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Tag: digital transformation

The Role of Containers in Business Transformation
Containers hold new promise for business and digital transformation. Yet many differences exist between monitoring containers and monitoring other elements of infrastructure, such as VMs, storage, memory and compute. Understanding those differences is vital for ITOps managers as they navigate their businesses’ digital transformation.

Interestingly, the differences are as much technical as they are organizational. Companies need to explore these differences and consider questions such as, how to ensure that a container-based project performs when it goes into production, and what changes you must make to infrastructure to ensure you have enough compute and storage power to support the containerized applications your development team is going to launch.

The essence of container management is to be prepared for the changes coming from application development, which means understanding resource and infrastructure as it is today to estimate the effect of those changes tomorrow.

Here are four differences ITOps managers need to consider with container management as they move their digital transformation journeys forward.

Containers Versus VMs

The signature feature of containers is they can hold and run an entire application all in isolation. VMs offer operating system level isolation, but at the cost of a much larger footprint; to begin with, each one has its own copy of the entire operating system. VMs are also far less portable than containers, especially when moving among private and public clouds and data centers. As a step toward digital business transformation, most companies are looking for DevOps tools and for ways to deploy their applications to the cloud, whether for QA or production. Organizations rolling out new applications are also gravitating to a container-based architecture from the start.

Advantages of adopting containers include:
- Agility: Instantiating a new container goes as much as 20 times faster than instantiating a new VM. Startup is measured in seconds rather than minutes and once deployed, containers scale up and down rapidly in response to load.
- Density: Most containers are megabytes in size rather than gigabytes. With their smaller footprint, containers allow for as much as five times greater density than VMs.
- Cloud-readiness: Containers can be deployed to any cloud (private, public, virtual or physical) which opens up the possibility of using the same containerized application in hybrid and multi-cloud environments.
- Blast radius: As software developers incorporate and release changes more quickly, they look for ways to control potential damage from bugs. A problem in a container is less likely to cause widespread damage and is easier to isolate and repair than a problem in an entire VM or physical server.
- Cost savings: Every VM requires a hypervisor and an operating system (OS), which can involve licensing and fees. Containers run side by side, sharing the OS kernel of a single physical machine while holding isolated copies of specific library versions they depend on. Architecturally, VMs tend to contain more components and require greater allocation of resources. Containers, on the other hand, tend to hold a specific component or a single micro-service, minimizing resource overhead.
Containers, DevOps and Real-time Monitoring

A company adopting DevOps to speed up deployment of its software products automates as many development processes as possible and relies heavily on automation scripts to move code along, from continuous integration through continuous deployment and continuous delivery (CI/CD/CD) to production. Along the way, multiple developers must check in on new changes. Automated processes, such as health checks and unit testing, take place and then the build is deployed to the next environment, such as integration or QA. With each set of changes, ITOps needs the answers to several questions:
- How will this affect performance?
- What will be the impact of the changes when we deploy?
- Do we have enough compute, storage, memory and networking to support the changes?
In a traditional environment, developers have plenty of time to answer those questions. But if they’re deploying modern, containerized, cloud-based applications, that window tends to be much smaller which can lead to the kind of guesswork that makes ITOps uneasy. That’s where container monitoring comes in. When ITOps can see real-time and historical analytics of containers and their hosts, across physical, virtual and cloud environments, they can create performance benchmarks to help them make informed choices about infrastructure.

Microservices Get Added into the Mix

Microservices are loosely coupled and independent services, each with their own release schedule and lifecycle. Developers are able to make small changes to elements of these applications which allows them to mitigate the risk of negative business impact by reducing the blast radius around those changes. In case of failure in a single change, there’s less to repair and less impact on surrounding, dependent services. We’re seeing developers move away from packaging a single application per container to packaging a single service of an application per container. This allows them to make changes more frequently and keep up with business demands.

Multiple Silos

The goal of DevOps is to bring application development and traditional ITOps closer together. However, container monitoring and management changes things. Traditionally, areas such as storage, network bandwidth, VMs and physical hosts that require monitoring have all been in the ITOps silo, an area that developers don’t typically own. Developers write code and build software in the application development silo and then hand the software off to the ITOps silo to run. However, things have changed and now developers aren’t only writing code, but also owning and using containers in the application development silo. Once the software and containers leave this silo, their consumption of resources like compute, storage, network bandwidth and memory will also affect the ITOps silo. That’s why monitoring and management is as necessary for containers as it is in areas like storage, VMs and physical hosts.

While container technology may be new for the traditional enterprise, the impact it will have on business transformation cannot be ignored. Containerization brings increased simplicity, consistency and portability to production environments, enabling faster IT delivery and increased performance, arming businesses with a new agility and allowing them to rapidly respond to changing customer needs. In fact, according to 451 Research, application containers will be a $2.7bn market by 2020.

The businesses that embrace this opportunity will be taking a vital step towards transforming into bustling digital enterprises that can deliver innovative products and top-notch customer experiences. To learn more about containerized infrastructure and cloud native technologies, consider coming to KubeCon + CloudNativeCon NA, November 18-21 in San Diego.

