Robotic Process Automation (RPA) Analytics with Eagle Insight

Businesses are transforming, there’s no stopping that. Driving this transformation are robotics and automation by helping make manual operations more skill-centric, value-based, and efficient. The COVID-19 pandemic has only fast-tracked the adoption of these inevitable technologies.

Robotic Process Automation (RPA) aims to take over the dreary, mundane tasks that consume a significant part of an average employee’s workday. By shipping off these tasks to the RPA platforms, employers enable employees to focus on value creation and increase productivity.

In RPA, efficiency is not compromised, tiredness is not a factor, and accuracy is unwavering. But as the technology is still taking baby steps, there is room for improvement. This is where data and analytics come in.

More than ever before, the ability to collect, organize, manage, and analyze data has become paramount. But with the rapid rise of automation, most companies are behind the eight ball in learning from automation-related data. According to a Harvard Business Review report, more than 70% of employees are inundated with data that is not relevant to them, and four in five data analysts waste time trying to discover and assimilate relevant data.

 

How Can Post Robotic Process Automation Analytics Supercharge Your Organisation’s Strategy and Planning?

 

A sturdy RPA analytics engine allows your business to achieve transformative outcomes by actively quantifying your automation benefits and demonstrating the areas of weakness. When automation is supported by intelligent analytics, the organization can maximize the benefits of the new technology and optimize the entire automated process.

 

Post automation analytics can unlock efficiency and enable quicker and smarter decision making, helping uncover new insights around your organization’s automation ecosystem and how to enable it to solve more meaningful problems. 

 

It allows for accurate forecasting, extending beyond the usual fiscal and performance revisionary methods. For forecasts to be useful, they must consider different variances and their impact. It must analyze how the variance impacts the overall target, different KPIs, timeline, costs, and process. This information provides the decision-makers with actionable insights.

 

Forecast vs actuals allows companies to also understand how predictions fare at different forecast points and help zero in on the optimal timeline for future forecasts. 

 

What are the Business Benefits of Post Automation Analytics?

 

Even as far as five years ago, the benefits of adopting automation included up to 200% return on investment, according to McKinsey. Effective Robotic Process Automation analysis can help sustain and/or improve the end-to-end automation process in your organization and increase the ROI.

 

Tracking down, analyzing, and expounding RPA data can help you understand whether the investment in RPA is paying off. Thanks to automation, various silos of data can be merged or converted into actionable insights that help optimize ROI and Net Present Value (NPV).

 

Advanced analytics can open your eyes to huge cost-saving measures and enhanced business intelligence. For example, you can predict buying and spending patterns based on historical data to better strategize and improve cash inflow. The forecasts can also enable greater process optimization by removing manual efforts.

 

How to Optimise Your RPA Analytics?

 

A recent Gartner report stated that by the end of 2022, RPA will be prevalent in some form in at least 85% of the big firms. That’s a significant achievement for RPA, but it still needs to be deployed and used effectively. 

Every metric to measure its success should tell a story about what your company wants to achieve. If it does not, then the metric needs a rethink. 

 

Aspects like robot productivity, velocity or time taken for automated processes to execute, utilization, process throughput, and real-time health help define optimal efficiency and success. Companies can clearly gauge process exceptions, process volume, queue, utilization, expected business value, and ROI. 



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