings that 68% of digital transformations were business process-centered, 4% employee experience-centered and 28% customer experience-centered.

My take: In most cases, business leadership knows what they need to do and where they need to place their primary focus. And it’s a tough call to broadly state businesses are missing the mark without looking at how specific businesses are choosing to invest, as well as their stated objectives. Such information was not available in the survey.

In many—if not most—cases, businesses are focusing on what they need to do, such as eliminating technical debt, automating business processes with robotic processes, streamlining their development pipelines and more. Of course, it’s essential to provide quality experiences to customers, as the survey found 47% of consumers will consider switching providers if their current provider doesn’t deliver the digital experience they demand and expect.

That said, it’s not always true that digital transformation begins and ends with the customer. Large enterprises have decades worth of technology investments they must manage, and successful digital transformation isn’t a set finish line that enterprises are rushing toward. Rather, it’s a never-ending continuum, and those enterprises that are investing in the removal of technical debt, modernizing their software delivery methods, machine learning and streamlining their businesses to be more cost-effective and agile are building platforms that will sustain their businesses and provide exceptional digital experiences over the long haul.

— George V. Hulme

July 24, 2019
Getting the Enterprise Digital Core in Shape

While enterprises rush to transform their business digitally, most are taking tactical steps rather than building a comprehensive digital core that can be improved over time. Very few are taking a thorough view of their entire technology portfolio and looking for ways to create a cohesive core—their digital core—to provide them the strength and stability to move forward swiftly in their digitization efforts. The enterprise digital core essentially is the vital set of technologies and employee skill sets that enable the organization to deliver its digital services. These services are both consumed by customers and internally by staff and others.

How do enterprises get their digital core into shape?

Emphasize Talent Over Technology

While a strong digital core includes the technological platform, it is also a people-platform. “The heart of digital transformation isn’t technology but the mindset and skill sets of your staff,” said Andy Lin, senior vice-president of strategy and consulting at Nexient. Digitization, he said, means enabling customers to transact and interact with you anytime they want, from anywhere, using any device. The only way to get there is if leadership makes it clear to staff why digitization is crucial; otherwise, they will struggle to adapt, he said.

If the staff does understand the reasons behind the transformation, they will—instead of just following rules for the sake of rule-following—be much more likely to adopt a digital mindset. They’ll also be more likely to embrace the training and skill set development they’ll need to make the transformation a success, Lin added.

Scrum.org CEO and product owner Dave West agreed that the digital core starts with the customer. “There needs to be a clear line from the mission and strategy of the business with the outcomes the customer wants,” he said. Teams need to understand clearly how their work helps deliver the organizational mission digitally to the customer, no matter what that mission may be. That means everyone needs to be clear on the nature of the business, or organizational business, as well as what success looks like

West also advised organizations that seek to improve their digital core to look both inward and outward for support. From within the organization, of course, support should come from leadership, who must set the course and ensure efforts are going in the right direction. “Externally you need to build a network of support from people and organizations that have done it before,” he said.

Put Cloud at the Core

Of course, a strong digital core must have a strong technological foundation. In today’s typical enterprise, that may very likely mean more about subtraction than addition. While emerging technologies, such as internet of things (IoT), artificial intelligence (AI)/machine learning (ML) and others are recommended to be integrated within enterprise software, “Many of them are not generally suited to run on legacy IT infrastructure,” said Maxim Ivanov, CEO at enterprise software development firm Aimprosoft. “The digital core relies on intelligent automation scalable platforms that are integrated in the cloud and prepares data for next-generation technologies.”

Gabriel Salazar, digital solutions manager at systems integrator Enstoa, agreed that building a cloud-based infrastructure goes a long way to improving the digital core. “It’s important, however, not to simply carbon-copy the business processes used prior,” said Salazar. “Look to take advantage of all automation, machine learning and analytics offered by converting and folding them into your updated business process.”

Finally, if organizations want to have a strong digital core, they are going to have to work to maintain it. “Due to the speed of technology change, getting your digital core in shape is a continuous process. Start by understanding what is preventing you from supporting business goals, what is causing ongoing stability or performance issues and what reduces your time to market,” said Nick Polachek, senior principal of strategy and transformation at Maven Wave Partners.

To do so, Polanchek recommended building the digital core iteratively while maintaining the focus on delivering business value or resolving current issues. It’s also important, he said, to have a thoughtful future vision for your digital core and ensure that each delivery is at least aligned, if not an improvement, over core technology already in place.

After all, keeping that digital core in shape is an ongoing process that will require ongoing work and practice.

— George V. Hulme

June 6, 2019