An important question in the realm of digital transformation is whether to employ Robotic Process Automation (RPA) platforms or traditional software development for automating processes. As the VP of Business Transformation at R-Path Automation, I've observed the distinct advantages of RPA in streamlining operations, especially when managed by a dedicated process automation team.
Unlike traditional software development, which excels in building complex systems from scratch, RPA platforms automate existing systems and processes swiftly and cost-effectively.
With that in mind, I’ve mapped out the key reasons why RPA platforms, managed by a specialized team, usually emerge as the superior choice for process automation. I’ll also shed light on the diverging skill sets required for effective process automation and traditional software development.
The primary advantage of using an RPA platform for automation lies in its speed and cost-efficiency compared to crafting custom code. It's like choosing an established CRM system like Salesforce or HubSpot over building a homegrown CRM.
Software platforms (including RPA platforms) provide an organization with a fundamental value proposition: it is much faster, easier, and less expensive to do whatever the platform is purpose-built to do than it would be to build from scratch. The drawback is that trying to use the platform for anything other than those uses will usually be slower, harder, and more expensive – or not possible at all.
Thus, while HubSpot is an excellent choice for CRM, it would be difficult to use it as a project management tool or for collaborative document writing.
RPA platforms are purpose-built to automate processes. When an organization needs to automate either a new or an existing process, an RPA platform will usually be the best tool for the job. It is faster and easier to interact with and automate desktop applications and websites as well as build in business logic using RPA than it is with custom code. RPA platforms can also interact with APIs (application programming interfaces) just as well as custom code can under most circumstances.
When the organization needs to develop a new system, however, custom software development is the better choice – because the RPA platform is purpose-built for something else and not particularly good for systems development.
RPA boasts a suite of ready-made capabilities, enabling development teams to focus more on adding true value and less on redundant efforts. The primary capabilities include:
RPA platforms come with a vast array of pre-built modules, covering a broad spectrum of functionality – including data format conversions, file manipulations, interactions with desktop and web-based user interfaces (UIs), sending email, and engagements with a multitude of third-party application programming interfaces (APIs).
While all of this is possible through custom code aided by open-source libraries, managing homegrown or open-source libraries proves overwhelming, particularly amidst the escalating risks of software supply chain attacks.
Setting aside the issue of managing third-party libraries, the sheer time investment required to develop even a fraction of these modules independently underscores the efficiency, speed, and cost-effectiveness of opting for an RPA platform.
Development teams frequently orchestrate batch processes and scripts using tools like Windows Task Scheduler, PowerShell, or CRON. However, these methodologies have several drawbacks, notably the challenges in managing an extensive array of jobs and the lack of visibility to non-developers.
To mitigate these issues, many teams construct a lightweight user interface (UI) to visualize and administer schedules. Despite that being a feasible solution, it is more practical to utilize the robust, ready-to-deploy scheduling interfaces furnished by RPA platforms, which eliminate the need for additional development time.
Beyond basic scheduling, teams often need to manage queues of scripts or automated jobs. It's important to ensure that should one script overrun its usual execution time, the subsequent script does not initiate concurrently, creating failures or conflicts. Moreover, a common strategy is to distribute demand evenly across multiple servers, optimizing capacity utilization while curtailing infrastructure expenditures.
RPA platforms adeptly navigate these intricate tasks, offering transparency and a level of customization that would demand a substantial investment to replicate in homegrown software solutions.
It is often ideal to build modular scripts that can be combined and reconfigured based on the situation. For instance, there may be a set of jobs that needs to run every night but also needs to run with a few extra steps once a week. Similarly, there may be complex run-time dependencies between different scripts that need to be managed.
When the orchestration rules are embedded within code, comprehending, tracking, modifying, or expanding them becomes a more arduous task. Even setting that aside, it is simply faster to set up the orchestration using the built-in orchestration mechanism that comes with RPA platforms.
If an organization has built its own scheduling, queuing, load balancing, and orchestration mechanisms, it will need to also implement the appropriate permissions and access control mechanisms to secure all scripts, credentials, and underlying systems properly. It will also be necessary to incorporate administrative functionality to define, group, and manage access privileges for various resources among users and groups.
