When it comes to the ever-persistent build-versus-buy debate, the “buy” decision is becoming a more obvious choice for many firms within their digitization journeys. That’s particularly true for smaller organizations with fewer resources and a lack of internal expertise to develop proprietary apps and other solutions.
But procuring third-party solutions has its downsides. The adoption of multiple platforms is giving rise to so-called “app fatigue,” and the challenge of integrating these technologies with each other is not always easily overcome. It’s one of the largest drivers of organizations that choose to go the “build” route.
In an effort to lower the barriers for businesses to develop their own tools, some technology companies are turning toward low-code and no-code interfaces that offer the building blocks and user experience necessary for firms to create solutions that fit their needs and seamlessly integrate with existing infrastructure. Sameet Gupte, CEO of EvoluteIQ, recently explained to PYMNTS how this strategy can support what he describes as “hyperautomation,” with potentially significant benefits for financial workflows in areas like accounts payable and accounts receivable.
Surmounting The Data Hurdle
Data integration is foundational to achieving an optimal level of automation in any workflow in the enterprise. As such, any proprietary applications a company designs must be able to aggregate the appropriate data, understand and analyze it, and integrate that information into other back-end systems.
This is a tall order for businesses that lack data scientists on their teams.
“Enterprises have many silos, from data to legacy applications to how automation initiatives are run,” explained Gupte. “As an example, RPA [robotics process automation] projects are run as a parallel stream and don’t tap into the APIs or other integrations with enterprise systems.”
Unstructured data is another key barrier, with vital information locked inside physical documents, emails, contracts and other formats of information.
In order to position itself to create custom hyperautomated apps, businesses first need to break down these silos and bridge “fragmented technology landscapes,” he added.
With a focus on addressing these data pain points, EvoluteIQ connects businesses to technology designed for “citizen users” — that is, end users that are not data analytics by specialization. Its e.IQ platform implements features like drag-and-drop capabilities and a low- and no-code interface to make the process easier for everyday professionals.
Also key to overcoming the data hurdle is its adoption of blockchain technology, a tool whose potential lies in its “asset tracking and data immutability capabilities,” as Gupte explained, as well as other technologies with sophisticated data management capabilities including RPA, artificial intelligence and machine learning.
Driving Finance Automation
Once an enterprise has overcome the data hurdle, the process of building custom apps and automated workflows can be applied to a variety of use cases. Adoption in the finance department is among the most promising thanks to the continuation of data-related challenges that accounts payable and accounts receivable departments continue to face.
Gupte pointed to use cases like a continuous audit of the order-to-cash and procure-to-pay workflows as one example of how hyper-automation can add value to the enterprise. Data-driven automation processes can also optimize billing and cash flow management, he said, while there is also significant opportunity for financial institutions themselves to deploy technology to drive automation and optimization in the back office.
“Data and money are synonymous today,” noted Gupte. “At a certain level, the core ability to process payments is getting into the utility model. The real value-add for financial institutions lies in how they are able to use the data they have to drive superior customer experiences.”
Proprietary apps have the ability to tackle unique and specific pain points for organizations and financial institutions, but it’s only when those apps are able to optimize data through automation and integration that entities can maximize the value of their custom solutions. By breaking down the barriers of usability for “citizen users,” the enterprise can unlock the opportunities to apply real-time data analytics and automated workflows, whether in AP/AR departments, or across the back office.