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Top 6 Steps to Identify Processes to Automate with RPA in 2024

Choosing the right processes to automate with RPA is one of the first decisions businesses need to take before implementing RPA.

Studies have shown that an RPA pilot project may take 4-6 months, instead of the expected 4-6 weeks. That’s because businesses don’t have enough knowledge about their in-house processes and which ones to automate. 

In this article, we will explain the steps and best practices to identify business processes that can benefit the most from automation.

Step 1: Identify processes that are best suited for RPA

Even if a process is not a good candidate for automation as a whole, it could be parceled into automatable sub-processes, that yield large benefits when automated. We recommend businesses to adopt process mining to automatically identify the most suitable processes to automate.

By utilizing the performance metrics, process mining tools can show automation rates and potential for businesses. Learn more about RPA-process mining integration.

Which processes are best fit for RPA?

Though process mining solutions can automatically identify processes to automate, it helps to understand underlying reasons behind processes’ suitability. This can help you double check process mining findings especially before applying them to your businesses’ core processes. These processes tend to be good fit for RPA automation

1. Rules based

Ideal processes can be described by specific rules. RPA bots need to be programmed. If the rules of the process can not be programmed, the process is unsuitable for RPA. AI can be trained with complex rules, and even uncover rules, that are not apparent to human operators.

However, automation of such processes requires careful observation of RPA results since there may be cases where AI incorrectly identifies rules.

2. With few exceptions

This is similar to the “rule-based” criteria above. However, some processes have so many undocumented rules that even if they are rule-based, it is time consuming to identify all rules via interviews with domain experts. Such processes are not good candidates for automation.

3. Company-specific

Is this a process that all companies undertake in the same way or is it unique to your company? For example expense auditing similarly takes place in most companies of similar sizes. Building an RPA ecosystem for expense auditing would be costlier and less effective than just using a solution built for such a process.

4. Mature

Automating a process that is changing every day is a waste of time because developers will spend a lot of time on maintenance. Stable processes are good candidates for automation.

5. Not on the roadmap for new systems

Processes that are part of legacy workloads which are on the roadmap to be replaced with new systems, must not be automated. For example, RPA bots that need to rely on screen scraping may not work if new systems are deployed to replace legacy ones.

Step 2: Prioritize most impactful processes

The most impactful processes and best suited for automation via RPA tend to be:

1. Processes impacting both cost and revenues

Most impactful and mission-critical processes touch customers. For example, order-to-cash can be expensive if pricing rules are not clear. The speed and effectiveness of order-to-cash processes can make or break a sale. Such processes are good candidates for RPA if they can be automated.

2. High volume processes 

One of the key benefits of RPA is the reduction of human effort. You should start automating your highest volume processes first. An example of high-volume processes is data entry from PDFs or web browsers to spreadsheets.

3. Fault tolerant processes

If a process can not handle any errors, then its automation should either be deprioritized or there should be a quality control process to ensure that automation errors get caught. This is because RPA bots rely on user interface (UI) to carry out their tasks, therefore, RPA may have errors due to UI changes or process changes. An example is invoice-to-pay use cases. For example, it makes sense to automate invoice-to-pay processes for most companies. However, payments above a certain value would need to be approved by humans.

4. Processes that are prone to manual errors

The more manual errors in a process, the more benefits your company can get by automating such a process. Manual mistakes can cause significant customer experience or regulatory problems, especially in customer-facing processes.

For example, financial reporting is an error-prone process as it depends on multiple databases which change frequently. Leveraging RPA for generating financial reports can significantly reduce errors in reports.  

5. Speed and delay sensitive processes

Any processes that can delay the delivery of services to customers are good candidates for automation as automation can make processes instantaneous. Some processes that can benefit from RPA to speed up customer response include:

  • Resolving simple IT requests (e.g. fetching troubleshooting information, renewing passwords)
  • Generating customer invoices
  • Fetching order information (e.g. date of shipping, place of shipment)

6. Processes that require temporary labor

Since finding temporary labor is difficult, processes with irregular labor demands force companies to employ for peak demand, which is inefficient. RPA bots can easily scale up or down, easily managing peak demand.

Best practices to identify processes to automate with RPA

It is almost impossible to know every process in a large organization. Without that knowledge, it is not possible to correctly identify highest highest-priority processes to automate. There are 2 approaches to overcome this issue:

Automate commonly automated processes. We have prepared a list of common RPA use cases and RPA case studies. The most popular process to automate is invoice automation. Feel free to read how RPA, complemented by AI vendors, can automate invoice capture and invoice processing.

Leverage process mining to identify the best process candidates for automation.

For more on RPA implementation

To explore the necessary steps to successfully implement RPA, read our in-depth articles:

If you still have any questions about RPA, read our in-depth whitepaper on the topic:

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And if you are looking for an off-the-shelf RPA solution, scroll down our data-driven list of RPA vendors, and check our comprehensive hub of automation solutions.

And we can guide you through the process:

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Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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