The old William Gibson adage “the future is already here—it’s just not very evenly distributed” has never been more apt. We live in a world where the leading internet companies have modernized their datacenters, software, and processes beyond what the average enterprise can even imagine. The gap has become so wide that we talk in terms of digital transformation to advance from one state to the other.
Over the years, Zorawar Biri Singh has offered his own unique vision the enterprise’s future—as head of cloud for IBM and HP, as a VC at Khosla Ventures, and until recently as CTO of Cisco. In my interview with Singh in February, he described a next-generation datacenter infused with containerized microservices and pervasive analytics. When I caught up with him again last week, he took stock of technology advances since then, but also outlined the initiatives enterprises must put in place to transform themselves.
Singh broadly defines this as “a modern set of capabilities, tools, and a recognition of culture where enterprises are in a continuous improvement cycle.” If you read InfoWorld, you’re familiar with the technology components: Containers as opposed to VMs, microservices instead of monolithic applications, scalable cloud infrastructure, internet-connected devices transmitting telemetry, and analytics coupled with machine learning to make sense of it all. But Singh’s recommendations go beyond technology.
The collaborative imperative
First and foremost, Singh believes every transformative initiative begins with a committed culture of collaboration. Like many in the industry, he sees devops as the engine of continuous improvement, yet he also recognizes that devops is more than a toolchain or even a methodology. Done right, it establishes a culture where people across the enterprise can breach silos and form ad hoc groups to concoct new solutions.
That sort of collaboration demands the right type of platform. “Collaboration is already moving to video, chat, messaging, and voice converged in one cloud-based platform,” Singh says. He notes that tools and platforms across departments have matured, codifying workflows and allowing them to scale in a cloud-first, mobile-first model–whether you’re talking about Salesforce, Asana, Slack, or Google G Suite, not to mention developer repositories such as GitHub, GitLab, or Bitbucket.
Yet he sees much more ahead. “The next step is how these platforms evolve to incorporate machine learning, cognitive computing, and even intelligent bots to facilitate that collaboration,” says Singh. In other words, collaborative platforms under development today will eventually help identify the people and resources necessary to pull together a project on the fly and sustain it throughout its lifecycle—enabling the next phase what he calls “people-centric digitization.”
According to Singh, at the heart of people-centric digitization is the ability to “look across enterprises and uncover deeply embedded human workflows, both implicit and explicit—the ‘contracts’ that determine how organizations and culture transform.” Ultimately, he says, this will radically change how business gets done and have a vast impact on traditional definition of jobs within organizations.
Machine-to-machine potential
Perhaps the most productive collaboration of all, says Singh, will be between IT and OT (operational technology), the latter defined as that which characterizes an enterprise’s core business: manufacturing, vertical disciplines, logistics, and so on. In most companies, he notes, IT and OT remain separate:
Traditionally, OT roles grew from and focused on the process controls required to operate the manufacturing side of the business. These have historically been custom, siloed tech stacks. In a digital world, the IT and OT domains quickly blur.
Integrating the two—in particular culling telemetry from sensors or intelligent devices and applying analytics and machine learning to that data—offers an enormous opportunity. Singh characterizes this as “machine-centric digitization,” where today’s arsenal of agile technologies and methodologies homes in on core industrial systems. The heart of future IT/OT collaboration, he says, will be around IoT deployments:
With 200 billion internet-connected “things” predicted by 2030, we will see massive demand for processing analytics/telemetry data at the edge—mainly large, ephemeral machine data that’s only relevant for a few seconds or a few minutes out on the edge of a network. If you don’t think, architect, and operate differently with all that data you’ll be left behind.
In fact, supporting this transformation will become a matter of survival for IT as a strategic part of the enterprise.
Sustaining the future
CIOs should either lead the buildout of the agile infrastructure and streaming analytics platforms necessary to extend OT’s capabilities—or get out of the way. As Singh puts it, “OT teams, much like line-of-business teams and their app developers who dove into cloud and mobile development five to eight years ago, will not wait patiently for their IT counterparts to provide tools and platforms to manage their IoT mission.”
Public cloud providers, in particular Google, have suggested that they intend to attack vertical markets in manner similar to ERP vendors of a generation ago. Some enterprises may opt to “exit the IT business” entirely and accept configurable cloud offerings rather than sustaining their investments in on-premises solutions, especially if IT drags its feet.
That’s one reason why collaborative culture along with investments in agility and analytics that extend deep into OT require a commitment at the highest levels of the enterprise. “If this transformation is not led from the company board and CEO level down, and it’s not truly empowering people, you can forget about it,” says Singh. For enterprise IT to stay relevant, IT management needs to start working toward this strategic vision now.