— Yinghua Qin
October 28, 2019
Legacy Databases Are Holding Back Enterprise Digital Transformations
As enterprises rush to digitize their business operations and enhance customer engagement, few are seeing the success they hoped. A recent survey points to a couple of culprits, including the difficulty of utilizing data held in legacy databases.

The survey, conducted by market research firm Vanson Bourne on behalf of Couchbase, of 450 heads of digital transformation at enterprises across the U.S., U.K., France and Germany found 68% of respondents said getting the right technologies in place for digital transformation can seem an insurmountable task. In fact, 80% report having to scale back ambitions for new IoT or mobile applications.

The primary reason? Big challenges using their data. A sizable 85% of architects surveyed said legacy databases are limiting their ability to transform.

These challenges, however, aren’t easing pressure from business leaders to quickly perform. Eighty-five percent of respondents said they were under pressure to deliver digital projects. And 41% said they were experiencing “high” or “extremely high” pressure.

Despite the pressure to move forward, architects are still scaling back their ambitions, the survey found. It’s no surprise that aging systems and infrastructure can bog down progress, the survey suggests legacy databases may be one of the biggest hurdles enterprises face right now as upgrading legacy databases is something that can be fraught with risk.

The Couchbase survey found that 60% of respondents stated that too much of the IT team’s time spent working on digital transformation projects is spent managing their way through legacy technologies.

The survey also found the most commonly supported way to deploy databases, with 50% of enterprises, still remains to be private cloud infrastructure. This was closely followed by hybrid cloud (45%), on-premises (39%) and public cloud (34%), and 31% are using database-as-a-service.

Some other highlights include:
- A total of 90% of enterprises rely on legacy relational database technology, 38% “heavily.”
- Seventy-two percent of those relying on legacy databases said these databases limit the organization’s ability to implement digital transformation projects.
- Seventy-nine percent of enterprises are actively planning to reduce their reliance on relational databases–with 56% aiming to do so in the next 12 months.
- At the same time, 74% are moving more slowly than they should because they rely heavily on legacy databases for critical applications.
Respondents were asked what transformative technologies they are currently using, or plan to use. Interestingly, 50% said they are–or will be–edge computing, 42% augmented or virtual reality, and 51% blockchain.

Whatever technology enterprises do, or don’t, end up using in their digital transformation initiatives over the long term, one thing should be clear right now: they’re going to be using data to make those efforts succeed. Let’s hope enterprises find a way to unleash their data so they can achieve the transformations they need.

— George V. Hulme
October 25, 2019
What is so Special About AIOps for Mission Critical Workloads?

As the wave of digitization sweeps more enterprises with each passing day, the threats posed to organizations, particularly IT organizations, have never been more complex and pressing. With cybercrime statistics, including those for more targeted crimes (such as phishing) pointing towards an alarming frequency of attacks, the stakes for securing enterprises have been higher.

However, many IT organizations have been unable to smoothly transition into pushing the digitization of their organizations forward. This inability to support and drive digital transformation isn’t a result of a lack of effort on behalf of these organizations. Instead, it has everything to do with the unavailability of the proper management tools needed.

Unfortunately, many IT organizations lack the tactics and tools needed to overlook the smooth shift to digitization on such a grand scale, which often leads to the degradation of critical business applications, along with IT slowdowns and outages. Luckily, however, artificial intelligence for IT operations (AIOps) arrives like a beacon of hope for revolutionizing IT application, along with increasing business agility.

The Failure of Enterprise in Tackling the Burgeoning Complexity of IT Infrastructure

A primary reason behind the ever-present issue of IT slowdowns in enterprises and organizations that is frequently overlooked is the fact that the customer-facing side of IT (applications) is growing increasingly complex with each passing day.

As the increasing number of applications continue to occupy more and more space, the IT infrastructure grows into a vast and hybrid structure which often spans across multiple clouds on a grand scale.

Although the vastness of the IT infrastructure is a byproduct of the digitization drive taking enterprises by storm, it is still worlds away from the security infrastructure of yesterday, which was much easier to manage and analyze.

From the Internet of Things (IoT) connecting thousands of devices onto an organization’s network to complex issues such as bottlenecks, application slowdowns and outages, along with performance latency and the ever-present threat of phishing attacks via a free host website (000webhostapp, being the most commonly used host), organizations are just setting their systems up for failure at some time in the foreseeable future.

Owing to the flourishing complexity of the IT infrastructure, an organization’s system fails to cope with new, dynamic workloads for any multitude of reasons. Usually, the system is utilizing extra resources or is under the influence of a recent addition to the system.

In instances of outages or IT slowdowns, the pressure to fix the IT infrastructure falls on the IT team, who are tasked with the immense responsibility of analyzing and diagnosing the issues as they occur in real-time, along with coming up with a solution that satisfies customers and prioritizes the business aspect of an organization as well.

Unfortunately, however, without access to the proper tools and techniques, the IT team can only conjure security patches that resolve the problem for the moment but fail to withhold security in the long run. Also, without the ability to effectively predict a pattern for the ever-present security threats, the IT team is operating on a whim rather than basing their solutions on the rationale.

How Can AIOps Help the Situation?

