11 Steps to Successful RPA Implementation in 2024

Automating business processes through robotic process automation (RPA) is a top priority for many companies today. But RPA success doesn‘t come easy. Industry surveys show high failure rates – up to 30% of RPA projects fail to move beyond the pilot stage.

You don‘t want to be part of those failure statistics. By following a structured approach, you can avoid common pitfalls and ensure your RPA journey delivers real business value.

In this guide, I‘ll walk you through the 11 essential steps to implement RPA successfully based on proven best practices. With the right planning and execution, you can join the RPA success stories we see across industries.

1. Map Out Existing Processes

The first step is to fully understand existing processes before attempting any automation. Surprisingly, many companies fail here – they either rely on outdated process documentation or make assumptions about how work gets done.

The best way is to visually map processes through observation and stakeholder interviews. You‘ll uncover the actual "as-is" state versus theoretical workflows. According to a Deloitte study, 95% of companies that conducted process discovery through interviews and process mining achieved over 15% cost reduction from RPA, compared to only 45% of firms that relied on guesswork.

Document all the nitty-gritty details – every step, decision point, input, output, and applications used. Highlight pain points and improvement areas. This becomes your master blueprint for identifying automation opportunities later.

2. Identify the Right Automation Candidates

Next, analyze each process step-by-step to determine suitability for RPA. Look for repetitive, rules-based tasks involving data transfers, data entry, or multiple system logins. For example, copying customer data from one system and pasting it into another system is ideal for automation.

You also need to estimate potential business impact across factors like cost, time savings, improved accuracy, and scalability. For instance, automating daily 2-hour report consolidation tasks across a team of 10 employees generates 20 hours daily productivity gains.

Based on automation feasibility and ROI, prioritize simple activities with quick wins versus complex end-to-end processes. Maintain a ranked shortlist of automation opportunities.

3. Secure Executive Sponsorship

Before going too far down the RPA road, get buy-in from business leaders. Walk them through your assessment of top automation candidates and their potential ROI. With executive sponsorship, it‘s easier to justify RPA investments and get participation from stakeholders.

Appoint a steering committee for governance and oversight. Form a diverse RPA delivery team with business analysts, RPA developers, IT specialists, and domain experts. Large organizations also establish RPA Centers of Excellence for sustained skills development and automation support.

With the right backing, you can devote resources required to adopt RPA successfully. Gartner found 33% higher RPA success rates for projects with C-level endorsement versus limited middle management approval.

4. Evaluate and Select RPA Software

Now it‘s time to assess RPA tools from leading vendors like UiPath, Blue Prism, Microsoft, WorkFusion, Automation Anywhere, etc. Compare capabilities to automate your shortlisted processes. Focus on ease of use, developer productivity, scalability, and licensing costs.

Ensure the platform easily integrates with your existing infrastructure. Look for prebuilt connectors, bots, components, and workflows related to your industry. For advanced use cases, verify capabilities like AI, machine learning, and analytics.

Start with a small proof-of-concept project. Once satisfied, expand the scope for broader adoption. Demo versions and trials allow hands-on tool evaluation before big commitments.

5. Build an RPA Competency Team

RPA success depends on access to specialized skillsets. WorkFusion‘s 2020 survey found lack of internal skills as the top RPA adoption barrier. Upskill employees through rigorous training and certification programs. Hire RPA coordinators, architects, developers, and QA specialists.

Engage external consultants to jumpstart deployments while developing internal capabilities. Over time, create a Center of Excellence to institutionalize skills in RPA solution design, development, testing, monitoring and management.

According to Everest Group, organizations investing in specialized RPA teams through training, new hires or partnerships achieve over 200% faster payback compared to relying solely on IT resources.

6. Design End-to-End Automations

With software selected and skills onboard, it‘s time to design your process automations. Walk through each step meticulously, documenting how software bots will mimic human actions. Will the bot log into multiple systems? Read and write data? Make rule-based decisions? Handle exceptions?

Chart out hand-offs between bots and humans to optimize workflows. Adopt a phased approach starting from simple point solutions, before building end-to-end automations. Reuse existing bot components where possible for faster development.

Good design sets the foundation for scalable solutions. Spend time on it. Consulting firm McKinsey estimates companies save over 25% in RPA costs by getting design right from the outset.

7. Develop and Validate Extensively

Now RPA developers start building automations iteratively by coding bots or configuring them visually via drag-and-drop interfaces. Maintain structured, documented code following standard frameworks and naming conventions for maintainability.

Conduct extensive testing across different use scenarios, data sets and environments. Automate testing using tools like Tricentis Tosca for scale and repeatability. Fix issues through successive rounds of development and testing.

Before deploying to production, verify RPA accuracy, integration, performance, security and compliance through mock trials and UAT. Don‘t take shortcuts here – robust validation ensures smooth downstream adoption.

8. Run a Limited Pilot

The next best practice is to pilot automations in production on a small scale. Run bots handling live data alongside a human worker who can intervene if needed. Start with non-critical processes and limited transaction volumes.

Closely track pilot performance – is the bot executing reliably without errors? Are service levels and accuracy targets being met? Are processing costs reduced? Address issues before expanding.

A successful pilot demonstrates RPA value, reduces stakeholder resistance, and refines your support model for large-scale adoption. Microsoft found RPA success rates improved by 52% for projects with short targeted pilots versus direct big bang deployments.

9. Manage RPA Like an IT System

Don‘t treat RPA as a one-time project. Manage and govern it like you would any other IT system or application. Assign technical resources to maintain a growing bot workforce as processes change over time.

Monitor process variations using process mining tools. Proactively modify and retest automations to keep pace. Avoid situations of redundant or conflicting bot versions.

Follow defined protocols for bot development, testing, release approvals and deployment. Institute controls and audits to manage risks as bot usage expands across your company.

10. Scale Intelligently

After successful pilots and change management controls, scale RPA across the organization. Right-size bot workforces through incremental additions versus overnight replacements.

Target quick wins first to build momentum, for example automating high volume repetitive tasks. With learnings, progressively expand scope to cover end-to-end processes and smarter capabilities like AI and analytics.

Evolutionary expansion allows smoother human-bot collaboration as employees become comfortable working with automation. It also provides time to address complex exceptions before rushing full speed.

11. Continuously Improve Over Time

Leverage RPA as a stepping stone to an intelligent automation journey with AI, analytics, and other emerging tools. Continue assessing processes for further automation – don‘t stagnate after early wins.

Monitor bot performance, conduct speed and accuracy audits, and enhance automations through ongoing improvements. Stay updated on latest vendor features and marketplace innovations to expand capabilities.

Over time, evolve RPA teams into "automation competency centers" supporting different technologies as the automation footprint expands across the enterprise.

By taking this structured approach, you can build a successful RPA practice delivering tangible business value over the long-term. Be patient and don‘t expect overnight results. Sustained commitment, investment and vision will put you firmly on the path to hyperautomation.

Remember, don‘t go it alone. I‘m here to guide you through your RPA and automation journey. Let‘s have a discussion to explore how we can work together to accelerate success. The future is automated – let‘s start building it today.