“You don’t need a data strategy. You need a business strategy that uses data.”

That was the most controversial take in a recent discussion I had with three highly respected voices in the data world - among them an ex-McKinsey partner, the former Head of Data Strategy at Capgemini and a Chief Data Officer at one of Europe’s most well-known marketplace businesses.

And it hit a nerve.

Because it raises a deep question: If data should just follow the business strategy, does it still make sense to talk about a data strategy?

What’s in it for you (and your data team)

If you’ve ever struggled to define what your data team should focus on, or how to align your work with company goals, this conversation will give you clarity.

You’ll walk away with:

• A clear way to define how data can drive business results
• Five paths your data team can take to create measurable impact
• A fresh take on the strategy vs. action plan debate

Let’s rewind to how this all started.

Where the debate began: Strategy vs. Action Plan

In one of my recent LinkedIn posts, I shared a framework for data strategy. My argument: the biggest mistake in creating a data strategy is starting with a tool stack, instead of starting with a problem and the user.

I also outlined nine core building blocks of an effective data strategy in my Data Team adjusted Lean Canvas framework:

I received a lot of praise and recognition for the framework and I have taught it to 100+ satisfied students in my masterclass "Create massive business impact with your data team."

But I was also challenged. The argument: Having a data strategy is a mistake.

Instead, data should be baked directly into the business strategy. Anything else is redundant.

Others chipped in: “Unless you are a data company then all business functions need to work out how they best support the company objectives”.

Or: “You don’t need a data strategy and you don’t need a marketing strategy. You need a business strategy and a data and marketing action plan to support the business strategy.”

So what’s really going on here?

What we all agreed on

Despite some nice heated takes, everyone agreed on one thing:

Data must serve the business strategy. Full stop.

Whether you call it a data strategy or an action plan doesn’t matter as much as the content and alignment.

So the real question is: How can data teams create real business impact?

Here’s how.

Five ways data can drive business results

Your data team should always be tied to clear business goals. And there are five main ways to make that happen:

→ 1. Increase revenue, growth, or market share

Examples:

• Data products that generate recurring revenue from external customers
• Monetization models built on proprietary data

Note that this includes only examples where data is monetized directly and not through supporting other teams!

→ 2. Decrease cost

Examples:

• Reduce operational expenditures by X$ by automating manual reporting processes
• Reduce operational expenditures by X$ by automating creation of ads

Note that this includes only examples where data products reduce costs directly and not through supporting other teams!

→ 3. Strengthen brand or reputation

Examples:

• Achieving 100% GDPR compliance
• Enhancing transparency in data practices

→ 4. Strengthen key stakeholder relationships

Examples:

• Achieving 100% satisfaction scores from investors on reporting
• Achieving 100% satisfaction scores from other important external partners on reporting (e.g. important suppliers and business partners)

→ 5. Increase organizational knowledge and capability

Examples:

• Building churn prediction models to support retention teams to reduce churn by 10%
• Sending profit margins to Google Ads to reduce customer acquisition costs by 8%

From strategy to action plan

Let’s make this practical.

Say your company’s top objective is to raise a new funding round.

The data team can support this by:

• Ensuring investors receive clear, accurate, and trusted reporting
• Defining a key result like: “Achieve 100% satisfaction score from current investors on reporting”

Or say the company goal is to reduce churn.

The data team could contribute by:

• Building a churn prevention model
• Enabling the retention team to reduce churn by 10%

Or if the company wants to reach profitability in a new market:

• The data team might define a key result like “Support the marketing team reduce cost of acquisition by 15% by providing a Google Ads feed with 99.9% uptime”

This is how data stops being a service desk and starts becoming a driver of outcomes.

What if business goals aren’t clear?

Here’s the trap I see all the time:

Data teams are told to “align to business goals,” but the business hasn’t clearly defined those goals themselves.

In this case, the data team still has an important role to play:

• Create reports that highlight performance gaps
• Include clear target values and run rates in dashboards
• Help business stakeholders define their own KPIs and targets
• Support the introduction of goal setting frameworks such as Objectives and Key Results (OKRs)

When done right, this doesn’t just clarify how data helps. It raises the whole organization’s strategic clarity.

The bottom line

Whether you call it a “data strategy” or an “action plan” is beside the point.

At the end of the discussion we all agreed about what’s important:

• Start with the business goal
• Define how your team contributes directly (or indirectly) to it
• Make sure that contribution is measurable and visible

Don’t waste time thinking about tools and data stacks.

Understand and help solve the most important business problem.

That’s how you stop being reactive and start creating business impact.