RPA platforms provide plug-and-play interactivity within existing access control systems such as Microsoft Active Directory or Google’s Identity Platform. They also contain built-in access control if an organization wants to handle permissions management within the RPA platform itself.
The amount of time and energy it requires to build homegrown scheduling, queueing, load balancing, orchestration, and permissions management functionality – to say nothing of modular actions and connections to third-party systems – is enormous. Creating from scratch also introduces a variety of security and stability concerns since most development teams do not have the expertise or tools available to ensure the level of security and stability organizations require.
In most cases, leveraging RPA for process automation rather than building automation from scratch will result in many more processes being automated more soundly, in a fraction of the time, and with more control and future flexibility.
RPA platforms empower non-developers like end users, subject matter experts, and business analysts to automate some processes, thereby freeing scarce development capacity for tasks that only developers can tackle.
This advantage stems from the specific design and optimization of RPA platforms for process automation. Consider Microsoft Excel's ability to enable a wide range of personnel to perform distinct types of analysis without learning Python, R, or another language. It encapsulates actions that would require sophisticated code within a user-friendly, visual interface
Similarly, RPA platforms encapsulate powerful functionality within a drag-and-drop interface. This setup allows for offloading some development work from the development team entirely.
In scenarios requiring custom code, RPA platforms provide access to the underlying code for review and editing and support the use of Python or other custom code. This way, the development team enjoys the benefits of a platform while retaining the flexibility to diverge when necessary.
Another common issue when using traditional software development for process automation is a drop in job satisfaction among both developers and non-developers.
Developers often find more satisfaction in projects that involve creating new systems, designing user interfaces, and solving complex problems through coding. However, process automation focuses more on automating existing systems. This shift from technical innovation to business operation can make the work less engaging for developers, feeling like a less effective use of their skills.
On the other hand, non-developers like business analysts, subject matter experts, and end-users can get bogged down by the lengthy software development cycle. Using an RPA platform can cut through unnecessary delays, creating a faster, automation-focused development cycle. This change can boost morale and job satisfaction by delivering business benefits quicker and more often.
The ideal set of skills and tools for automating processes is different than those that are ideal for systems development - and it is hard to have both coexist in the same team at the same time.
Software development organizations are optimized to create and manage systems – not workflows. This requires a certain set of skills, tools, and processes that are either overkill or at least suboptimal for automating processes. These tools and processes are optimized for systems development but are likely to make process automation unnecessarily slow and do not add much, if any, value.
Automating processes requires an in-depth knowledge of how users and the business interact with specific domains. The individual creating automations must be aware of each potential outcome a process might experience. They must also be able to discern and account for each edge case and personnel who may need to be involved to complete the process.
Having a team excel in both areas can be challenging due to the divergent focus and skill sets required. For instance, continually shifting between the technical mindset needed for systems development and the operational focus required for process automation can be demanding.
When a single team handles both responsibilities, it can lead to organizational challenges. The differing focuses can cause confusion, making it difficult to maintain a unified working structure day-to-day. This split focus can lead to inefficiencies and frustration among managers, developers, business analysts, and users.
In navigating the digital transformation journey, the choice between leveraging Robotic Process Automation (RPA) platforms and traditional software development is pivotal.
The inherent design of RPA platforms, being purpose-built for process automation, offers a swift, cost-effective avenue to automate processes as opposed to the often laborious and costly route of custom software development. The out-of-the-box functionality, including pre-built modules, efficient scheduling, queue management, and load balancing, significantly trims the development timeline, enabling organizations to reap the benefits of automation sooner.
RPA platforms, when managed by a team with a keen focus on process automation, unlock a realm of efficiencies and cost-savings that traditional software development teams may find challenging to replicate. The specialized focus and skillset of a process automation team, coupled with the inherent capabilities of RPA platforms, provide a robust solution for organizations looking to optimize their operations. By recognizing the distinct differences between process automation and systems development, organizations can better align their IT expertise, fostering an environment where both domains can thrive.