Beyond Silos: Automation Strategies for the Long Term

    Within today’s enterprises, teams are looking for ways to optimize their existing assets to increase agility, so they can meet customer demand and quickly capitalize on emerging opportunities. Automation is one key way to pursue this optimization. This post examines why traditional, piecemeal automation approaches are falling short, and it offers key automation strategies that will enable enterprises to lead disruption, rather than be the victim of it.

    The Limitations of Siloed Automation Approaches

    To date, many teams have focused on the straightforward automation and digitization of existing manual and analog processes that are used to operate IT and business services. In the past, distinct job schedulers and IT experts would typically orchestrate tasks, such as file transfers, ERP processing, data integration, and other workloads. Different teams and tools would manage various aspects of infrastructure provisioning, application release, and service delivery.

    But in this new era of transformation and disruption, this type of model can’t last because it tends to create islands of automation. When automation is introduced opportunistically, without a holistic vision, fragmentation is a problem. Too often automation is employed in a tactical way, just to relieve a particular pain point: Each element is automated without proper consideration of how this automation affects the ecosystem it sits in, or how various tools and processes will work together.

    The immediate consequence you experience from a point automation strategy is higher cost of operations because of your inability to realize economies of scale. In addition, even if it stems from an attempt to reduce complexity and save time and effort, this siloed automation ultimately results in convoluting the IT landscape further, causing delays and inefficiencies that occur when tools are not running in sync.

    The Imperative: Pervasive Automation

    Today’s digital processes demand the integration of multiple internal systems and cloud services. But with complexity comes challenges. In a world dominated by apps, development and operations teams are struggling to keep up with the endless consumer demand for new features and functions, without causing negative consequences to ongoing business processes.

    Within most IT organizations, teams now recognize that a fundamental change in approach is required if they are to contend with the convergence of new customer experiences, new technologies, and modern practices such as SRE, DevOps, and DataOps.

    To unleash the full potential of automation, you need unified enterprise automation strategies to integrate and standardize processes across all functions and technologies. Only a holistic automation strategy can empower teams to work efficiently and drive customer-focused agility as part of their digital initiatives. From a business perspective, effective enterprise automation can be the difference between being agile and being a victim of disruption. In other words, if today automation is just technology, tomorrow automation is business.

    In the next phase of evolution, teams will move beyond the simple replication of existing processes, and begin to employ automation to create new sources of business value and customer engagement, often by using big data and artificial intelligence. Following are some key automation strategies that will propel businesses over the long term.

    Automating DevOps

    Through DevOps, development and operations teams coordinate and collaborate more closely than in traditional siloed IT organizations. However, you don’t achieve the huge increase in release velocity with developers and operations staff eating pizza together and slapping each other on the back.

    DevOps necessitates a shift in working practices towards collaboration to root out manual processes, then automate wherever possible. Automation is the culmination of all DevOps collaborative efforts.

    DevOps automation orchestrates existing islands of automation at an enterprise scale and automates handoffs between subject matter experts. Moreover, this approach can help ensure application enhancements are developed and deployed in a secure manner across all environments, including production. Ultimately, automation ensures a consistent and repeatable application deployment process, allowing IT to meet business demands more directly, fostering innovation, revenue growth, and customer loyalty.

    Automating Data Pipelines

    The digital world is swamped with data, but that data is only useful once you can extract value from it. In order to leverage the benefits of artificial intelligence and machine learning, companies have to adapt data flows and analytics to move beyond the boundaries of traditional data warehouse silos.

    However, it’s not easy to manage that data pipeline efficiently. Too often, the data you need is generated in too many places and processed in too many silos. Through emerging disciplines like DataOps, teams can incorporate agile approaches to minimize the cycle time of analytics development. This approach aims to bring together environments, tools, models, and data into a unified, end-to-end ecosystem. These pipelines enable you to incorporate an increasingly intricate blend of big data into end-to-end business processes. They also enable teams to leverage cloud and traditional processing models. The result is that data scientists and operations teams can establish a far more efficient data pipeline.

    As you work to do more and more with data, automated data pipelines are invaluable. By fully automating workflows that previously demanded manual intervention or synchronization, you improve IT agility and ensure more consistent outcomes. Further, you help IT to speak the language of the business.

    Automating Incident Response

    For every organization, when downtime or other incidents occur, it is essential to restore functions to working order as quickly as possible. A fast and accurate response by your IT services team prevents undue impact on your business. This responsiveness is also the foundation for building positive customer relationships and a good reputation for your brand.

    If they are to meet their service level imperatives, your teams have to achieve fundamental breakthroughs in scale and efficiency. In order to accommodate larger volume of changes while accepting the increased risk of failure, IT organizations are increasingly looking to adopt SRE models.

    Automated service incident remediation can enable the resolution of the most common problems, from a simple system restart to full recovery runbook. This automation can also put more power into the hands of level 1 operators. This sense of control and faster time to resolution improves the customer experience, while freeing IT experts to work on complicated issues.

    Longer term, automated remediation can be employed to analyze incoming tickets within existing IT service management (ITSM) processes, sort them into pre-identified categories, and automatically start the appropriate predefined workflow—ultimately resolving and closing the ticket without manual intervention. In this way, automation reduces the cost per ticket and improves the overall quality of service delivery.

    Conclusion

    Digital transformation is fueling rapid integration and automation across development, deployment, and operational support processes and infrastructure. While each silo of automation can certainly deliver benefits on its own, make no mistake: Unified enterprise automation strategies can result in much more significant benefits, both to IT and the business.

    Enterprises looking to prepare for the future should be aiming to systematically automate every digital process, and build their business on top of this automation. This requires a new perspective: Automation must not be seen as a function but as an end-to-end service. In order for enterprises to compete, IT and business leaders should consider automation as a service for all to leverage, and fundamentally shift their mind-set from niche automation to consumerized automation.