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While Robotic Process Automation (RPA) is a relatively new market in the world of technology, enterprise organizations have been automating labor-intensive IT processes for many years. In this article, I share how RPA can now address the ultimate frontier of enterprise IT — the mainframe.
RPA and IT: A brief history
Every day, evolving technology simplifies the enterprise computer user’s work. For example, we already use scripts that automatically log into an application, regularly generate complex reports on a cadence, and automate large batch jobs in the middle of the night when the network is less busy.
Some technologies have taken what’s “possible” to the next level, moving from a macro that automates a short process in a single application to automating a complicated business process from end-to-end by orchestrating the exchange of data between desktop, web, and other applications. Enter Robotic Process Automation, or RPA.
RPA is a practical, non-invasive way to automate enterprise processes. Using software “robots” to perform everyday tasks boosts productivity, while preserving underlying applications and IT infrastructures. Robots interact with applications and systems as we do, but are faster, more accurate, and highly secure. They save time, reduce costs, and free employees to work on other projects.
Recently Dimension Research identified early RPA successes, with 89% of companies citing “extremely” or “mostly” successful RPA projects, and that “nearly all” RPA implementations reduce time and costs. Gartner agrees. Their latest forecast projects global RPA software revenue to reach $1.89 billion this year, a 19.5% increase from 2020. Further, Deloitte’s recent RPA survey observes that 53% of the respondents “have already embarked on the RPA journey” and a further 19% of respondents “plan to adopt RPA in the next two years.” So, if your organization is not already using RPA, it is likely to start doing so soon.
Next steps: RPA and the mainframe
With so much important business data housed on the mainframe, it is logical to leverage the mainframe for RPA initiatives. But accessing mainframe data can be more complicated. Since this data is business critical, utilizing RPA with the mainframe must be done right.
Involving your mainframe team in the process matters, as they understand the specific needs of the platform. Mainframe teams should lead RPA initiatives that involve big iron, as interacting with a desktop- or web-based application is typically straightforward. However, accessing data on host systems typically requires special skills, and technology often referred to as a connector.
Whether integrating via web services or more traditional Application Programming Interfaces (APIs), such as HLLAPI or .NET, developers can find tools to support RPA requirements.
Accessing Mainframe Data
Automating processes to accelerate the speed of business is an ongoing objective for enterprises, which often requires ways for applications to talk to each other. The advent of the internet simplified the process of applications communicating with each other over a common protocol, TCP/IP. IBM’s MQ Series is an example of messaging middleware that has made it easier to integrate applications and key data across platforms for automating business processes and can be used in services-oriented architectures (SOA). More recently, cloud vendors are offering similar capabilities on their platforms while also providing the server infrastructure required.
At least for today, RPA initiatives do not typically require a sophisticated SOA infrastructure to begin automating important business processes. With a large percentage of key business data historically stored on the IBM mainframe, the market has created many ways to programmatically access mainframe data for any process automation initiatives. Terminal emulators using IBM’s HLLAPI standard became the de facto screen-scraping standard that originated with MS-DOS (yes, that DOS!) in the 1980s and morphed into many related automation interfaces, as the Windows operating system and other technologies evolved over the decades — WinHLLAPI, EHLLAPI, OHIO, and many others.
Enabling mainframe RPA comes down to two primary access methods: (1) service-enabling the mainframe and (2) HLLAPI. We also refer to these respectively as API- and UI-based approaches to programmatically access host data.
The first, more scalable method gives RPA developers the ability to create consumable web services that perform units of work in host-based applications. In an automated process, the RPA tool calls on these RESTful web services as needed. We call this “service-enabling the mainframe,” or host.
The alternative is to utilize HLLAPI, the client-based, green-screen data access standard for more than 30 years. In this scenario, the RPA tool leverages HLLAPI to access host data through a terminal emulator and corresponding green screen.
Every major RPA solution on the market supports using this standard interface for mainframe data access. For the HLLAPI-savvy organization, this can be the quickest way to leverage mainframe data in an RPA-based automated process.
The new Host Access for RPA solution from Micro Focus includes technology for both service-enabling the mainframe and screen-scraping via HLLAPI (and similar interfaces, including a .NET API option) from client-based terminal emulators.
Your journey to RPA and the mainframe can start today. Whatever method of RPA you choose, your organization will be able to leverage your business-critical mainframe data in your RPA initiatives. Get started by viewing any of these resources or contacting Micro Focus today:
Image Credit: Photo by Lyman Gerona on Unsplash
Que Mangus manages the product marketing for Micro Focus host connectivity solutions. Que has 14+ years of experience in software solutions marketing and received ITIL version 3 Foundation Certification in 2010. Que graduated from Utah Valley University located in Orem, UT, USA with a Bachelor’s Degree in Business Management.