The five stages of digital maturity

Where does your organization rank for digital maturity, and how can automation get you to the next level?

Digital is now the default setting for tech companies. During the pandemic, businesses found new ways to reach their customers and support remote workers. That has put a new level of pressure on every aspect of digital operations, and the pressure continues to rise. Employees have embraced hybrid work, and consumers expect a perfect online experience.

Digital operations teams have a lot to lose. They’re responsible for managing thousands of services that deliver critical end user experiences. Mistakes can be damaging to the bottom line, and to corporate reputation. But the complexity of these systems means incidents are inevitable.

The key is for organizations to better understand, assess, and improve digital operations maturity. That’s the road to enhanced incident management and reduced downtime. In this article, we’ll walk through the five stages of digital maturity, and how to get there. But first, let’s start with why maturity matters.

Why does digital ops maturity matter?

From aerospace to retail, and from healthcare to banking, digital services increasingly form the backbone of modern business. But they also introduce complexity – a lot of it.

An estimated 92% of global enterprises have a multi-cloud strategy, and the complex application architectures built in these environments could contain hundreds of millions of lines of code, and billions of dependencies. While this infrastructure offers scale, speed, and relentless innovation, it’s also prone to failure.

A secondary challenge is the way teams are organized in these enterprises. They’re often split into separate lines of business with their own siloed toolchains and workflows. This can introduce visibility and communication issues, making centralized management almost impossible. From an incident response perspective, this inefficiency can hit hard, lengthening downtime and impacting the customer experience for longer than it should.

So, while the failure of some services is all but inevitable, the impact on the organization and its customers doesn’t have to be catastrophic. Becoming more operationally mature can help digital ops teams better manage incidents and other unplanned, mission-critical work. It’s all about managing and maintaining the consistency, reliability, and resilience of enterprise IT infrastructure. This can be measured by a team’s ability to detect, triage, mobilize, respond to, and resolve outages and system failures.

There’s plenty at stake, besides revenue and reputation. For every minute a digital ops or DevOps team member is troubleshooting a problem, they’re losing time that could be spending on innovation. Operational maturity can also work to create happier, more productive teams. Research shows that, on average, organizations that take such an approach are able to acknowledge incidents 7 minutes faster, mobilize responders 11 minutes faster, resolve incidents 2 hours faster, and have 14 fewer hours of downtime each month.

The five stages of digital ops maturity

The first step to becoming a more resilient and innovative organization is to understand your current levels of digital operations maturity. This will enable your teams to benchmark yourselves against industry best practices, and focus on areas of improvement. It will allow you to gain a better understanding of where you need to be heading with strategic planning. And it will help you to identify the right metrics so you can measure and set goals for improvement.

There are five key stages to digital operations maturity:

1. Manual organizations are, as the name suggests, still laboring with manual incident response processes such as queued workflows and ticket-based systems. Issues are always identified by customers first rather than internal tech teams, and are manually escalated by a central team. It can be challenging to reach subject matter experts (SMEs) when escalating unplanned work.

2. Reactive organizations have made some progress at improving visibility and real-time mobilization. They have begun cloud migration efforts and tech teams are starting to decentralize. But this hasn’t been accompanied by improved coordination or knowledge sharing. Major incidents are still being managed in an ad-hoc manner and it still feels like teams are in constant fire-fighting mode.

3. Responsive organizations are beginning to use machine learning tools to identify issues, reduce false positives and minimize “noise.” It becomes easier to select the right set of SMEs, who are able to automatically identify and resolve incidents – but the right processes need to be in place around service ownership and customer facing teams. However, knowledge sharing continues to happen in an ad-hoc fashion.

4. Proactive organizations coordinate incident response in a seamless manner, with teams detecting and fixing issues before customers even notice. A good example would be automating diagnostics to ensure checks and even fixes on common issues such as CPU or memory health can be completed without involving SMEs. Distributed teams have full ownership of any issues and visibility into service dependencies and impact. The right information is delivered to the right SMEs and business stakeholders at the right time. There’s a clear way to document and share learnings from past issues, and programmatic learning technology identifies opportunities for optimization.

5. Preventative organizations are the most operationally mature. Machine learning insight helps them to predict and remediate in order to optimize customer experience. These organizations tie together insights from events and automation to eliminate incidents and prevent humans being interrupted. Application self-healing becomes a reality. These organizations have tied event management with process automation. This can help prevent repetitive, high-toil events that don’t require humans, but it also means events can be prevented with automated runbooks. A culture of continuous learning, improvement and prevention across the business makes it easier to predict the future impact of changes.

What can organizations do to get to the next level?

Progress is happening. Recent research reveals that 50% of organizations class themselves as “responsive” and a further 8% as “proactive”. Just 14% put themselves in the least mature two categories. What’s more, the majority agree they’re better at resolving critical incidents than they were 12 months ago. However, there’s still some way to go.

Intelligent automation can help organizations get to the next level. But automation can come in many forms, from automating the engagement of people, to noise reduction and corrective actions like runbooks. Organizations need to ensure they adopt the right use cases for automation that work for them in order to foster success.

The right tooling can help organizations shift from a reactive to a proactive digital ops approach by reducing and better managing incident “noise.” This ensures only the most urgent and important signals are allowed through, whilst optimizing root cause analysis and enabling auto-remediation. Automation can also reduce the amount of repetitive, manual tasks that responders are forced to undertake, as well as minimize false positives and streamline processes to make individuals more productive as they work through incidents.

This is why organizations are increasingly adopting AIOps and runbook automation tools. In a best case scenario, these will free DevOps teams to focus on what they do best – adding value to the organization via innovation, rather than firefighting incidents. Digital services have created a dynamic and unpredictable world where customer patience is measured in seconds, not minutes. In this world, strategic use of AI and automation can help digital ops teams get back on the front foot.