Why Your Team is Slow: The Hidden Cost of Missing Business Context

Over my career leading engineering and data science teams — from regulated industries to early-stage startups to large enterprises — I’ve consistently seen one pattern: Teams can move incredibly fast when they understand how their work drives business value, and painfully slow when they don’t.

Most recently, as VP of Engineering and Data Science at a mental health startup, I watched our team’s velocity multiply after making one fundamental change. It wasn’t better processes, fancier tools, or more meetings. It was something simpler yet more powerful: creating crystal-clear clarity about how our business actually worked.

Here’s what I’ve learned from transforming team velocity across vastly different contexts — from zero-to-one products to large-scale systems, from heavily regulated environments to rapid experimentation cultures: The root cause of slow teams isn’t lack of process. It’s lack of context. The best processes in the world won’t help if your team doesn’t understand how their work creates value.

The Answer Isn’t Process

When teams feel slow, the natural instinct is to add process. More meetings. Deeper work tracking. And it gives a great illusion of control.

But here’s what actually happens:

1. Each new process adds coordination and communication overhead
2. Leaders get stretched thin managing communication
3. Less time is spent on critical strategic thinking
4. The team gets even slower
5. Repeat

We’re optimizing the wrong thing. The core problem isn’t process – it’s uncertainty about what actually matters.

The Real Solution: A Shared Mental Model

Instead of more process, teams need a clear way to connect their daily work to real business value. This is where the concept of a “Business Thesis” comes in.

Here’s how it works:

1. Define Your Core Value Metric

Start with one key metric that captures the core value you deliver to customers. This should be:

• Hard to move
• Clearly valuable
• Something everyone can understand

For example, Amplitude uses “Weekly insights shared and read by 3+ people” as their North Star metric.

2. Build Your Input Tree

Break down the drivers that influence your value metric:

• What inputs do you believe affect this metric?
• How do these inputs interact?
• Which teams can influence which inputs?

This creates a “metric tree” showing how different activities theoretically drive value. These should be things which interventions can influence (whether it be a new model, a product feature, etc).

3. Structure Your Bets

For each input metric, define clear bets:

• What specific changes do you think will move this input?
• How will you measure the impact?
• What timeline do you expect to see results?

4. Learn Systematically

This isn’t just a one-time exercise. You’re creating a learning framework:

• Is your value metric actually predicting business success?
• Are your input metrics really driving the value metric?
• Which bets are working and which aren’t?

Why This Works: Cutting Through Uncertainty

This framework does something powerful: it gives everyone a shared mental model of how the business works. This means:

1. Teams can make independent decisions because they understand the context
2. Cross-functional collaboration becomes easier with shared language
3. Learning becomes systematic rather than scattered
4. New opportunities are easier to evaluate against clear criteria

Making It Real: A Practical Example

Let’s say you run a B2B SaaS product. Your business thesis might look like this:

Value Metric: Monthly Active Teams (teams with 3+ users who complete core workflow)

Input Metrics:

• Time to first value (how quickly new teams complete setup)
• Team activation rate (% of teams who establish regular usage patterns)
• Cross-team collaboration (average connections between teams)

Example Bet: “We believe reducing setup time from 45 to 15 minutes will improve team activation by 40% by removing early friction”

Now every team member can clearly see how their work connects to business value:

• Product can focus on streamlining setup
• Engineering knows which performance metrics matter most
• Support understands which friction points to prioritize
• Sales knows which benefits to emphasize

Start Small, Learn Fast

You don’t need a perfect framework to start. Begin with:

1. Draft your initial business thesis
2. Share it widely and gather feedback
3. Start tracking basic metrics manually if needed
4. Review and adjust monthly
5. Let the framework evolve as you learn

Your Turn

Ready to make your team move faster? Book a free consult with me here.