To leave the momentous challenge of perfecting an organization’s IT infrastructure solely on the IT team is not only outdated, but it is also impractical. Taking into consideration the complexity of the threats facing enterprises, a solution that arches above each aspect of cybersecurity in an organization should be implemented.

Today, that solution arises in the shape of AIOps. The hybrid IT infrastructure has become too complex to be handled through traditional tools and tactics, which is why AI, along with machine learning and automation, has to step in to bridge the gap.

Unlike other security strategies, AIOps integrates a wholly modern and unique approach, which allows for the AI to view systems in terms of business outcomes. Simply put, rather than analyzing and diagnosing identities, infrastructure and applications independently, the AIOps platform follows the path taken by the user into the complex IT infrastructure and back out of it.

Ideally, AIOps platforms run automated investigations that derive the root cause of existing and recent issues on a regular basis. When it comes to managing a business-critical application, an AIOps platform can detect an unusual response within the system, whether it’s an anomaly in a workload profile or variant response to critical workload.

Other benefits to incorporating AIOps as a security tool include tapping into the truly unique set of capabilities offered, including predictive capacity management and forecasting/predictive abilities. The predictive ability of AIOps allows for the AI to smartly notify IT teams about any attack or potential outage, or slow down, before they actually happen so they may act accordingly.

By taking a different approach to the pressing issues faced by enterprises today, AIOps manages to do what several security strategies have failed to accomplish—provide organizations with an end-to-end, app-centric approach to security, which also takes into consideration the context at hand.

Moreover, AIOps will push organizations to shift their focus from reactive problem solving and cause them to optimize their IT infrastructure on a more proactive basis. Fundamentally, AIOps provides IT teams with the necessary tools to diagnose and combat both internal and external threats to an organization’s security infrastructure.

After the integration of AIOps within an organization’s infrastructure, enterprises can turn their attention into optimizing the balance of critical workloads, along with prioritizing business functions and improving applications, rather than worrying about security.

What Hurdles Can Enterprises Expect with AIOps?

Despite the countless benefits AIOps brings to the table, certain obstacles arise when it comes to the implementation of the security model into organizations.

Perhaps the most apparent obstruction organizations have to deal with is the extensive amount of time investment AIOps requires. Like every other security tool centered around an AI or machine learning technology, time is absolutely pivotal for the learning to actually take place. A simple way to smoothen the transition, AIOps must be fed with data, statistics and analytics originating from multiple data centers.

Another common issue that arises, mainly because of a lack of research, is when an AIOps platform fails to perform as per the specific requirements of an enterprise. Keeping this in mind, CIOs must voice their concerns about fine-tuning AIOps before committing to a vendor.

AIOps abilities in performing an in-depth analysis into the IT and security infrastructure—within the context of the applications it performs—gives the unique chance to stay ahead of the threats they face.

— Rebecca James

October 18, 2019
Low-Code Meets DevOps: A Smart Way to Manage Modern App Delivery Demands
In a fast-moving and often fiercely competitive marketplace, companies need to embrace technology to stay relevant and drive growth. To this end, the business community is increasingly placing a high priority on digital transformation. In fact, more than 80% of organizations believe that digital transformation is crucial to business success.

Digitally driven processes can power increased business speed and agility, as well as enhance competitive differentiation. Many organizations are now focusing on tools and methodologies that allow them to optimize more processes through accelerated internal application development efforts. Their goal is to be able to create, test and deploy the volume (and variety) of applications required to elevate performance and unlock more opportunities.

In response to these growing needs for rapid app delivery, DevOps practices are evolving and becoming more critical to the success and agility of a business. According to a study conducted by Verified Market Research, the global DevOps market was valued at $3.62 billion in 2018 and is projected to reach USD 20.01 billion by 2026. Today, many businesses are combining DevOps approaches with low-code or no-code app development platforms, because these solutions provide them with the tools to build applications faster and more efficiently. This strategy helps to alleviate the immense pressures placed on developers today, by streamlining their workloads and responsibilities, while simultaneously enabling them to reduce their development cycle times.

The Business Benefits of Fast, Agile Application Development

Due to combining the roles, practices and culture of software developers and ITOps teams, DevOps allows a business to deploy apps more rapidly and with a higher degree of consistency. This is essential in organizations where there’s more pressure than ever before to deliver applications at the speed of internal and external demand.

Often, the goal of adopting DevOps within a company is to reduce the tedious manual tasks that monopolize developers’ time and lead to app delivery backlogs. Solutions that help lighten and streamline the workload of DevOps–through automation and low-code development environments–are becoming more critical as a growing number of demands are being put on this still somewhat evolving, yet increasingly prioritized, team role and culture.

