Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Short-term (< 3 months)
Last year, I had a B2B startup client approach me with an "exciting" opportunity: automate their entire HubSpot-to-Slack workflow using robotic process automation. The budget was substantial, the technical challenge seemed interesting, and RPA was all the rage in business automation circles.
I said no.
Not because I couldn't build it, but because I've learned something that most automation consultants won't tell you: RPA is often the wrong solution dressed up as innovation. While everyone's chasing the latest automation trends, the real wins come from understanding which tool actually fits the problem.
After working with dozens of startups on automation projects, I've discovered that the best automation isn't always the most sophisticated. Sometimes a simple Zapier workflow outperforms a complex RPA system by every metric that matters: cost, reliability, and team adoption.
Here's what you'll learn from my contrarian take on business automation:
Why RPA fails for most small businesses (and what works instead)
My framework for choosing the right automation tool
Real case studies from client projects that went wrong (and right)
When RPA actually makes sense (spoiler: rarely)
The AI automation approach that's actually working in 2025
Industry Reality
What the automation industry won't tell you
Walk into any business automation conference, and you'll hear the same promises: RPA will revolutionize your operations, eliminate human error, and deliver ROI within months. The industry has done an incredible job selling the dream of "digital workers" that can handle complex business processes without human intervention.
Here's what the consultants typically pitch:
Screen scraping automation - Bots that can interact with any software interface
Legacy system integration - Connect old systems without API development
Rule-based decision making - Automate complex workflows with conditional logic
Scalable digital workforce - Deploy unlimited "robots" to handle repetitive tasks
Quick implementation - No coding required, rapid deployment
The market research supports the hype. Studies show RPA can reduce processing time by 90% and deliver ROI of 200% within the first year. Major consulting firms have entire practices built around RPA implementations.
But here's the problem: these success stories come from enterprise environments with specific conditions that don't exist in most small businesses. The RPA industry has created a one-size-fits-all solution for problems that need nuanced approaches.
What they don't tell you is that RPA works best when you have stable, repetitive processes with minimal exceptions. Most startups and growing businesses live in constant change mode - exactly the opposite environment where RPA thrives.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
My wake-up call came during a project with a B2B startup that wanted to automate their deal-closing workflow. Every time they closed a deal in HubSpot, someone had to manually create a Slack group for the project. Small task? Maybe. But multiply that by dozens of deals per month, and you've got hours of repetitive work.
The client had been pitched an RPA solution by another consultant - a sophisticated bot that would monitor HubSpot, detect deal closures, and automatically create Slack groups with the right team members. The proposal was impressive: screen scraping technology, conditional logic, error handling, the works.
Here's where I learned my first lesson about RPA vs. reality: the client didn't need a robot, they needed a bridge.
Instead of building a complex automation that could break with any interface change, I started exploring simpler solutions. That's when I discovered the power of platform-native integrations and workflow automation tools like Make.com, N8N, and Zapier.
The startup's challenge wasn't unique. They had a growing business with evolving processes. Their HubSpot configuration changed monthly. Their Slack workspace structure adapted to new team members. An RPA solution would require constant maintenance and updates.
But the real insight came when I started working with their team directly. The manual task wasn't just about creating Slack groups - it was about setting up the right context, inviting the right people, and ensuring proper project kickoff. A bot couldn't replicate the human judgment needed for these nuanced decisions.
This experience taught me that most businesses don't have RPA problems, they have integration problems. They need systems to talk to each other, not robots to pretend they're humans clicking through interfaces.
Here's my playbook
What I ended up doing and the results.
Instead of implementing RPA, I developed what I call the "Platform-First Automation Framework." This approach prioritizes simple, maintainable solutions over complex robotic systems.
Phase 1: Platform Assessment
I started by auditing their existing tools for native automation capabilities. HubSpot had workflow triggers. Slack had API endpoints. The solution wasn't to bridge these with a robot - it was to connect them directly through their existing infrastructure.
For this client, I implemented a three-tiered approach:
Make.com Implementation - Started with Make.com for cost reasons, but discovered it stops all workflows when any step fails
N8N Transition - More robust automation but required developer knowledge for every small change
Zapier Migration - Finally settled on Zapier for team accessibility and reliability
Phase 2: Smart Workflow Design
Instead of replicating human behavior, I designed workflows around system strengths:
Used HubSpot's deal stage changes as triggers
Leveraged Slack's team management APIs
Built conditional logic based on deal properties
Created fallback notifications for edge cases
Phase 3: Team Handoff Strategy
The biggest advantage over RPA? The client's team could actually understand and modify the workflows. Unlike black-box RPA systems, these integrations were transparent and editable.
The key insight: automation should enhance human decision-making, not replace it. Instead of a robot making all the choices, the workflow prompted team members when human judgment was needed.
This approach worked so well that I started applying it to other automation challenges. Whether it was content generation workflows or e-commerce order processing, the pattern remained consistent: platform-native solutions outperformed RPA in reliability, maintainability, and team adoption.
Tool Selection
Choose the cheapest viable option first - you can always upgrade when you hit real limitations
Process Mapping
Focus on outcomes not activities - automate the result you want not the steps you take
Team Adoption
Build workflows your team can actually understand and modify themselves
Maintenance Reality
Simple solutions require less maintenance than complex ones - optimize for sustainability
The results spoke for themselves, but not in the way you might expect. Instead of measuring "automation success," I learned to track business impact:
Immediate Wins:
Project setup time reduced from 30 minutes to 2 minutes
Zero missed project kickoffs due to automation failures
Team could modify workflows without calling me
Long-term Impact:
Six months later, the client had expanded the automation to handle customer onboarding, invoice generation, and progress reporting. The beauty? They built these additional workflows themselves using the same platform.
But here's what surprised me most: the client's manual processes actually improved. Because the automation handled routine tasks reliably, the team could focus on the high-value activities that genuinely required human insight.
Compare this to RPA implementations I've observed: they often create rigid processes that become harder to change as business needs evolve. Teams become dependent on automation specialists for every modification.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
After working through this automation challenge and several others, here are the key lessons that changed how I approach business process automation:
Start with the simplest solution that works - You can always add complexity later, but you can't easily remove it
Platform-native beats custom every time - Use tools the way they're designed to be used
Team accessibility trumps technical sophistication - If your team can't understand it, it will become a liability
Optimize for change, not perfection - Growing businesses need flexible systems
RPA works best for stable, high-volume processes - Most startups don't have these
Integration problems need integration solutions - Not robot solutions
Measure business outcomes, not automation metrics - Time saved means nothing if it doesn't impact results
The biggest mindset shift? Stop thinking about replacing humans and start thinking about amplifying them. The best automation makes your team more effective, not redundant.
When clients ask about RPA now, I recommend they first exhaust simpler solutions. In my experience, 90% of automation needs can be solved with workflow tools, APIs, and smart integrations. Save RPA for the 10% of cases where it's genuinely the best fit.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
Evaluate existing platform integrations before considering RPA
Start with Zapier/Make.com for simple trigger-action workflows
Focus on customer-facing process automation first
Build workflows your team can modify independently
For your Ecommerce store
Automate order processing and fulfillment notifications
Use platform APIs instead of screen-scraping solutions
Integrate inventory management with sales channels
Prioritize customer communication automation over internal processes