With the growth of a powerful digital economy worldwide, businesses of all sizes are increasingly investing in onboarding digital solutions. They want to deliver unparalleled experiences to end-users, both customers and employees. But at the core of every major technology they adopt, the underlying transformation is achieved mostly due to automation.

Enterprise automation is often regarded as the foundation of achieving a sustainable digital transformation in any business. Automation delivers the efficiency, responsiveness, and speed required for the digital world.

If manual intensive and biased decision-making tasks remain within the enterprise ecosystem, it will be nearly impossible to achieve digital success. Hence the path to becoming a truly digital-first enterprise requires a strategic adoption of enterprise automation across the length and breadth of the business.

In the post-COVID period, organizations will have to step up their digital adoption game at a pace never seen before. It is estimated that by 2022, there will be nearly USD 596.6 billion spent on technology that enables automation and hyper-automation for enterprises.

The challenge here is that there is a sizeable number of cases where enterprises get their automation initiatives wrong. This could be because of the lack of a clear idea of the stages and possibilities of enterprise automation.

Let’s have a deeper look into how modern business success stories can be woven by getting their enterprise automation initiatives done right.

Identify Candidates for Automation

The first step to take before proceeding with million-dollar automation initiatives is to clearly understand how exactly different technology could work in your business model. This will help you then prioritize functions or modules that need automation according to the impact they make on the smooth functioning of the business. Map out dependencies, business workflows, and processes that have the potential to be affected when a particular business function or process is automated with an automation platform.

Start Small

If your business is relatively new to the digital world, it may be safer to start with automation initiatives that are contained in their scope and controlled in their execution. Depending on how mature your existing business processes are, there is a range of simple automation solutions that you can deploy to quickly realize benefits. Robotic Process Automation or RPA can be a perfect start if you want to transform those boring repetitive and mundane application tasks such as data copying, task scheduling, data consolidation between different systems working on the same project or department, etc. An RPA bot can be programmed to mimic human actions on multiple computers and can easily handle tasks such as copying data from one system location to another or recording logs for activities, etc. This will improve process efficiency and show success to the business stakeholders too.

Scale Up

Once your organization has attained a certain level of digital maturity, then there will be enough volume of transactional and behavioral data that will be available within different departmental systems. This data holds the potential to unlock more hidden value from your business’s operational approach. You could mine that data to uncover inefficiencies and value generators from different patterns of behavior that systems exhibit during customer interactions and workforce utilization. This is the stage where your organization needs to invest in data-driven automation platforms that use big data analytics to generate insights. This could be the foundation for AI and ML initiatives that enable “near-autonomous” actions. These insights can be the source for automating business workflows and processes and streamlining the overall productivity of digital systems within the enterprise.

Orchestrate Data Flows

The next stage after your business has successfully empowered data-driven automation in pilot projects or across the entire technology landscape, is to ensure that data flows are seamless between the integrated or connected systems. Different digital applications within your technology ecosystem or different modules of the same business system need to communicate with each other by exchanging the right information at the right time and in the right order. Only then would enabling an automated workflow to run these systems autonomously yield the desired results. Thus, the next stage after scaling up is to ensure proper orchestration of data between systems and modules to build a highly connected technology ecosystem that will ensure more success for enterprise automation initiatives.

Incorporate Intelligence

When the right systems are automated, sufficient data flow is established and all systems are well interconnected for seamless information and data exchange, your enterprise technology landscape offers an ideal enterprise-wide hyper-automation use-case. As a business, reaching this stage allows you to reap benefits substantially. But technology evolves at a rapid pace and with multiplying complexity. As time passes, your automation efforts would need periodic boosting and reconfiguration of systems to ensure optimal performance. But what if we say that your digital applications can handle this optimization and evolution on their own? By integrating artificial intelligence and machine learning into your enterprise technology landscape, it becomes easy for your enterprise automation initiatives to evolve autonomously on their own.

The stages of enterprise automation covered in this blog don’t require a fixed pattern of adoption strictly. Depending on your organization’s current levels of digital and data flow maturity, you can make a push into any of the stages directly without waiting in line for each stage to complete.

However, it is important to understand the objectives of each of these stages and ensure that your enterprise automation initiatives comply with those objectives irrespective of the roadmap you follow. You will also need to factor in how you acquire, manage, and process the data, as well as how you secure it. Knowing what data is needed and what isn’t is an important decision point. Data management and data governance will need to become focus areas. Get in touch with us to explore how your business can unlock the true potential of enterprise automation with the right progress roadmap tailored for your unique business needs and challenges.