The pandemic is now considered an inflection point for automation, with some predicting that RPA spend will reach $25 billion by 2025 (compared to $3.6 billion today). In the first quarter of 2020, UIPath added 836 customers, as it helped a number of enterprises ensure business continuity, including patient data collection, health alerts, government approval for stimulus assistance, contact tracing, and more.
There’s no cut and dry definition of RPA success; it will vary depending on a company’s unique workflows, and there are some use cases that are better suited for RPA than others. At the highest-level, RPA is about re-examining how a business runs and determining if things can be re-engineered to achieve greater efficiencies. Put simply — it’s all about optimization.
If you’re new to RPA, here are the top tips for success we gleaned from the Fortune 500 execs we spoke to:
1. Align your workforce: The first step is establishing alignment across departments. There is real fear from employees when they hear the term “automation” — a recent survey shows that nearly 25% of employees fear losing their jobs — so ensuring employees understand the objectives (e.g., empowering them to focus more on mission-critical processes) is vital for long-term success.
2. Implement governance and prioritize security: Create a Center of Excellence (COE) that operates as the “HR” of automation in your organization to govern what works, where automation is needed, and best practices for security and IT. The COE can also provide change-management for exception handling and process overview, guidance, and course correction. The COE manages the actions of the automation tools, similar to how HR manages human labor. This will ensure that “shadow IT” does not occur and actions taken are in accordance with compliance and security.
3. Focus on visibility, documentation, and lastly automation: As companies stay remote longer, they’ll need to better understand their existing internal processes, with documentation being key for data-informed decisions on the best path forward. Catalog internal processes with process mining tools before selecting areas to automate. Historically, process mining was log-based (Celonis) to visually digitize workflows, but now computer vision-based tools (FortressIQ and Skan.ai) provide increased accuracy in revealing mismanagement, inefficiencies, compliance issues, and the ineffectiveness of existing tools. Automation is not always the answer, with alternative paths including redesigning workflows or retraining employees.
4. Target long-term objectives, not individual tasks: After documentation, change-management must think critically about whether automation is truly needed and, if so, what improvements it can offer. Process intelligence is important so companies can think through from a first principles perspective to re-engineer their process, re-train employees, or implement automation. A business must first understand its existing processes before considering implementing automation technologies.
5. Juggle best-of-breed and horizontal tools: Most executives recommend using both horizontal and best-of-breed solutions. End-to-end intelligent business process automation platforms (e.g., Tonkean, Automation Hero, Camunda, Workfusion) allow companies to consolidate tools and reach the desired business outcome. These are especially helpful as most business processes include a combination of human intervention and data manipulation, with complex workflows consisting of numerous data formats and applications.
To achieve the best results with RPA, take an iterative approach. Don’t expect perfect automation after a 12-month development cycle.