Three must-have accelerators to drive your automation efforts
It’s widely accepted that automation can bring about a 40% to 60% effort reduction in application and infrastructure maintenance – and 60% to 80% in business services and testing.
But despite all the positive analyst reviews and media predictions I see every day, the reality just isn’t living up to the hype.
I’ve found that managers and stakeholders behind the systems are active in coercing their teams to accept and react to the reality of rapid change that automation efforts bring. But in the majority of cases, the process of automation takes more time for many different reasons. These range from validating the business case, technical security clearance, and deploying automation scripts and tools in the production environment.
So how do you get around this and guarantee the success of your automation?
How do you remove or reduce the negative impact these bottlenecks, increase the speed of your automation efforts, and start to reap the benefits of huge numbers in effort reduction?
I’m convinced that the answer here lies in correctly implementing these three key accelerators:
- Automation DevOps model
- Automation design thinking teams
- Automation skill development
Automation DevOps model – Increase control and efficiency
In automation, we identify manual service delivery areas and automate them. This means that automation is a software development project consisting of requirements, design, development, testing, deployment and maintenance.
Your automation projects require appropriate coding guidelines, test design and continuous deployments. With adequate version control, code management and reusability, you can achieve huge gains in efficiency. So adopting the right DevOps platform is essential for faster, cheaper and better service delivery.
Application Maintenance (AM), Cloud and Infrastructure Services (CIS), Testing and Business Services (BSv) teams are supposed to receive automation service from AD teams with specialized DevOps skills – but I’ve found that this is not actually happening in practice. Teams try to mobilize their skills and automate, but this results in pockets of automation. This not only affects your overall automation speed, but it also fails to motivate your teams to deliver faster automation results and success.
Putting the “Dev” in Development – Your DevOps model needs one clear vision
Several RPA and ITPA tool vendors cater to business process and IT support teams without proper onboarding of the DevOps development approach. Business process and IT support teams are automating simple functions with enormous effort without understanding the end game plan – Development. So the key to a successful Devops model lies in aligning your vendors and teams to create one development vision.
Automation design thinking teams – Your foundation for developing agile automation scripts
Agile development has matured over the past ten years. However, the rapid communication between users and developers has resulted in decreased focus on design, as well as lower code quality and maintenance. While architects are a big part of agile development teams, it’s clear that little time is spent on design.
Design thinking = Design quality from the bottom up
To put innovative ideas into place in the cognitive cloud, researchers use a design thinking approach for quick, quality products. Design thinking demands a quick and thorough understanding of customer requirements with the help of a tangible prototype and a few conversations with the customer before implementation. To guarantee quality, agile solutions from the bottom up, your automation implementation team must use a design thinking approach to develop automation scripts utilizing agile methods on your DevOps platform.
Automation skill development – Giving the right people the right skills
I’ve found that when it comes to candidates for automation, 25% to 30% are simple tasks that can be automated using scripts like Perl, Python or R. For example, application maintenance, report generation, server restarts, password resets, and shutting down long running processes, can be automated by using scripts.
However, reprocessing of failed orders is a complex task. There may be hundreds of checks to perform within the transaction. You need to compare with the reference data retrieved from a database before correcting the transaction. This requires an orchestrator tool that has a developer studio with a drag and drop facility and a powerful scheduler.
You can choose from popular orchestrators such as ServiceNOW, BMC Attrium and HPOO. But in Business Services, the loan approval process, account closure and insurance claim procedures are complex in nature. So they’re automated using RPA tools such as BluePrism, UIPath, Automation Anywhere, etc. Artificial-Intelligence-based automation is performed to understand structured and unstructured data and convert them into actionable intelligence you can use.
Creating an automation training plan that works
I know that as automation gains momentum, the demand for the above skills will only increase. In fact, the next two years will result in 25% of team members developing and maintaining automation scripts and systems. So you should strongly consider creating a plan for specialized training sessions with hands-on modules to meet this demand head-on.
DevOps, design thinking and skills development – Your automation keys to effort reduction
We know automation adoption is increasing at a rapid speed in almost every industry segment as the next wave of modernization and optimization expands. The volume of work in automation is enormous and every delay impacts your customers in terms of cost and quality.
In order to accelerate your automation implementation, it’s crucial to focus on developing the required skills and utilize design thinking to create tangible designs. You can then implement these skills and designs within your DevOps platform.
I know this seems like a very complex undertaking, but these three key accelerators form the pillars of an exciting journey towards a new world where machine intelligence augments human work, as machines can now react faster and process more inputs than humans. And the benefits that your business and customers reap from this will only multiply.