In my previous Industry Insight, I elaborated on the need for agility and how multigenerational IT involves different layers of technology, all of which need to be automated from the bottom up.
Legacy systems such as mainframe also need to be modernised in order to drive digital transformation. Many enterprise-level organisations are still reliant on the mainframe, and yet it forms just one part of an increasingly diverse technological landscape.
As such, we need to be able build workflows that traverse mainframe, distributed systems, the cloud and hybrid environments.
However, the reality is that not many workload automation products have these capabilities yet, and as such, are only able to serve the needs of small to medium businesses. Ironically, the more technology moves forward, the more important it is to synchronise with the older systems that the business still relies upon.
Job scheduling versus astute automation
One of the tangible benefits of automation solutions is speed. However, the ability to turn data into tangible information that can be acted on is equally fundamental to the modern business.
Businesses want faster response times, better-informed decision-making, improved resource utilisation and lower costs. But improving service delivery without redefining all business processes and IT architectures has, up until recently, been problematic.
Adding intelligence to automation will usher in a new era of productivity and innovation, setting new standards of speed and agility.
The traditional approach to workload automation is now changing dramatically once again. Identifying business events as a static series ‒ whether by a timed schedule or recurrent polling ‒ has a number of limitations and is no longer sufficient.
Intelligent business automation can sense and synthesise large amounts of data for driving complex processes and workflows, learning and adapting dynamically. Adding intelligence to automation will usher in a new era of productivity and innovation, setting new standards of speed and agility.
As information flow and event traffic increase exponentially, it has become practically impossible to understand how changes in assumptions or conditions in one arena will affect operational delivery in another.
Therefore, to gain the requisite insights and deliver intelligent results, a workload automation tool far surpassing basic job schedulers and script runners is needed. It must be able to check itself, understand its own business context and enable a company to move from a reactive approach to the proactive intelligent management of business processes.
Organisations should be implementing a workload automation tool that possesses the ability not only to run a process, but also to determine the result of it. This means the workflow has completed and succeeded only when it has delivered the expected business outcome. Instead, as it stands, too many tools simply operate as glorified job schedulers. They are unable to either analyse their own actions or to remedy errors.
As technology advances, new security issues are constantly created. Modern automation tools should be equipped to handle new challenges, and they should be encapsulated within the automation policy itself.
So, what is the future?
Well, as already stated, the advent of software-as-a-service (SaaS) has changed how businesses purchase and consume software. Organisations are continuing to move from the traditional operational expenditure (OPEX) model of purchasing software (whether hosted on-premises or in the cloud) to the OPEX model of SaaS.
The mobility of workloads is accelerating and is, once again, being dramatically impacted as we move into the world of serverless architecture.
This switches our purchasing model to simply paying for what we consume, without overheads, while at the same time providing us with scalability and high-availability. However, serverless workloads also create more and more silos, adding complexity and reducing visibility. Therefore, it is vital to implement a workload automation solution that can support and scale along with these evolving environments.
Looking into the future, the concept of scheduling will change. The automation platform will make the decision about when events should commence ‒ based on policies, available resources and conflicts on the systems with the aim of delivering results to the business as and when they are required.
We are also at the tip of the iceberg when it comes to realising how new technology might affect the landscape. Recently, we have seen how blockchains are disrupting the status quo, and the necessity for automating the integration between them and the outside world has already become apparent.
So, what’s the bottom line?
While the Internet of things, big data and cloud computing have all meant a massive increase in the velocity and volume of business processes, the next major step will be artificial intelligence (AI).
In recent years, there has been a race by some organisations to try and commercialise AI, but as with all tech evolution, a better approach would be to first understand what it can bring and then apply it to a use case.
The companies that embrace this strategy across their future automation policies will be the big winners ‒ and in the long run, winners will commercialise the results.
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