Outlined below are a few examples of how low-code app development platforms can enhance the growing role of DevOps and improve the bottom line. This approach helps to:
- Broaden the app development space to non-technical professionals: As mentioned before, low-code platforms enable a wider pool of less-technical users to work on and improve the speed at which applications can be built. Instead of the traditional app development team being solely responsible for a growing number of application requests, business users are now able to support digital transformation efforts by building and modifying their own processes, without writing complex lines of code.
This approach makes the process of development more accessible to non-technical professionals. As a result, businesses can liberate their developers from routine coding work and redeploy these highly skilled individuals to more strategic projects that are critical to core business processes.
- Facilitate faster application building: In addition to making application builds more accessible and less complex, the low-code environment also speeds up the entire development and deployment process. With this approach, companies can reduce development timelines from weeks or months to hours or days. Accelerating this cycle is crucial in any business that aims to outpace competitors.
- Streamline consistent application deployment: Low-code platforms can integrate into toolchains (or a set of programming tools) that can automate the deployment of applications across various business environments. This ensures that apps created by non-developers can be deployed in the same manner as traditional, developer-based applications. This consistency provides a lower cost of ownership because it allows a low-code platform to more easily integrate into the business processes and workflows the organization already has in place. This minimizes the risk of disruption and irregularities.
As businesses embrace innovation and elevate performance across the enterprise through agile, accelerated app delivery, the role and function of DevOps will continue to grow in influence and priority. Businesses that strategically leverage low-code solutions in combination with modern DevOps practices are likely to position themselves for growth, competitive differentiation and sustainable business success.

— Holly Anderson
October 14, 2019
Building Effective Digital Transformations

Enterprises have reportedly spent upwards of $5 trillion on their digital transformation efforts, yet they’re also not hitting their objectives. In fact, in many industries, such as banking, health care and utilities, only half of organizations are keeping pace with their digital transformation expectations.

According to Joe Garber, global head of strategy and solutions at Micro Focus, it’s essential to set goals early and clearly. Garber said most organizations find that their primary objectives for digital transformation fall into one of four buckets: optimizing for speed by prioritizing enterprise DevOps, maximizing agility with hybrid IT, driving insights with predictive analytics, and enhancing the ability to protect users, applications and data with advanced security measures. “Establishing a framework early on helps inform next steps,” he said.

Once those categories are in place and prioritized, many organizations can benefit from starting small with one department or one geography. This will enable organizations to test their theories and control their trials more closely, but also leverage positive results to establish a business case for future projects, Garber said. “Just be careful to think broadly and long-term when you decide what technology to deploy—software that may be good for a small-scale operation can break down or paint you into a corner if you’re not looking at the big picture and select technology that can support your enterprisewide requirements,” he said.

Contentstack chief operating officer Matthew Baier advises organizations to pick a real-world challenge and provide a proof of concept that could garner a quick win. Be sure to note upfront the goals and key performance indicators. “Another piece of advice is to include both the affected business and IT teams in the project, to capture feedback holistically about what impact digital transformation efforts have across the organization,” he advised.

Nabil Freij, CEO at GlobalVision International said pilot projects are key to effective implementations. “Before transforming your entire processes, you need to make sure that the proposed transformation will bring sufficient monetary, quality and/or schedule benefits before they are proliferated across the board,” he said. “This is not hard to do. Be selective with the pilots that you undertake. Make sure that they are representative of the majority of the work that your teams undertake on a regular basis. Create key metrics that are important to meet and measure and track them. After a few pilot projects, you will have enough data to start making conclusions regarding further testing or regarding starting across the board or limited implementations.”

With objectives down, it’s essential to get the right people in place. “The first step in developing a successful digital transformation strategy is bringing together the right people to assess the current state of the workplace environment,” said Dave Maffei, president and chief revenue officer at Akumina.

“To get the right feedback, organizations should deploy a survey and interview their employees across business units and job functions to understand what technology and processes they value most, as well as what challenges they face while performing their job duties,” said Maffei. “Without completing this essential step, organizations won’t truly understand what solution they need and could be missing out on solving existing challenges to the overall employee experience. Having internal feedback will allow organizations to understand what their ideal solution might look like.”

Larry Wolff, CEO, Wolff StrategyPartners, added that a team of digital transformers should be established, if possible. “If an enterprise has the luxury of time, such as no imminent existential threat, then they may want to set up a single, high-performing team to tackle an initial phase of the digital transformation. Set them up for success so that others want to emulate them and drive the next phases,” he said.

“People are naturally apprehensive about change. Drive one positive change initiative to diminish those fears and get more and more people on board,” he added.

— George V. Hulme

October 8, 2019
The Secret to Digital Transformation is Human Connection

We know digital transformation is no longer an option for today’s organizations–it’s a requirement. End-users have come to expect an easy, digital-native experience, whether they are ordering a pizza or automating an entire network infrastructure, which is why businesses and governments are throwing trillions of dollars at new technologies and related services.

Organizations must build and deliver exciting new software applications, faster than ever before. They must continuously innovate, adapt and stay ahead of the never-ending demands of digital data, experiences and channels. These demands have contributed to the meteoric rise of cloud computing, DevOps methodologies, open source technologies, predictive analytics, AI and many other innovations.

However, even with all these investments, more than half of all new software or IT projects still fail. In fact, according to a study by Forbes Insights, 75% of executives say they’re still waiting to reap tangible benefits from disruptive technology. Here’s why: Technology alone does not solve digital transformation. It doesn’t address some of the most fundamental issues that inhibit or enable transformational success nor the most critical dependency, which is people.

