How to see ROI, extract value from a data platform and get more from your data consultancy, as explored by our Principal Engineer Advocate, MLG, at Data Decoded 2025.
In today’s world, you don’t run a business unless you make decisions. It doesn’t matter what industry you’re in – utilities, transportation, computing, retail – you are in the business of making decisions.
Whether you’re setting unit-rates of electricity in utilities, organising a fleet in transportation, or optimising a process in the tech/computer industry, the truth is that you are making decisions. And to compete and stay relevant, you try to be data-driven. Because philosophically that’s the only way humans really know how to operate, right?
The Purpose of Being Data-Driven
When I say “data-driven as a business”, I mean this: for many of the decisions we make as a company, as an employer, as a person, we stop trusting “vibes” or our “spidey sense” about a customer’s behaviour, or whether some process will succeed or fail. Instead, we lean on evidence. We use the data. We say, “This person matched profile A rather than B. Therefore, we think this person will buy A rather than B because we have evidence and data to support that.”
You could spend a lifetime writing books on the subtlety of evidence-driven vs bias-driven decisions. But we don’t have the luxury of endless pages. So, let’s unpack what it means to truly become a data-driven organisation.
Clear Decision Boundaries
First, if you’re going to drive value from data, you need to adopt some ground-rules. In particular, you need clear decision boundaries.
I want you to reflect on the worst dashboards you’ve seen: the chart-junk, the yellow warning‐lights, the numbers splattered without interpretation. Those dashboards are not enabling decision-making. They’re confusing.
If you’re going to be evidence-driven, you must know in advance:
- If this number > X, we’ll do Action A.
- If this number < X, we’ll do Action B.
At platform, engineering and analytics levels, this means knowing your decisions before you build the data asset. Because when you build without knowing the outcome, you’ll create a data platform, you’ll move numbers, you’ll host dashboards…
…but you won’t get value.
Data Decoded: Stop Acquisitive, Start Inquisitive
One of the biggest pitfalls in data programmes is what I call an ‘acquisitive data strategy’. That is: “Let’s take every dataset, grab every number, throw it into a warehouse, and then maybe something good will happen.”
No.
You need an inquisitive strategy. Ask yourself:
- What decisions will you support?
- What thresholds matter?
- What outcomes will change?
Then drive your data platform accordingly.
When businesses implement a data platform, they often think: “Here’s our cloud budget, build everything, feed everything into the data warehouse, hook up dashboards, we’ll iterate.” But a platform alone doesn’t give ROI. Tools alone don’t deliver value. Without decision-boundaries, without usage, without an evidence base, you’re just moving data around from one expensive database to another expensive database.
What Does “Value” Really Mean?
So, let’s get into value. You may have heard the initialism “ROI” (return on investment). In the data world, ROI is sometimes misused or misunderstood. Value, when you’re building data platforms or data products, comes in (at least) three flavours: time, money and opportunity. Yes, they’re all about money if you dig into them – but they come at you in different ways.
Time saved
If your data platform or analytics process saves hours, days, weeks of manual reporting or intervention, that frees people to do higher-value work.
Money made
If you can use your data to optimise pricing, reduce cost of goods sold, improve marketing performance, increase conversions, then you’re generating revenue (or preventing loss).
Opportunity unlocked
Sometimes you build a platform that enables new products, new customer segments, new business models – and all of these are valuable too, even if it’s future-facing.
If you’re working as a data engineer, a data platform consultant, or leading a data programme, you must ask: Which one of these am I addressing when building this feature, this platform, this dashboard? If you cannot answer that, you should reconsider your life choices…
…(well, maybe!).
For more insight on the value of data, please read: Why is Data Important for Business?
What We Do Day-to-Day
At the end of the day, what you and I do is we make decisions. Whether you’re in utilities, transportation, tech, retail, you decide. And your ambition is to decide based on evidence, not guesswork. When you embrace data, you move away from trusting your “gut” to saying: “Here’s the evidence, let’s act.”
To become data-driven means that for many of the decisions now, as a company, we’re going to stop using vibes, stop relying on “this customer might buy” because our spidey sense tells us so. Instead we say: “Look at the data. Based on this profile, we believe they will buy A, not B.” Because we have the evidence.
That’s the first of my Data Decoded series finished, but there’s plenty more like this in the second blog: The Four Pillars of a Data Platform. You can also send your questions to me or speak with the rest of the Oakland consulting team by getting in touch – we’d love to hear from you.
