Here is a fact check:
Studies have shown that by 2025, we could expect enterprises to potentially save approximately USD 5 – 7 trillion by implementing RPA and benefit from its cost efficiencies coupled with the right technology. It will enable enterprises to focus on higher-value tasks and enhanced customer experience.
So, RPA has the answers. But are you asking the right questions?
Despite the advantages of RPA, businesses are losing out on automation opportunities, simply because they are not asking the right questions before implementing it.
So, before deploying your RPA strategy, here are the questions that you need to ask from your enterprise:
- Process: Is automation a volumes game?
Remember, RPA is like a lubricant, which enhances performance. It cannot repair an engine, or in this case, an inefficient process. It can only automate what exists, so if your business processes are ineffective, RPA will be unable to add any value. So, should you automate manual processes that are low-volume? While it makes sense to automate high-volume manual processes, you should automate low-volume ones only if there’s scope for expansion in the future or repeated human errors, which are costing the enterprise dearly.
- Data: Do you know the structure of your data?
RPA requires structured data to function because it employs pre-defined business logic and rules to automate business processes. If your enterprise manages a lot of unstructured data like scattered emails and print documentation, you will first need to invest in a solution, which structures this data and aids the RPA process.
It includes extracting, digitalizing and categorizing the data.
- Human intervention: Can automation replace human decision-making?
RPA automates repetitive, mundane, and laborious tasks, which do not require strategic thinking and human intervention. However, if your business runs on the fuel of human judgment and decisions-making, investing in a workflow or case management solution will empower rapid end to end process digitalization. As more people work remotely – enterprises are turning to AI enabled automation to bring consistencies at scale in people-intensive processes to support cognitive decision-making, which is bringing in machine learning to increase throughput at scale with consistency and accuracy.
- Workflow: Is RPA equipped to handle exceptions?
Exceptions are a part and parcel of every business. Though RPA can learn to handle exceptions, it offers maximum output with little or no exceptions because they require workflow and case management. If you want RPA to handle exceptions, then you should consider integrating it with an existing workflow or case management solution.
- One size fits all: Can RPA be a one-stop-shop solution?
Such an approach means expectations are too high from RPA. Be realistic about your expectations and view RPA as an enabler rather than a be-all-end-all solution., RPA provides a building block to digitize processes but can’t work as a single approach to sort out all your efficiency and cost issues.
- Readiness: Is my enterprise ready for an automation journey?
Remember, RPA is mostly suitable for repetitive and manual tasks with minimal process changes. Avoid any processes slotted for large-scale IT integrations in the near future, and instead, consider automating processes involving non-custom applications. You don’t even need to automate your process 100% or a task to begin enjoying RPA’s benefits.
- Result-driven: Will RPA will bring results to my enterprise right from day one?
Don’t expect too much too soon after implementing RPA. A lot of businesses feel dejected after implementing RPA because they see automation as the end goal. Automation works best when it works in tandem with an agile approach. It means focusing not just on automation but also on improving business processes. An agile approach evaluates which component will yield maximum results.
- Stakes: What are the risks of executing an unplanned RPA strategy?
RPA goes far beyond cost reduction and rapid development. Here are the risks that can arise from a poor and ill-planned RPA implementation:
- Demographics and geographic
Customized solutions based on countries and business units can lead to inconsistencies and errors, which will result in a higher cost of automation.
- Passing the buck
By and large, RPA projects fail due to a lack of ownership and clarity about the roles and responsibilities of business heads and the IT team.
- Are you being watched?
Despite rapid advancements in RPA technology, security and data privacy remains a huge concern. With no proper access rights defined, a business’ valuable data can be compromised and exploited.
- A change-ready environment
RPA implementations involve a lot of operational and tech changes, which include data mapping and configuration. These need to be updated immediately to avoid poor outputs and inaccurate results.
- Poor diligence = Poor business intelligence
It’s a no-brainer that selecting an inexperienced RPA implementation partner will result in operational problems as well as financial losses. Ask the right questions and ensure that you conduct proper due diligence.
- Demographics and geographic
The bottom line
Coincidentally, the success of your RPA implementation strategy also depends on
- Why should you do it?
- What should be done?
- When to get started?
Without this clarity and subordination from the senior management and stakeholders, building internal capability and managing change is going to be a major challenge.
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