To truly transform, organizations must go beyond just technology to embrace the human elements of this evolution. We’ll look at six factors driven by the human side of the business, and how each of these can help, not hinder, digital transformation when properly addressed.

Organizational Culture

One of the biggest challenges for companies as they embark on digital transformation is the needed cultural change. The technology decisions, while daunting, are easier compared to the cultural shift organizations must undertake to truly become digital leaders. Top down mandates won’t work, because for it to be successful, digital transformation needs buy-in from all involved. People need to connect to the change and feel they can have an impact, or at the very least, know their job is safe amid the change. Also, to achieve the speed of change and innovation, organizations need to empower everyone to make decisions, not just a select few.

Embracing an open culture can help with this. In an open culture, digital leaders look at their organization more like a community of individuals, all contributing to something bigger than themselves. Anyone can participate, lead and suggest a change or improvement. This methodology helps for the best ideas to win out, regardless of where they come from. Employees feel part of the process and ultimately, it empowers them to work toward the shared goal. Let me be clear, this isn’t a democracy or a lack of clear decision making power. However, it is using more open decision frameworks that move everyone toward a common goal, which brings us to the next big human factor.

An Inspiring Vision with Metrics of Success

It is often said to start with the end in mind. With digital transformation, this is absolutely true. For digital transformation to be successful, everyone in the organization needs to understand, and ideally agree with, the destination. Visions are not just words—they are driving the priorities, investments and decisions made by every team and employee. Without a clear vision, organizations can’t create an executable business strategy. The key is to make sure you have a vision that clearly describes what your organization will be like in several years–and then make that vision measurable.

All good visions come with goals attached to them. Yet according to research from Gartner, 50% of organizations have no digital transformation metric or way to measure progress for digital transformation. Set up clear, ambitious targets–stretch goals the entire company can work toward. These metrics allow organizations to clearly check on how they have progressed and where they still need to get to.

Cross-Organizational Teams and Processes

Another cultural barrier to digital transformation is siloed behavior and workstreams. Often, teams refuse, or just don’t know, how to break out of their silos. Digital transformation requires collaboration and breaking down boundaries, as data, insights, applications and processes need to flow seamlessly throughout an organization. It all goes back to having a vision and an open culture. Without a culture of trust and a shared agreement on the end goal from across the organization, you won’t be able to break down these silos.

With the vision and culture in place, adopting DevOps and agile processes is a great way to initiate this. It helps bring together business, technical and other people from across an organization to solve a specific problem or figure out how to better work together. Often, this takes a courageous leader, who doesn’t measure their value by the power or budget they hold, to broker these cross-organizational relationships and new teams.

People Development

In talking to IT and business leaders all over the world, they are faced with a common challenge: skill set gaps. This includes both soft skills, such as communications or management, and hard skills, such as technical capabilities. According to Red Hat’s survey on Global IT Trends & Priorities Research, the biggest blocker to an organization’s digital transformation efforts is people. More specifically, the survey found IT talent or skills gap was preventing organizations’ efforts from being successful. Technology and digital processes are changing so quickly, it’s hard to keep up. This is creating a digital skills gap in organizations across industries and around the world.

Rather than hoping to hire people with the skills and talent you need, I encourage organizations to develop the people you have. Take your loyal employees who already fit your culture and believe in your vision and invest in them. Also reward them for taking risks. Digital disruption does not happen by standing still or encouraging small moves–it takes big bets. Leadership must also be willing to stand up for employees who try new ideas and push the boundaries.

User Experience Focus

According to CareerFoundry, which manages a Web UX design school, the cost of a bad user experience is high. Really high. Its research estimates bad user experience costs e-commerce companies $1.4 trillion in lost revenue.

As we focus on the human connection part of digital transformation, user experience takes the front seat and is a top priority. We need to start with the user. What are they trying to do? What is the pain we are hopefully solving? Too many times organizations start with the cool technology and slap on the user experience as almost an afterthought. By starting with the user, projects are more likely to give users the feeling they are interfacing with a human being rather than a digital thing—and ultimately, will succeed because of it.

Personal Connections

One of the downsides of the digital era is we don’t have enough face time. We believe video conferences provide the same benefits as face-to-face meetings. We put our trust in digital handshakes instead of the real thing. However, to succeed at a company-wide digital transformation, you can’t rely on digital communication alone. Ironic, right?

One key reason for making face time is to build trust. As humans, we need to see someone, look them in the eye, shake their hand, respond to their cues. All of this helps us trust the other person. To put your organization through a major transformation takes trust–across the organization, but especially of the leadership. This means leadership needs to get out there and talk to employees, customers, partners and users. Take the time and the effort to make your transformational efforts relate to the humans doing the work and buying your products or services.

The Bottom Line

The most common mistake organizations make is believing technology alone can solve their problems. Technology is still needed for a successful digital transformation. In fact, I am not in any way advising we all sit around and have a lovely conversation and hold hands to solve these massive technology issues. However, technology must be combined with human connection.

In other words, it’s not just what you use to transform, but the how and the why of your transformation. The human elements require hard work across culture, hiring, people development, leadership and communication.

Human connection is the killer application for digital transformation.

