What is Hyper-Automation?

Hyper-automation refers to an advanced approach towards automation, where businesses leverage a combination of tools, technologies, and platforms to automate as many business and IT processes as possible. This concept extends beyond traditional automation by incorporating advanced technologies like artificial intelligence (AI), machine learning (ML), robotic process automation (RPA), and other emerging technologies to enhance decision-making processes and automate tasks that were previously thought to require human intervention.

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The background context for hyper-automation lies in the evolving needs of businesses to increase efficiency, reduce errors, and respond more swiftly to market changes. Traditional automation could handle repetitive, rule-based tasks, but the complexity and variability of many business processes limited its application. With advancements in AI and ML, it became possible to automate more complex tasks, including those requiring decision-making that could adapt to changing information.

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Hyper-automation assumes that almost any business process can be automated, at least in part. This includes not only simple tasks but also processes that involve decision-making and adaptation based on new data. It aims to create a digital twin of the organisation, a virtual model that reflects the organisation in real-time and can be used for analysis, simulation, and decision support.

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The step-by-step thinking behind hyper-automation involves several key components:

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1. Identification of automation opportunities: Businesses need to evaluate their processes to identify which ones can benefit from automation, considering not only the potential for efficiency gains but also the complexity of implementation and the return on investment.

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2. Selection of appropriate technologies: Depending on the process, different technologies may be more suitable. For example, RPA is great for repetitive tasks that don't change often, while AI and ML are necessary for processes that require adaptation and learning from new data.

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3. Integration and orchestration: Hyper-automation requires these technologies to work together seamlessly. This means not only integrating them at a technical level but also ensuring that they can exchange data and trigger actions in a coordinated way.

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4. Continuous improvement: As these automated systems operate, they generate data that can be used to improve their performance. Machine learning models, for example, can be retrained on new data to make better decisions.

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The rationale behind hyper-automation is not just to reduce costs or save time but also to enhance agility, enabling businesses to respond more effectively to opportunities and challenges. It also aims to free up human workers from mundane tasks, allowing them to focus on more strategic, creative, or complex problem-solving activities.

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Hyper-automation represents a comprehensive and strategic approach to maximising the potential of automation technologies within an organisation. It involves not just the application of technology but also a change in mindset, embracing continuous improvement and innovation to transform business processes.