“Through 2021, 40% of enterprises will have RPA buyer’s remorse due to misaligned, siloed usage due to inability to scale.” – 2020 Gartner Magic Quadrant for RPA
Robotic process automation (RPA) is an emerging technology that replicates business processes to improve accuracy and/or relieve human involvement. It has become more prevalent and an integral part of digital transformation initiatives accelerated by the pandemic.
Due to the demands for enhanced RPA capabilities, RPA must be complemented by other technologies as a part of a comprehensive “hyperautomation” strategy designed to help organizations iteratively streamline and automate qualified processes. One such complementary technology is data preparation and its role in driving increased value in RPA investments and reducing the risk to avoid buyer’s remorse.
“By 2022, 80% of RPA-centric automation implementation will derive their value from complementary technologies.” – 2020 Gartner Magic Quadrant for RPA
RPA Processes Rely on Data
At the heart of most RPA processes is data, the strategic asset that gives organizations a competitive advantage provided it is accurate, managed judiciously and used strategically. Here are the 3 most common types of RPA processes that rely on data.
- Integration via application interface: This is common with the need to enter data into certain fields on legacy applications like the mainframe for use cases like closing accounts or adding notes to existing accounts. Examples include matching and reconciling data between multiple systems, where the means of data access (retrieval or input) are the application front end or unstructured data sources like reports (text, pdf).
- Large scale data migration: A typical scenario is the need to migrate data from a legacy enterprise resource planning (ERP) system into a new one, or a new loan servicing platform, or a new electronic health record platform. An important aspect of this approach is the need to gather, analyze, filter, and clean the most relevant data to be migrated at scale.
- Enable information workers: This includes providing insurance case workers with timely data in the context of a claim case, or frontline retail associate with current inventory levels.
Data Preparation Enhances RPA
As organizations continue to invest in RPA, a complementary data prep solution such as Altair Monarch™ provides the ability to justify the investment, determine the total cost of ownership and the overall value of the solution.
Through our partnership with RPA vendors like Automation Anywhere, Blue Prism, Bank RPA, Amdosoft Systems and others, Altair is helping our customers more efficiently prepare their data for pre- and post-RPA processes.
“Clean and well-structured data is important to increase the value of an organization’s RPA investment. Our partnership with Altair can add significant strategic value in helping businesses advance their RPA initiatives,” said Griffin Pickard, Director, Technology Alliance Program, Automation Anywhere.
Altair Monarch enables an agile and iterative process of acquiring, cleaning, and transforming data into a trustworthy and consumable format that complements RPA for the following reasons:
Variety of data sources: One of the challenges for RPA tools is that the data is not often well formatted for the bots to run a process. As a result, more time could be spent trying to gather and format the data before a bot can run. Data prep empowers business and IT end-users to access data from a wide variety of traditional data sources such as Excel, CSV, and databases, as well as semi-structured data sources such as pdf, text, html, json, xml, etc. With data prep the acquisition and cleansing process is more streamlined and scalable, allowing the RPA tool to focus on its own competitive advantage.
Data quality: RPA processes that are based on poor-quality data significantly increase the risk the buyer’s remorse via rework, resource drain (time, money, talent), and poor employee experience. Data prep tools facilitate an easy business context review of data quality for missing values, nulls, duplicate items, etc.
Ease of use: Monarch is an easy to use data prep tool. Native drag and drop features, and no-code menus drive data prep functions to speed up time to insight, and the time it takes to produce well formatted data for RPA bots to consume.
This demo illustrates the integration between Altair Monarch and an RPA tool. If you have an RPA solution or work with any of our RPA partners would like to learn more about the integration and how Altair can help, please complete this form and someone from our team will contact you.