— Margaret Dawson

September 26, 2019
Before We Burn the Martech Silo
There’s an ongoing debate about where marketing technology (martech) should sit in an organization. Does it live with the CMO, the CIO, the CXO–a hybrid strategist with both IT and marketing background–or some collaboration? As technology use grows, it’s tempting to move martech under another role. Before we burn the martech silo, like how McDonald’s, Uber, Mastercard and others are doing, let’s look at the implications for DevOps teams.

A recent article in PR Week cited a University of Texas study claiming “only 40% of a corporation’s marketing-related activities today report to the CMO.” Martech is being siphoned off into other areas–sometimes slowly, sometimes abruptly. It’s because the tech outweighs the marketing, at least in the eyes of the C-suite.

In March 2019, McDonald’s announced they were acquiring Dynamic Yield for $300 million. Dynamic Yield rose to fame as one of the leaders in omnichannel personalization. Translation: they watch visitors searching, viewing and ordering. Then, they show those related results to other visitors. With the deal closed, McDonald’s announced they were eliminating their CMO position and creating an SVP of martech reporting to the CIO. Automating the customer experience with in-store kiosks and mobile app ordering is their top priority.

Another case where mobile app ordering dominates, Uber clobbered both its CMO and COO in June 2019, right after going public. Their rockstar CEO said he wants to be more involved in day-to-day operations. Uber rolled non-martech functions into a VP of marketing communications. For Uber, martech is the product–an automated experience connecting riders and eaters with drivers. Everything else is branding and communications.

There’s a third org chart option: the CXO, or chief experience officer. More digital customer interaction is forcing a partnership between technology and marketing insight. Mastercard hired its first CXO earlier this year, bringing in a veteran from the digital marketing industry.

What do these three moves have in common, besides moving martech out of traditional marketing?
- All have powerful, ubiquitous brands with huge recognition.
- Their core product shouldn’t change much moving forward.
- Personalization shapes their offers using global and local trends.
Here’s the thing: Marketing automation automates what marketing knows. When the current and future requirements are clear, evaluating martech tools is easier. Moving martech out of branding, advertising and communication to IT sounds reasonable until you realize what you don’t know.

The martech silo often houses hunters, not farmers. Marketers have different metrics. They discuss impressions, and click-thru, and time viewed, and calls-to-action, and conversions. Strategy and content often have more impact on results than the delivery technology. In a fast-moving environment with many product or service offerings, what works once may not work elsewhere. Creativity comes into play, with cycles of learning.

In today’s SaaS model, marketing can pick a cloud-based tool and explore possibilities with minimal IT support. That’s good, until data and process accumulate, needing a bigger silo. Be careful. Burning the martech silo can be far worse for the organization than leaving it alone, even with all the shadow IT downside. No matter who does it, picking tools for a martech suite before understanding requirements is a formula for disaster. Without integrated marketing experience, IT is set up for failure. It can cascade into marketing failure and finger-pointing.

For a fluid marketing environment, a CXO is best suited for the job. They speak the language of both sides, along with representing external customers and their experience. If your organization doesn’t have a CXO, modeling a DevOps team responsible for martech in that image is the next best option.

DevOps solves the problem of speed marketing needs in making changes. Teams also have deep experience in maintaining applications and overseeing security IT wants. Many teams already have a product marketing person managing their software requirements. What a martech DevOps team needs is people with customer and digital marketing expertise. This include creative writers, graphics artists and advertising and social media specialists.

If that sounds like a problem without a CXO running air cover, you’re right. Budget and headcount come from somewhere. Both the traditional marketing team and the IT team want input, perhaps even control. The key for a martech DevOps team is behaving as if the silo had disappeared, no matter what the org chart says. The DevOps leader should keep everyone informed, managing up and across. It usually means creating different presentation views, one for marketing, one for IT and maybe one for the CEO. Make sure everyone gets answers to their questions in their language.

We’re going to have more martech moving forward. Creating effective martech DevOps teams is a priority, even without sweeping C-level reorganization. Don’t just burn the martech silo–reclaim the pieces that work for both marketing and IT and build the right team around the customer experience. If you need help getting started on a bigger martech mission, let’s talk marketing strategy.

— Don Dingee
September 13, 2019
The Bedrock of Digital Transformation

Trends come and go. I’m old enough to have been persuaded, twice, about the good sense of flared jeans. I had a space hopper. I had a Betamax video player. Fads and cool ideas are a constant white noise, vying for our attention. Some will stick, some won’t. And that’s true in technology. No-one admits to owning a C5, but plenty of us built PowerBuilder and Delphi apps. A few of us tinkered with Smalltalk.

But genuinely smart, enduring ideas find a way of sticking, of evolving, and adapting. No-one these days thinks of a phone as a wired device stuck to a wall which you could only use if you asked someone to connect you. And no longer do you have to employ anyone to run in front of you with a flag as you drive your motor car. Like cars and phones, good ideas endure and in the world of computers and IT, the COBOL language is no exception.

Very few organizations of any size are not being impacted by today’s digital era and the seismic changes being seen in the market place. Entire industries have been disrupted beyond all predictions in the last decade or so. Indeed 88% of the Fortune 500 have dropped off that list in the last 50 years, as those who fail to keep up with the pace of change are being replaced by those who can adapt.

