The early 2000s were a turning point for enterprise software delivery. In those days, companies were struggling to release software fast enough to handle customer requirements and software issues. The entire landscape was a land grab, with companies rushing to get software products to market and hustling to get accompanying mobile apps and websites live before their competitors. While many companies did figure out how to rush an app to market, the aftermath of that process was chaotic, to put it mildly.
At the time, I led product management for a mobile app platform that helped companies with many of these issues, but the truth was that software alone couldn’t solve the problem. Companies themselves needed to fundamentally transform how they built and delivered their software.
Out of that quagmire came concepts like Agile and CI/CD – continuous integration and continuous delivery – created by a crew of developers who combined “use of technology” concepts with best practices in process change. Some new technologies emerged, including containers, code repositories, and test automation that enabled the new concepts to be implemented. Thanks to these improvements, companies were able to speed up their software delivery.
But with more companies delivering software at accelerated rates, a new problem arose: the problem of software operations, and how to ensure a software product was running correctly. This was solved by DevOps, a discipline that works to keep operations workers and developers aware of how their software is running.
The drive towards continuous delivery
Through all these movements, one thread has remained critical: automation.
Within the realm of CI/CD, automation is necessary for the software delivery pipeline to move code through to deployment. In the case of DevOps, automation acts on the events occurring as the software is running to ensure the best uptime and fewest interruptions possible. But automation is so much more than what’s at play within these areas of function.
Automation within an organization can fundamentally change how a business works. In the past few years, the pandemic has driven a tsunami of automation adoption, as well as a tremendous amount of innovation in automation technologies. While everyone has heard of RPA (robotic process automation) automating basic and repetitive work, the Continuous Automation Movement is even more significant, in that it focuses on optimizing the entire business, including both internal and external processes.
This drive towards continuous automation predates the pandemic, as businesses for years have been challenged to maintain a workforce with the right skills, keep employees focused on valuable work, and drive the business results they need to see. However, over the past three years, automation has leapt out of the IT world and made its way solidly into the business world, with tremendous adoption ensuing.
IT professionals may shrug their shoulders at this thinking, knowing as they do that automation has been around for a long time. But I want to point out that a lot has changed here, and this generation of automation improvements bears little resemblance to what we thought of as automation in the past.
4 ways automation across the enterprise has changed
- Automation no longer needs to be siloed. It’s no longer necessary to automate in a vacuum. Now, data, integration, business processes, IT processes, app and site creation, and software delivery and operations can all be orchestrated to work together. This is incredibly important for the optimized business as it means that, regardless of what kind of automation is used to drive speed in response handling and prediction, systems can seamlessly interact.
- Non-developers can now create automations. While it was previously challenging for business users to participate in software creation and automation design, tools like iPaaS, RPA, low code, and new app and site creation tools have democratized the space, making it much easier for non-developers to work alongside their more technical counterparts.
- Automation collaboration tools are on the rise. Automation collaboration tooling enables IT teams to control things like testing and deployment, but it also makes it simple for business users to publish apps and updates without needing to rely on IT’s assistance.
- Automation and AI are a powerful combination. Automation can go a long way towards optimizing business processes, but when artificial intelligence (AI) is applied to automation, optimization soars to the next level. AI as applied to process automation can help discover where processes can be improved, determine where an app or site delivery isn’t working well, and predictively look at key metrics like consumption and performance.
Together, these four transformative factors are the new system of continuous automation.
If you haven’t started a continuous automation initiative within your organization, the time is now
Analyst firm Gartner recently predicted, “By 2024 diffuse (siloed) approach to hyperautomation initiatives will drive up initiative-specific total cost of ownership by 40-fold, making adaptive governance a differentiating factor in financial performance.”
With a team focused on continuous automation, you can both transform processes and optimize them to drive a company’s best possible performance. Whether your team starts small by setting parameters for the scope of what to automate or is charged with driving a full enterprise automation program, taking a holistic approach is the best path to ensure your business sees the full range of benefits.
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