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  • Writer's pictureAnthony Bosisto

Deploying RPA in under 6 weeks (Part 2)

Updated: Aug 15, 2019

It is my strongly held view that if you can’t develop and deploy a robot in under 6 weeks then you should look at other alternatives to solve the problem.

For those new to the subject of Robotic Process Automation (RPA) it involves the use of specialised software to automate repeatable and predictable computer based processes performed by humans. RPA is often less expensive and quicker to deploy than traditional systems integration as it works with the user interfaces of your existing IT systems.

In this series of blogs I am presenting tips for deploying your robots in under 6 weeks. Tip of the week : Apply the Pareto principle The Pareto principle (aka the 80/20 rule) states that, for many events, roughly 80% of the effects come from 20% of the causes.

What this implies for an RPA project is that you can usually deliver 80% of the functionality with only 20% of the effort. To illustrate how this applies let me give an example:

In a credit approval process an applicant submits an online form for a personal loan to fund their holiday. The credit officer manually transfers the financials from the form to a credit calculator and does a basic credit check. For 20% of customers the result will be inconclusive so the process will require a more advanced review of bank statements and payslips.

To automate the whole process would be a lengthy project involving cognitive interpretation of varying formats of payslips and bank statements. Automating the basic credit check however is a much smaller project that is easily achievable with simple RPA scripting. By delivering a solution that covers 80% of the volume your business benefits are realised earlier, staff are freed up to work on more complex tasks and credibility is gained with stakeholders.

In a real world example the choice will not always be so simple however you should always be applying the pareto principal. Most processes have exceptions that require human discretion and add complexity. My experience is that you are better to leave the complexity for humans to solve and let robots do what they do best. Following simple instructions and never getting tired or making mistakes.

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