Guide to Business Process Automation

Although business process automation is constantly gaining recognition, crucial data-driven processes such as manual data mining, reviewing and data input still exist in most companies. Those tasks consume lots of time,are error-prone and ineffective. This is a perfect scenario for robotic process automation

Those tasks are completed manually and require staff to login in and out of multiple internal and external systems and transfer data between different formats. The data is further checked and analyzed by employees and if we are completely honest their time could be spent with greater value. Not only is this job mundane and boring it is also a remarkably inefficient and inaccurate process, compared to RPA. It can be tricky here to distinguish which is a task and which is a process – in fact, it is interesting to see that on occasion, the terms appear to be used somewhat interchangeably. You can take a look at Task vs Processes: Are they Actually Different? for more clarity on this subject.

The Rise of Automation

Complete business process automation is hard to achieve due to technology limitations. Almost every business includes activities that haven”t been automated yet. Those activities are performed by human operators and require initial data input as well as, re-keying and copy/pasting data between multiple systems.

Drawbacks of Manual Processing

• Low productivity: Even the highest-skilled workers can”t compete with robots in productivity. Despite the talks, we all need food, a rest, and vacations
• Poor customer experience: Inefficient processes can create a domino effect that will affect all areas of Your business including customer service
• Expensive: Highly repetitive work steals precious time from the staff that could spend on highly skilled or creative tasks.
• Lack of security: In the enterprise level companies, the ability of humans to bend the rules and implement insecure shortcuts under pressure is definitely not a good thing
• Work style diversity: Work style difference of hundreds of workers and up as a huge standardization headache. Manual processes are very inconsistent when we talk about exception handling or file naming
• Learning curve: New employees require the adaptation period and a dedicated guide. When the manual tasks depend on human it is very cumbersome to scale rapidly

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So What is RPA?

Robotic process automation is the application of technology that mimics specific actions of an employee on a computer. This includes interacting with web portals, enterprise applications, websites, emails, Excel, legacy systems and more.

Identifying automation opportunities

Are you familiar with all pain points in Your companies business processes? Where does Your staff have big backlogs? Do You know the stage in Your processes where the error rate exceeds the threshold? Is ERP Integration with external apps and services vital? Those are the examples of the areas where RPA makes sense to apply.

Virtually any process that uses a structured or unstructured data streams has an opportunity for RPA to increase efficiency. You should keep in mind though that automation applied to sloppy processes only multiplies the sloppiness. It is vital for the business processes to be perfected before the adoption of robotic process automation

The Potential impact?

Perfect Accuracy: Data entry with no human error

Scalability: Seamless handling of seasonal volume peaks

Round the clock productivity: No vacations, no fatigue, no personal problems

Compliance: Robots don’t miss a step and will leave a digital audit trail

Any real alternatives?

The way You treat automation of repetitive tasks in Your company has the real impact on the bottom line processes. Because of the rapidly changing business needs, traditional automation approaches almost never produce a perfect outcome.

Here are two real-world alternatives to RPA with their main drawbacks:

• Outsourcing or offshoring – Amount of human errors isn”t reduced
• Rebuilding current technology – Requires months of planning and coding spent on development