But adapting isn’t easy. Making fast progress toward new digital objectives is often hampered by practical barriers that are individually difficult to solve, particularly in the case of the existing technology landscape already in place. Things such as vendor lock in, complex business processes, interdependent apps and data, inefficient delivery processes, technical constraints and skills issues.

Additionally, the technology landscape is forever changing, but only growing in complexity. Today, large global enterprise businesses typically run a hybrid environment, which is a consequence of adopting multiple waves of technological advancements over time. Each individual advancement offered opportunity and progress, but eventually results in a highly complex and inefficient technology environment. Most organizations are pursuing digital transformation programs with a view to reduce complexity, create better flexibility and reduce total cost of ownership.

There has been tremendous value created in business applications and data and there is a lot to be gained in digital transformation by leveraging that value as much as possible, in transforming it with the minimum cost and risk. Much of this value is encapsulated in systems built some time back, and which have evolved with the business. Oftentimes, using COBOL technology. COBOL was invented way back when, but has adapted to support ongoing business technology demands and rigors.

Having an appreciation for where your organization is today, along with an awareness of what needs to be achieved in regard to the required updates, the process used and the infrastructure considered, can assist with plotting the pragmatic steps to develop a plan that delivers transformational value. With some of the most critical systems being written in COBOL, these core systems continue to power a variety of fundamental processes in modern business.

The risks of ripping and replacing systems are measured as an average IT project failure rate of 71%, which amounts to a $1.7tr cost in a single year. These are dreadful numbers and no organization wants to waste that sort of time and money and reputation. There is now a growing realization, from many years of experience in those more radical transformation projects, that their success rate is relatively low, planned costs and timescales typically grow exponentially, and the risks to successfully continue business during such a transformation are unacceptably high.

Enter stage left a more pragmatic approach: modernization. This concept prioritizes on protecting the value of what companies already have, exploiting advancements in technology to deploy and integrate applications in new ways and to surface and integrate data in new ways, with the minimum change to what already exists. Creating portability and operational independence for applications and data is becoming recognized as the fastest and most future proofed path to building a platform for digital transformation. Market influencers such as Gartner and IDC have commented on it, and most of the global systems integrators are industrializing their modernization practices to support companies successfully transform. So what is the underlying technology acting as the catalyst for this modernization and transformation?

COBOL enters its seventh decade of helping run great chunks of the world’s largest IT systems entirely thanks to its staying power; its adaptability.

COBOL’s endurance owes a lot to its original design that make it readable and portable, meaning it can be picked up by new staff quickly, and deploy wherever it is needed. What kept it in such demand owes more to the ongoing evolution of the language itself, and the tooling surrounding it. COBOL works alongside, integrates with and supports containers, cloud, JVM, .NET, JSON/REST, micro services, modern IDEs and other technology typically associated with more contemporary names. COBOL technology plugs directly into a DevOps toolchain that is adopting continuous delivery practices for some of the economies’ most important IT systems.

COBOL is, in fact, a 2019 technology; just with a 60-year heritage.

Next time you pick up your mobile to make a call, or sit in your car to drive to work, ask yourself how you feel about how old that idea is.

— Derek Britton

September 10, 2019
The Barriers to Robotic Process Automation, Part 2

Enterprises are rushing to embrace robotic process automation (RPA) but, as we covered in The Barriers to Robotic Process Automation, Part 1, they’re also hitting considerable challenges along the way. While we cited prominent barriers to the effective implementation of RPA in part one, here, we will provide practical ways organizations can overcome these barriers.

One of the biggest causes of RPA failure is the lack of executive-level sponsorship for such initiatives. When it comes to RPA success, getting management’s attention–and keeping it–is essential. One way to do this is to focus on RPA quick wins and efforts that have a measurable return on investment.

Next, IT leaders need to understand how significant digital transformation is to AI technology.

“An efficient digital transformation strategy will eliminate internal IT silos through integration and automation, leading to opportunities for AI projects,” said Marcel Shaw, AI expert and Federal Systems engineer at Ivanti. Shaw pointed to how organizations that interface with customers will see opportunities for chatbots that leverage natural language processing technology, thereby reducing demand on operators while enhancing the user experience.

“IT leaders will be able to take advantage of machine learning technology that will support and enhance complex automated processes that will fulfill customer requests from beginning to end, without intervention from a human analyst,” said Shaw.

Such benefits could make RPA an easy sale to executive leadership. Other benefits that can be used to sell RPA to leadership include cost savings, more efficient processes, improved process quality and free staff to focus on higher-value tasks.

“The only thing holding AI back at this time is a lack of experience with the technology. AI will take many years to develop. Some estimates point to a 75-year maturity lifecycle for AI. AI technology is designed to learn. As it learns, it will correct mistakes and mature, much like a human has to learn,” said Shaw.

Next up: The high level of investment needed for effective, automated and intelligent robotic automation.

