What's Next In Digital Transformation?

Digital transformation isn’t new. However, the conversation about the topic has shifted. For years, it has been the prevalent topic in the boardroom, and it remains so today. With billions of dollars invested in digital transformation initiatives, executives are now exploring the impact of their investments and asking, “What’s next?”

The hallmark of previous digital investments was technology for the sake of efficiency and productivity. Companies adopted more software, systems, and devices with the hopes of becoming completely automated and intelligent. But with additional technology came sprawl, disparate systems and siloed teams. Today, digital enterprises are sorting through the chaos to determine how people and systems can best work together -- how they can recoup their digital transformation investments in bottom-line business returns.

Fast forward to the autonomous enterprise where architecture, automation, and human intelligence operate in harmony to help companies create amazing customer experiences. The bedrock of every company, the network, will be augmented with machine learning to enable fully automated self-healing and self-driving workflows. This is a step beyond digital transformation and its pay-off.

As leading companies embrace this vision, let’s explore three core traits companies face when embarking on the autonomous enterprise journey.

The Autonomous Enterprise Is A Vision, Not A Technology

The autonomous enterprise doesn’t come in a box. In fact, it's bigger than any single technology or solution. While software, network infrastructure, and other technologies are critical to automating processes and workflows, the actual product or solution isn't what makes an enterprise autonomous.

The autonomous enterprise framework is analogous to an autonomous, self-driving vehicle. Many cars today, like many organizations, contain automation technology. Cruise control, blind spot technology, and backup-camera detection systems are examples of low-level automation, but they’re not intelligent on their own. Each technology performs a basic function -- accelerate or decelerate to a certain speed, alert the driver when an object appears within set proximity to the sensor, etc.

What makes a car autonomous is the software it uses to add intelligence to the array of automated functions so it can operate on its own. For example, software, hardware and machine learning (ML) help the autonomous car recognize what’s happening on the road around it. Feedback from the sensors is relayed to the cruise control and lane-assist automation to guide what the vehicle should do (adjust left, speed up, stop). It happens instantaneously based on real-time feedback. The car is connected like a neural network, transforming the car’s capability from basic cruise control to a self-driving system. That's the critical difference between automation and autonomy.

Like the average car today, many businesses have sophisticated automation technology that streamlines things but isn't yet intelligent. They must embed automation, software, and ML within a reliable network infrastructure to become autonomous. The autonomous enterprise of the future depends on marrying AI and human intent.

Building An Autonomous Enterprise Is A CEO Imperative

One may assume the autonomous enterprise falls under the CTO’s purview, but the CTO cannot be the only driver of the autonomous enterprise business imperative. Autonomous enterprise initiatives aren't akin to moving your CRM to the cloud. The goal isn’t to make IT more efficient. It’s about the entire organization of people and systems working in a fundamentally different way for the sake of customers. The CTO has a seat at the table, but it’s a bigger table.

Before you can become an autonomous enterprise, you must understand the underlying goals and core identity of your enterprise. No person should understand this identity better than the CEO. An organization must have a commitment at the highest level and a firm understanding of the differentiated experiences you hope to deliver to your customers. For example, Amazon prides itself on being “Earth’s most customer-centric company.” Every strategic decision maps back to this core ideal of bringing more convenience and value to its customers.

After the vision and strategy are articulated, the success of the initiative requires complete organizational buy-in. Leadership teams should continue to reiterate this vision while managing for alignment.

Getting To The Autonomous Enterprise Is A Journey

While there are many companies making tremendous strides in software integration and automation, these initiatives are only the tip of the iceberg. Similar to the evolution of digital transformation projects, the journey to an autonomous enterprise is an iterative process that will look different from organization to organization. It will take time.

One monumental challenge companies face when trying to embark on the autonomous enterprise journey is defining the scope of the first project. The key is to identify a project that isn’t too broad, making it impossible to achieve anything and isn’t too narrow, making it difficult to yield a measurable impact.

For instance, consider a major concern in the healthcare industry: Hospital security and patient safety. In 2018, 82% of healthcare organizations experienced significant security incidents, according to the "2019 HIMSS Cybersecurity Survey." While a security breach is serious in any organization, an attack on a healthcare institution could impact technology supporting human lives. How can organizations pursue autonomous enterprise projects to address patient safety?

Overhauling entire systems and replacing thousands of devices is expensive and time-intensive. That project is too broad. In contrast, securing individual devices is inefficient, and it would be difficult to measure the impact. That project is too narrow. One right-size project might be to explore how healthcare IT teams can use AI to detect security incidents by spotting small changes in behavior indicating attacks that evaded traditional security defenses. ML can augment tools already in place to learn the expected behaviors of the connected devices, and a combined system can automatically alert and respond when an endpoint acts in an unusual way. The scope of this project is achievable -- and it has the potential to reduce the number of security incidents.

“What’s Next?”

Forward-looking companies recognize digital transformation isn't the end game. And technology isn’t the sole means of achieving transformation. There's a new era of automation on the horizon where human intelligence, technology, and systems will work in harmony. The autonomous enterprise will drive the next wave of business transformation, and we’re just getting started.

*This blog post was originally published by Forbes on 6/21/19.

About the Author
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Lisa Yeaton
Senior Social Media Manager

Lisa Yeaton is a Senior Social Media Manager at Extreme Networks. In her role, Lisa oversees all of Extreme's corporate social media accounts and creates corporate communications content.

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