Our Contrarian Hypothesis to Automation
Automation is a buzzword in tech, but many startups approach it the wrong way, diving headfirst into automating everything.
“We currently observe most tech teams getting caught up in ‘let’s automate 90%’. We think the more valuable approach is augmenting productivity first and enabling teams to understand how they work. That can help save money now and lays the groundwork for thoughtful automation later.”
At beams, we believe there’s a smarter way: start with understanding workflows, augment productivity, and only then move toward thoughtful automation.
Here’s why—and how you can get it right.
Why Understanding Comes Before Automation
In a talk our co-founder Jana gave recently at the Berlin AI Meetup (see video below), she shared an unconventional take on automation:
"We believe the path to real value isn’t ‘automate everything now.’ It’s augmenting productivity first - helping teams deeply understand how they work. This saves money now and sets the stage for smarter automation later."
Let’s break this idea down into three key insights:
1. People Struggle to Explain Their Workflows
Knowledge workers, especially in dynamic or creative roles, often find it hard to describe their workflows. If you’ve ever tried mapping out your own processes, you know how complex and messy they can be.
AI tools and Robotic Process Automation (RPA) tools depend on clear instructions, e.g. based on chat, but workers often give incomplete or inaccurate explanations. This means automation only works part of the time, leaving inefficiencies and frustrations behind.
2. The Real Opportunity: Process Analysis
Instead of rushing into automation, we see an overlooked opportunity: process modeling and analysis.
Deeply understanding workflows, productivity habits, and tool usage reveals inefficiencies and opportunities for improvement. This “dirty work” may not sound exciting, but it lays the foundation for meaningful change.
3. Thoughtful Automation as the Next Step
With clear insights and better processes, automation becomes a natural next step - not the starting point. Thoughtful automation delivers better results because it’s built on a foundation of clarity.
This shift in mindset can lead to smarter systems, happier teams, and real cost savings.
How to Rethink Automation in Your Organization
If your team is eager to automate, it’s tempting to jump straight to solutions: integrating new tools, implementing AI, or rolling out RPA. But before automating, take a step back and focus on building a solid foundation.
- Understand Your Current Workflows: Most knowledge workers don’t fully grasp their own workflows, making it hard to automate effectively. Start with a detailed audit of processes, tools, and team collaboration. Look for bottlenecks and redundancies and gather data through tools like usage dashboards or productivity analytics.
Use productivity analytics tools to get data-backed insights. For example, tools like time trackers, usage dashboards, or process mining software can reveal patterns you might miss.
- Fix Inefficiencies First: Automating flawed workflows often makes things worse. For example, automating a manual approval process sounds great—until you realize approvals aren’t necessary in the first place. Instead, identify repetitive tasks and low-value processes that truly benefit from automation.
- Start Small and Scale Thoughtfully: Don’t aim to automate everything at once. Pick a small, well-defined task, document the process clearly, and measure results before scaling. Think about it as augmentation, not replacement. Instead of aiming to replace humans, use automation to enhance productivity and free up time for high-value tasks.
At beams, we believe that true productivity starts with understanding. That’s why the beams Work Intelligence Platform is designed to give teams a clear picture of their productivity, tool usage, and inefficiencies. By uncovering these insights, organizations can make smarter decisions about where automation will have the most meaningful impact, reducing waste and maximizing value.
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