“There’s a great deal of catching-up to be done before most companies can even consider building out their own advanced developments with AI,” said Salvatore Stolfo founder and CTO at Allure Security. “It may be more cost-effective and faster to partner with a software vendor that has already put the time into dedicated research and development to build an AI-powered solution, and then customize that solution for your particular use case.”

Simha Sadasiva, CEO at Ushur might agree. “Many intelligent automation solutions on the market today require a heavy IT investment. This can include hiring an outside third-party just to manage the platform they’ve invested in,” said Sadasiva.

“Those attempting to manage the technology in-house are finding that it requires personnel with sophisticated developer-level knowledge, which is in short supply today. These issues are causing some companies who were initially interested in exploring intelligent automation solutions to abandon their projects altogether,” added Sadasiva.

Sadasiva said one possible way to solve this is to evaluate potential zero code platforms. “These are SaaS-based intelligent automation solutions born in and live in the cloud,” said Sadasiva.

Finally, and while perhaps self-evident is often overlooked: know what needs to be achieved with robotic process automation.

“An organization needs to identify what the problem is that they are trying to solve with AI. This needs to be the most important pain point to them at that point in time. Inherently AI requires data to be able to train the machine to learn,” said Ben Mercer, co-founder at personalized web experience provider Personify XP.

“The challenge for some organizations, when it comes to accessing data, is that valuable data is stored on legacy systems and difficult to extract. In cases like this, it may make more sense to train the AI on new data, than fighting with legacy systems that may delay or reduce the ROI of the deployment,” said Mercer.

Effectively managing data, AI and the resulting automation requires staff with strong skills and experience in these areas.

“Regarding skillset development, most of the skills needed can be learned, but you need to find different types of team members who have a great comprehension of data and database management and secondly a development background,” said Jesse Tutt, CEO at mattress company Gotta Sleep.

Finally, chances are if an enterprise is planning to do something there’s already someone who has tried and has lessons to share. “Every automation project has likely been done by someone else already. Tips and tricks are freely available from others who have more experience so networking on Linkedin, meetups, and conferences are key,” adviced Tutt.

— George V. Hulme

September 9, 2019
Successful Transformation: Challenge the Status Quo

If enterprises are going to succeed in their digital transformations, they need to be able to shake-up and challenge the status quo within their organizations. In fact, not being able to challenge the status quo is one of the biggest barriers to successful digital transformations. Yet, challenging the status quo is always a risky move for individuals and small groups within organizations.

“Many large organizations are intrinsically unable to challenge the status quo and execute a large scale successful digital transformation,” said Mads Hennelund, advisor at consultancy Nextwork. “There are good reasons for this, since established bureaucratic organizations are built in order to handle complex procedures.”

“Most CIOs, CTOs, and enterprise technology leaders want to challenge the status quo, but doing so can be dangerous because there’s no room for error,” said Laura Stringer, principal at strategic consultancy Ninth Fourth LLC. “IT leaders are under intense pressure to deliver continuity and multiple competing projects on an insufficient budget.”

But it’s even more than just budget. It’s human nature’s near-ubiquitous aversion to change and inability to endure a number of losses on the road to find big wins. Stringer and other experts we questioned about challenging the status quo all agreed senior business and IT leadership must acknowledge the risks inherent with experimentation, while also providing a comfort level so teams can execute on transformational initiatives.

Some initiatives will certainly fail and some will succeed. Ideally, like a portfolio of investments, while some investments will fall short, the winners will more than make up for the losses.

“The organization needs a shift in culture to encourage all employees to become more open to changes in their daily processes and tools–digital transformation is largely about creating a culture of constant learning. Without the pressure to provide perfect continuity in current technologies, IT leaders can become more comfortable trying new things,” said Stringer.

“This is one of the reasons why it’s common to see large organizations collaborate with smaller companies for projects,” said Hennelund. “In the financial sector we see a flourishing fintech and insurtech market around established banks and insurance companies. Companies successful in challenging their status quo are those that can navigate between these collaborations or even small in-house sub-divisions that develop new digital IT-based projects,” added Hennelund. “Putting into place a quick decision-making process is also critical.”

This could include making it possible for stakeholders to hold meetings and move forward with their consensus without always having to get board approval.

Such shifts in behavior require culture change. So, how do organizations and IT leaders get there?

First, leaderships needs to make the staff feel safe taking risks and, even potentially, failing. “This only happens in an environment where current practices can be freely challenged without repercussions from upper management,” said Nabil Freij, CEO and GlobalVision International, Inc.“This means that upper management needs to be on board with digital transformation.”

Only then is the right culture, one that can safely challenge the status quo, possible. “The right company culture is extremely important. One that embraces adopting technology, taking calculated risks, thinking outside the box, rocking the boat, challenging status quo, rejecting complacency, empowering employees to lead and overcome challenges…is the essence of enabling digital transformation,” said Freij.

The ability to challenge the status quo all begins with building the right culture. A culture that encourages fresh thinking and intellectual risk taking. “Thirty-eight percent of CIOs think their digital strategy would fail without an innovative and experimental culture,” said Joe Garber, global head of strategy and solutions at Micro Focus.

If so, it’s essential for organizations to build and maintain such culture.

— George V. Hulme

August 19, 2019