The robotic process automation (RPA) market is booming, with revenue projected to reach $13.74 billion by 2030 according to Grand View Research. As more companies invest in RPA, one of the most critical determinants of success is identifying the right processes to automate.
However, this is also one of the biggest challenges. Lack of visibility into all processes, legacy systems operating in silos, unclear ROI, and other factors make it difficult to determine automation priorities. Studies show 75% of RPA projects take 4-6 months instead of the expected 4-6 weeks largely because of poor process selection.
In this comprehensive guide, we’ll walk through the top steps and best practices for organizations to identify the most impactful processes to automate with RPA in 2024.
Step 1: Leverage Process Mining Tools
Gaining end-to-end visibility across all processes is foundational. Yet this is extremely difficult in large companies with distributed systems, fragmented data, and siloed departments.
Process mining technology is purpose-built to address these challenges. It automatically analyzes system event logs to uncover processes, identify variations, quantify performance, and spotlight automation opportunities.
On a technical level, process mining algorithms interact with system event data to visualize real processes, often uncovering broken or inefficient workflows that went unnoticed. Leading solutions like Celonis even benchmark process variants to identify the optimal flow.
Process mining dashboard revealing process variants (Image credit: Celonis)
By parsing system logs rather than employees‘ subjective perceptions, process mining provides objective, data-driven visibility. This eliminates bias and spots bottlenecks that users may not even be conscious of.
Vendors like UiPath Task Mining, Celonis, Signavio, Minit, and QPR ProcessAnalyzer use process mining to benchmark as-is processes versus best practice. Their automation opportunity dashboards estimate potential efficiency gains and ROI from automating each process with RPA.
Process mining provides the critical data-driven insights to identify the biggest automation winners.
Step 2: Understand Characteristics of Automatable Processes
While process mining guides process selection, augmenting its findings by understanding properties of automatable processes adds an extra layer of diligence.
This helps double check suitability, especially when applying automation to mission-critical processes where mistakes incur high costs.
Rules-Based
RPA bots follow programmed logic, so processes with ambiguous or highly variable rules are poor candidates. Well-defined rules that can reliably be encoded make processes automation-friendly.
For example, password reset procedures are highly rules-based – making them low risk to automate with RPA. In contrast, aspects of customer service with complex or subjective judgment calls are better left to humans.
Few Exceptions
Some processes adhere to clear rules but have so many exceptions that trying to address all edge cases in bot programming becomes impractical.
Prioritize automating processes with minimal deviations rather than highly exception-prone ones. Financial reporting for instance tends to have many unwritten nuances making full automation extremely difficult.
Company-Specific
Processes unique to your company provide automation opportunities that off-the-shelf solutions can‘t address. Generic processes handled the same way across all firms likely already have tailored software, so custom RPA is less beneficial.
Mature and Stable
Automating constantly shifting processes creates headaches from ongoing maintenance to address endless changes. Mature processes that have stabilized are better automation targets.
For example, automating new system workflows while they are still evolving leads to rework down the line as the process matures.
Not Pending Other Changes
It‘s best to avoid automating legacy processes that will soon face overhaul like migrations to new systems. RPA bots dependent on old UIs and workflows will break once those deprecated systems are shut down.
In past RPA initiatives, we learned this lesson the hard way when newly automated legacy processes had to be discarded post-migration.
Step 3: Prioritize by Impact and Suitability
Once processes with automation potential are identified, they must be prioritized based on importance and suitability. Key factors include:
Business Impact
Processes directly affecting revenue and customer experience offer maximum benefit. Order-to-cash, lending decisions, personalized marketing are high impact examples.
Volume
Automating high volume, repetitive tasks provides the most tangible productivity gains. Data entry, reconciliation, document processing are prime candidates.
According to surveys, 72% of early RPA adopters target high frequency tasks.
Error Reduction Potential
Automating manual processes prone to human error improves quality. Regulatory report generation and data integration are common examples.
Speed Needs
Any process on the critical path to delivering service should be automated to improve speed. Invoice processing and customer service requests are illustrations.
89% of businesses prioritize automating processes with fast ROI according to Deloitte.
