How to Alleviate RPA Implementation Headaches with Low-Code Development

Alleviating RPA implementation headaches with low-code development

The rise of Robotic Process Automation (RPA) has ushered in promises for faster, more efficient workflows with cost savings for companies of all sizes.

Business and IT teams have acquired numerous legacy solutions over the years and now require additional staffing to massage data and set up laborious integrations. With RPA, headlines of increased productivity, integrated legacy technologies, and reduced bottom lines dazzle executives everywhere.

So what’s not to love? Perhaps it’s the reality that the implementation, execution, and maintenance of RPA solutions require even more staff and resources to make it all happen.

What is Robotic Process Automation (RPA)?

Deloitte defines RPA as software that “automates repetitive, rules-based processes usually performed by people sitting in front of computers.”

Picture your mouse automatically scanning your email for 70 new unread invoices, adding the data to a spreadsheet, and inputting information into your CRM, while sending two outliers to an employee for manual review – all within a fraction of the time it would take a person to do the same tasks and with far fewer errors.

RPA workflows are established on logic-based inputs and tasks across applications for the bot to efficiently carry out manual, repetitive tasks with greater accuracy.

Additionally, by separating uniquely human skills like critical thinking, empathy, and decision making from manual, repetitive tasks, corporations can provide a more fulfilling and rewarding career for their employees.

Sounds great, right? Of course, it does.

That’s why it’s the fastest-growing market in enterprise software, with 48% of companies saying they are planning to invest in RPA and is projected to be worth nearly USD 4B by 2025. Corporations across industries are buying in to streamline a wide variety of operational tasks, connect legacy systems, and drastically remove errors introduced by humans. Operations that can benefit from RPA technology include:

  • Generic office tasks – gathering quarterly cross-department data into an excel sheet, automating CRM inputs, and inventory management.
  • Back office processes – instead of five people checking for new orders and applying discounts, the tasks are reorganized so the employee is providing a human-level of validation to the order.
  • Manufacturing – order fulfillment, purchase order processing, and transportation and inventory management.
  • Retail – product categorization, automated checkout, and delivery tracking.
  • Customer service – credit checks, account number assignment, and activation tasks can be allocated to bots and employees can speak to a customer and apply empathy and discernment to the situation at hand.

But are RPA implementations actually effective?

Spoiler alert: reality doesn’t always deliver as promised.

According to KPMG, 55% of companies deploying RPA aren’t making significant progress. The top challenges to undertaking technology initiatives for the past three years have been dysfunctional or fragmented processes, lack of skilled talent, inadequate change management, and inadequate IT systems. Executives dazzled by the potential of RPA aren’t always taking into account the full costs of implementation and it’s impacting program success.

The goal of RPA is to streamline manual tasks across applications, however, it’s not necessarily guaranteed the applications can effectively talk to each other or that the bots can navigate the interfaces as easily as a human. Additional engineers and developers are needed to plan and implement RPA across legacy and 3rd party systems which can result in patchwork and complex integrations if they even integrate at all. Sometimes customized UI coding is needed for the bot to effectively operate across platforms and there’s continual legacy system and infrastructure maintenance. And then there’s confusion about who actually owns the RPA process – is it IT or the business unit?

Executives search for additional help through staffing and consulting firms, but even then, there aren’t enough RPA advisors and engineers to adequately support companies. Ultimately, corporations that implement RPA to cut costs can end up spending unexpected budget in implementation and operational staff, resulting in negligible budget savings (if any at all).

Low-code is the glue for RPA implementations

Here’s where low-code development can save the day.

Low-code platforms enable cross-functional teams of professional developers, citizen developers, and functional staff to easily collaborate and connect multiple applications for end-to-end solutions.

Because the platforms are built on open standards and are cloud-native, they can easily connect internal legacy and third-party applications in a bot-friendly interface. And they can quickly establish bot workflows that model real business processes. Enterprise RPA initiatives can get off the ground in a fraction of the time without bringing on additional staff and infrastructure.

What does low-code and RPA implementation success look like in real life? Just ask Avertra and 2 Sisters Food Group.

Avertra provides technology and consulting solutions for telecom and utility companies, including a modular digital customer experience framework built with the Mendix ecosystem and integrated via API with enterprise solutions like ERP systems, work management applications, and external data sources.

Alongside their clients, Avertra establishes which processes to automate, builds user stories, and deploys bots which then follow workflows, transfer data between systems, select appropriate resolution paths, and follow through with documentation and compliance – all within a fraction of the time it takes an individual agent.

Meanwhile, UK poultry supplier 2 Sisters used low-code to implement RPA across 11 accounting transactional processes, moving from 100% manual work to 97% automated within six weeks. They used Mendix to build a data-structuring application that extracts, parses and cleans the data.

2 Sisters was able to reduce their customer invoice verification process from 65% of invoices needing manual data verification to only 8%. Manual data entry was nearly eliminated, save for a few outliers identified by the bots, and employees have more time to analyze the data and costs.

Low-code enables both technical and non-technical users to play an active role in implementing and maintaining RPA initiatives, taking the burden off of the IT team, operating securely within their infrastructure and parameters, and reducing the need for additional developers.

Avertra empowered their client’s citizen developers to make workflow iterations in the Mendix platform based on data results and their internal business knowledge. With the assistance of Mendix partner AuraQ, 2 Sisters built 300 unique customer remittance templates in 3 months and over 3,000 have been created to date (and they’re still going).

The beauty of low-code platforms is that applications can be easily adjusted as the business evolves, RPA technology improves, and new automation opportunities are identified, enabling companies to be more agile and competitive.

Avertra’s clients have used data insights to produce new and revised resolution paths addressing outlying issues not caught by the RPA framework and 2 Sisters is now analyzing their data to identify their next digital transformation target. Their investments in RPA implementation and low-code development have quickly paid off and will continue to return dividends in the months and years to come.

Headache alleviated.