Build a digital ops toolbox to streamline business processes with hyperautomation

Reliance on Singles Technology as a lifeline is now a futile battle. When simple automation no longer does the trick, delivering end-to-end automation requires a combination of complementary technologies that can reshape business processes: the digital operations toolbox.

According to a McKinsey surveyEnterprises that have been successful in their digital transformation efforts have adopted sophisticated technologies such as artificial intelligence, the Internet of Things or machine learning. Enterprises can achieve hyperautomation with Digital Ops Toolbox, the centerpiece of your digital operations.

The hyperautomation market is growing: analysts predict it will reach approximately $860 billion by 2025.

Toolbox is a synchronous blend of Intelligent Business Process Management (IBPM), Robotic Process Automation (RPA), Process Mining, Low Code, Artificial Intelligence (AI), Machine Learning (ML) and a Rules Engine. Technologies can be optimally combined to achieve Key Performance Indicators (KPIs) of the organization through hyperautomation.

Hyperautomation market is growing: analysts predict it will reach by 2025 about $860 billion. Let’s see why.

Purpose of Digital Ops Toolbox

Toolbox, it’s wealth of technologies, helps in three important aspects: process automation, orchestration and intelligence.

process automation: A hyperautomation mindset introduces the world of “automating whatever it can be”, be it a process or a task. If something can be controlled by bots or other technologies, it should be.

musical instrumentHyperAutomation: Adds an orchestration layer to simple automation. Technologies such as intelligent business process management streamline the entire process.

wisdomMachines can automate repetitive tasks, but they lack the decision-making abilities of humans. And, to achieve a perfect harmony where machines are made to “think and act” or to acquire cognitive skills, we need AI. The combination of AI, ML and natural language processing algorithms with analysis drives simple automation to become more cognitive. Instead of following if-then rules, technologies help gather insights from data. Decision making ability enables the bot to make decisions.

Simple Automation vs HyperAutomation

Here is the story of evolution from simple automation to hyperautomation with an example: the order-to-cache process.

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