Strategic Importance
Mission-critical processes with outsized influence on competitiveness deserve priority. Examples include pricing engines and customer targeting.
Difficulty of Staffing
Automating processes with large fluctuations in capacity needs is valuable since temporary labor is costly and often unavailable on demand.
Degree of Judgment
Highly rules-based tasks with little subjective decision making are prime candidates. Automating ambiguous processes requires AI rather than just RPA.
Data Integration Needs
Processes requiring data aggregation from multiple systems benefit significantly from automation.
Pleases Many Stakeholders
Choose processes providing wide cross-functional gains to secure buy-in. Avoid niche use cases benefiting just one group.
Step 4: Focus First on Common Automation Opportunities
While every company‘s needs differ, it helps to know common processes other organizations automate successfully to gain quick wins:
Financial Reporting
Extracting data from multiple systems to generate consolidated reports and filings. Useful for balance sheet, income statement, AP/AR, fixed assets, cash flow, and more.
Invoice Processing
Digitizing invoice info, validating against POs, matching shipments, and forwarding to approvers. 70% of businesses target early automation here.
IT Support
Automating mundane IT tasks like password resets, how-to‘s, software installs/updates, hardware requests. Enables refocus on strategic initiatives.
Customer Onboarding
Automatic form filling, data collection, identity verification, credential creation for new customers. Accelerates activations.
Claims Processing
Gathering supporting documents and policy information to validate and pay out eligible claims. Speeds closures and improves accuracy.
HR Onboarding
Provisioning employee accounts, credentials, and resources when people join. Reduces IT tickets and call volume.
According to surveys, 45% of RPA projects target finance processes while 35% focus on IT functions initially.
Step 5: Get Organizational Buy-In for RPA
To drive enterprise-wide adoption, upfront buy-in from leadership is crucial. Tailor the pitch to each stakeholder showing how RPA benefits them:
IT: Scalable capacity, lower ticket volume, focus on strategic initiatives
Operations: Process efficiency, improved quality, significant cost savings
Customer Service: Increased speed, higher CSAT through 24/7 automation
Finance: Hard dollar ROI, short payback period, funded from cost reductions
Proactively address concerns around disruption, job loss, skill gaps, and change management. Demonstrating a well-developed program governance model upfront fosters trust.
According to McKinsey, RPA success requires "selling the automation journey as a business-driven initiative rather than an IT scheme." Grounding the pitch in dollars and cents is key.
Step 6: Continuously Measure and Refine
Effective metrics allow ongoing optimization of automation performance and maximize ROI:
Processes Automated: Tracks expansion to new use cases showing scalability. Target automating 5+ new processes within 18 months.
Bots Deployed: Measures capacity growth. Bot count should rise steadily over time without human intervention needed.
Efficiency Gain: Quantify reductions in process time and cost versus manual work. Target over 40% improvement within first year.
Accuracy Increase: Error reduction versus human performance as automation bears more volume. Goal of near 100% accuracy.
ROI: Hard savings validating net positive business case. Goal of full payback within first 1-2 years from efficiency gains and labor savings.
End User Satisfaction: Feedback scores showing automation delighting business users, not creating headaches. Target rising metrics.
Continuous performance tracking identifies opportunities to expand automation while rectifying any deficiencies that arise before they become problematic. This optimization mindset is key to maximizing value from RPA long-term.
Choosing the right processes to automate is one of the most impactful yet challenging aspects of RPA success. Follow these steps and best practices:
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Apply process mining for data-driven process insights and automation opportunity analysis.
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Understand automation suitability factors like rules-based, low exceptions, and strategic importance.
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Prioritize processes by volume, error reduction potential, customer impact, and other key criteria.
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Pursue quick wins by automating common processes like financial reporting and IT support at first.
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Secure executive buy-in by conveying the hard ROI business case tailored to each stakeholder.
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Continuously monitor and refine automation performance using KPIs to expand scope over time.
Taking this targeted yet flexible approach will lead to maximum RPA impact. The key is selecting the right processes and demonstrating tangible business value. Done right, RPA delivers transformative benefits.