How RPA helps when one software doesn’t talk to the other

CHASING digital transformation has taught businesses that automation is critical in this day and age.

It helps reduce human errors, increase efficiencies, lower costs, and create more room for professionals to focus on what matters most — the customer.

However, automation isn’t an easy thing to achieve, and it’s not because organizations don’t have the skills, talent, resources, or capabilities necessary to pursue automation across its different business units.

The reality is that in most cases, a prerequisite for setting up and configuring automation loops is that all software required to perform the task must be integrated in some way. Meaning to say, they must talk to one another.

Traditional software has been developed in silos, either in-house or by different software vendors who are leaders in their own area of specialty. As a result, organizations find that they’re stuck with great applications that don’t talk to one another and hence cannot be automated.

In the long-run, companies might need to migrate to a product suite that’s more robust or wait for vendors to collaborate in order to develop and offer suitable integrations, at least for products lines that don’t compete with one another.

The immediate solution, however, is RPA, short for robotic process automation.

Think of it as a macro that you record on a spreadsheet to perform a series of tasks in the way that you would normally perform them, all done quickly and sequentially.

RPA is the magic tool that bridges the gap between two or more pieces of software that aren’t integrated, have no way of talking to one another, and cannot be linked up in any way.

It’s the perfect tool for organizations with legacy infrastructure to make the leap to new-age products and services for front-end applications without disrupting reliable core business services.

According to a recent note by KPMG, organizations that ignore RPA face a daunting task when it comes to building business automation solutions, often stalling their entire digital transformation as a result.

The think tank evaluated a large insurer’s recent use of RPA to integrate legacy systems and found that consolidating front and back office teams into a single customer service team resulted in 9x acceleration of service processes and a 40 percent reduction in service cost.

The insurer achieved all that without the headaches of building integration points into the legacy systems and managing disparate mainframes and database systems — all because it was willing to give RPA a shot.

To be honest, what one large insurer achieved can be achieved by any organization willing to experiment with RPA. However, it’s probably important to mention that for any business relying on RPA as a way to integrate different pieces of software, governance must be top of mind.

Governance is key to most RPA projects that support digital transformation because the system is designed to carry out a job in the way that it has been taught. It follows the set of tasks as they have been programmed — but that doesn’t take into account two important things — efficiency overhauls and marginal breakdowns.

When an RPA system is being implemented, it might be taught to do something based on a benchmark set by a model employee. This might be good for the short run but doesn’t guarantee that the way that the job is being done is the most efficient.

That’s what governance is for. In the RPA governance function, organizations use data to understand the job that is being performed, lags in the different legs and series of the tasks being performed, and the overall efficiency.

This is where the team can exercise their creativity to find better ways to do the task and get more out of the RPA solution.

The other function that an effective RPA governance tool performs is providing real-time intelligence on RPA solutions that fail to execute and deliver an expected result.

Obviously, this is incredibly important for businesses that built on the results that RPA tools generate by joining disparate systems together — and it seems entirely logical when you think about it.

Despite that, organizations tend to forget about it when actually scaling up their RPA solutions enterprise-wide to support bigger digital transformation projects. Neglecting RPA governance, however, is not an option.

Businesses, irrespective of size, that are looking to get started with workflow automation but struggling to piece together different pieces of software must definitely think about RPA.

However, to get the most out of their RPA bots, organizations must not neglect building in some sort of RPA governance practices before they scale up and build other digital transformation capabilities on top of the output that the solution produces.

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