“I don’t need more dashboards. I need something that actually helps my stakeholders hit their targets.”

That’s what a data leader at a major food delivery company told me recently.

We were discussing a typical request: their sales team wanted a map showing onboarded vs. non-onboarded restaurants. Pretty standard, right? The data team built exactly that: a nice map-based dashboard, clean and polished.

But here’s the problem: it didn’t help the sales team do their job.

The Real Problem

Let’s step back for a second.

The sales team’s actual goal wasn’t just to see which restaurants were onboarded. Their mission was: onboard new restaurants that contribute to business growth and profitability.

A map showing dots on a screen? That only describes the status quo. It tells the sales team where things stand, but not what to do next.

And that’s a critical miss.

Most dashboards are descriptive. They tell you what is. But high-impact data products need to be prescriptive. They should:

• Tell your users what to do next
• Reduce guesswork and manual effort
• Align directly with company goals and key results

The food delivery sales team didn’t just need a fancy visualization. They needed:

✅ A prioritized list of restaurants,
✅ Ranked by likelihood to convert and drive profit,
✅ Delivered directly to each sales agent,
✅ So they could work through it from top to bottom.

That’s what a high-impact data product looks like.

Why Does This Happen?

In many companies, the same pattern repeats:

1. A business team requests a dashboard.
2. The data team builds exactly what was asked for.
3. Both teams are frustrated when it doesn’t lead to real results.

Why? Because the request focuses on outputs (the dashboard) rather than outcomes (moving key business metrics).

That’s why I use the Key Result – Service – Product Framework.

It helps data teams shift focus from building stuff to driving business outcomes.

The Key Result – Service – Product Framework

Here’s how it works:

1️⃣ Vision & Mission:​
You start by understanding the big picture. Not just for the company, but for each business domain (like Sales, Marketing, Ops).

Example:​
​Sales Vision: Build the strongest network of restaurant partners for sustainable growth.
​Sales Mission: Identify, engage, and onboard high-quality restaurants that meet customer demand and drive healthy margins.

2️⃣ Objectives & Key Results:​
What specific, measurable results is the team working toward?

Example key results:

→ X new restaurants onboarded.​
→ Achieve a profit margin of X% for newly onboarded restaurants.

3️⃣ Services:​
This is where things often break down. The service is what the business domain needs to achieve the key result.

In our example, the Sales team thought they needed a map dashboard. But in reality, the service they needed was:
→ A prioritized lead list delivered to each sales agent, ranked by conversion and profitability potential.

→ Ideally sent to a sales automation tool such as Hubspot or Salesforce to allow the sales agent to work in their regular environment and feedback data into the system

4️⃣ Data Products:​
Once the service is clear, the data team can build products to power it. For example:

• A restaurant data mart containing sales information and profiles of existing restaurants
• A new restaurant scoring data mart containing predictive scores to rank new restaurants based on their profit potential

5️⃣ Data Product Components:​
These are the building blocks, like:

• dim_restaurants table
• fact_sales table
• A predictive model to estimate conversion likelihood and profitability scores

Every part is linked. Every part matters.

Who Defines What?

This is where many data teams stumble.

• The business side (ideally, a project manager within the domain) should define the service: What do we need to achieve the key result?
• The data side (product owner) should define how to build it: How do we create the data products that power the service?

It’s a partnership.
And it’s also a healthy tension:
The data product owner should challenge the service definition to make sure it’s realistic and impactful.

Playing It Through: The Restaurant Example

• Vision: Build the strongest network of restaurant partners.
• Mission: Identify, engage, and onboard high-quality restaurants that meet customer demand and drive margins.
• Objective: Grow restaurant count in the EU.
• Key Result: Achieve a profit margin of X% for new restaurants.
• Service: Deliver prioritized leads to each sales agent - straight into the sales automation tool.
• Data Products: Restaurant & sales data marts + conversion prediction model.
• Components: Dimension and fact tables + ML model output.

Suddenly, the purpose of the data work is clear, and it's linked directly to business impact.

The Bottom Line

Most data teams are stuck in a build-to-order mindset.

The business asks for a dashboard → the data team builds a dashboard → nothing really changes.

The Key Result – Service – Product Framework changes that. It pushes you to:

• Map every data product to a clear business goal
• Define what’s needed to achieve key results before jumping into build mode
• Make your data team a core driver of business success

If you want your data work to matter - really matter - start mapping your products to the vision, mission, objectives and key results of your company.

Ask yourself and your stakeholders:
→ What service does the business really need to hit its targets?​
→ What data products will power that service?

The best data teams don’t just build stuff.
They build impact.

P.S.: If you want to build really impactful data teams, check out my masterclass "From dashboard factory to strategic partner."

In this 5.5 hour self-paced masterclass, I dive deep into the Key Result - Services - Product framework and many more frameworks developed over my 17+ years building high-impact data teams.

Cheers,

Sebastian