Why Automation is all about the DATA and not RPA.

Effective intelligent automation tooling enables firms to obtain, move and transform data at an unimaginable speed. This data can then be used to derive outsized value for organizations.

When businesses start out using intelligent automation technologies, they inevitably make mistakes by focusing on the wrong things. For example, RPA is often seen as the new and shiny tool that can ‘digitally transform’ an organization.?

When used correctly, Robotic Process Automation (RPA) is a fantastic tool, that uses software robots or bots, to complete back-office tasks, such as extracting data or filling out forms.

?Organizations quickly learn that they need Intelligent Automation tools and analytics to complete more complex end-to-end automation e.g., improving decision-making processes, improving compliance, or evaluating and monitoring process data on an ongoing basis to reduce customer friction and business cost.

Four core intelligent automation analytical capabilities play a vital role in automating entire business processes, such as order to cash or purchase to pay.

1.??Execution analytics allows computing programs to type, click, open applications, or send emails through low-code platforms and robotic process automation i.e., the ‘hands and legs.

2.??Vision analytics use programs such as sensors or cameras that capture images i.e., the ‘eyes’. Vision analytics uses machine learning to identify and classify objects in images and then act upon that visual information.

3.??Language analytics enables machines to understand and respond to human language i.e., the ‘voice’. For example, chatbots use natural language processing (NLP) to interpret and act on voice analytics.

4.??Machine learning analytics enables computers to think, learn, analyze, predict, make decisions, and improve over time i.e., the ‘brain’.

Organizations that combine these four analytical capabilities with RPA have the data and directional insight they need to handle more complex tasks and use cases. And as a result, those organizations generate exponential process, productivity, profit, and cost improvements over time compared to their peers.

While removing mundane work from employees’ daily duties is an admiral goal it should not be the goal organizations focus their automation programs on

.Progressive organizations have learned to focus on the liquid gold that flows through their digital operations i.e., their data analytics; and to combine that with RPA to generate outsized returns.?

Intelligent automation makes things faster and more efficient, but good-quality data is the most critical component of any smart automation program. Good data input results in automation output.

Conversely, lousy data input usually has bad automation results.

By using machine learning and complex algorithms to analyze structured and unstructured data, organizations can develop a knowledge base and formulate predictions based on that data. This then becomes the decision engine of any intelligent automation program.

Organizations that generate, orchestrate, and transform data, and then turn it into new forms of economic value or actionable decision insights are winning in the fourth industrial revolution.

For more information on how we can support your risk-free with your Intelligent Automation program, reach out to?IAC.ai - Intelligent Automation ?today at [email protected].